Parents\u27 Knowledge and Perceptions Regarding Their Rights During the IEP Process

This paper aimed to examine what parents of children aged three to six understand about their rights during the IEP process. Literature from the past ten years (2002-2012) revealed that parents had some understanding of the IEP process including planning and contributing to development of IEP documents and participating in IEP meetings. Findings regarding parents being valued during the IEP process varied. In terms of the results of communication strategies utilized during the IEP process, literature showed that parents understood terminology used during IEP meetings better during the subsequent ones than the initial one. However, written documents such as the prior written notice were often difficult for parents to understand. Limitations and implications are addressed along with recommendations for future studies to assess the generalizability of the current findings

Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task.

Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions' temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions' neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed

Solving Conflict in Academic Contexts: a Comparison of U.S. and Taiwanese College Students

In today’s globalized society with intense interaction between and among cultures, cross cultural understanding is becoming of crucial importance for successful communication. Whenever there is communication among people from different cultures, disagreement, argument and interpersonal conflict may occur. For this reason, the study of cultural differences in conflict resolution is of great value to society at large. Yet, the number of studies that have examined conflict resolution approaches across cultures is insufficient. This study sought to contribute to this area of research by investigating conflict resolution strategies employed by US and Taiwanese college students in academic contexts and the motives underlying participants’ preferences for certain strategies. The US and Taiwanese samples were chosen as representative of two different cultures, individualistic and collectivistic, respectively. Specifically, 15 US college students and 15 Taiwanese college students were selected from a US college campus. The Taiwanese group included students who have spent less than one year in the United States. The instrument consisted of a written questionnaire with four conflict scenarios and an audio-recorded interview with six randomly selected participants from both groups. The data were analyzed through descriptive statistics, Discriminant Function Analysis and content analysis. Both the descriptive and the Discriminant Function analyses showed that the US college students were significantly associated with the use of direct or avoidance conflict resolution approaches, while the Taiwanese college students showed a significantly higher inclination towards an indirect approach often involving a third party. The qualitative results revealed that the motives underlying the participants’ responses stemmed from both cultural and personal factors, such as individualistic and collectivistic values as well as family and religious background

MuraNet: Multi-task Floor Plan Recognition with Relation Attention

The recognition of information in floor plan data requires the use of detection and segmentation models. However, relying on several single-task models can result in ineffective utilization of relevant information when there are multiple tasks present simultaneously. To address this challenge, we introduce MuraNet, an attention-based multi-task model for segmentation and detection tasks in floor plan data. In MuraNet, we adopt a unified encoder called MURA as the backbone with two separated branches: an enhanced segmentation decoder branch and a decoupled detection head branch based on YOLOX, for segmentation and detection tasks respectively. The architecture of MuraNet is designed to leverage the fact that walls, doors, and windows usually constitute the primary structure of a floor plan's architecture. By jointly training the model on both detection and segmentation tasks, we believe MuraNet can effectively extract and utilize relevant features for both tasks. Our experiments on the CubiCasa5k public dataset show that MuraNet improves convergence speed during training compared to single-task models like U-Net and YOLOv3. Moreover, we observe improvements in the average AP and IoU in detection and segmentation tasks, respectively.Our ablation experiments demonstrate that the attention-based unified backbone of MuraNet achieves better feature extraction in floor plan recognition tasks, and the use of decoupled multi-head branches for different tasks further improves model performance. We believe that our proposed MuraNet model can address the disadvantages of single-task models and improve the accuracy and efficiency of floor plan data recognition.Comment: Document Analysis and Recognition - ICDAR 2023 Workshops. ICDAR 2023. Lecture Notes in Computer Science, vol 14193. Springer, Cha

Fuzzy Environment Mapping for Robot Navigation Based on Grid Computing

In order to navigate autonomously, a mobile robot needs to build an environment map where the robot is navigating. Currently, the sensors are mounted on the robot to detect if the obstacles exist and then the map immediate surrounding of the robot is built to help for navigation path planning. The map created by this method is a local map that may cause global navigation problem which a global coverage map is needed to solve such a problem. In this study, a sensor network is deployed for building global environment map. All the sensor locations are assumed known. The navigation space is divided into grids and a grid is to be detected if obstacles exist by one or a number of sensors. Fuzzy set concept is used to introduce a tool useful for sensor perception. Those sensors work as a team to explore all the space and then the global fuzzy map is constructed. The experiments show that the fuzzy map is more practical and helps the path planning problem to be solved more efficiently

Structural insights into the gating of DNA passage by the topoisomerase II DNA-gate.

Type IIA topoisomerases (Top2s) manipulate the handedness of DNA crossovers by introducing a transient and protein-linked double-strand break in one DNA duplex, termed the DNA-gate, whose opening allows another DNA segment to be transported through to change the DNA topology. Despite the central importance of this gate-opening event to Top2 function, the DNA-gate in all reported structures of Top2-DNA complexes is in the closed state. Here we present the crystal structure of a human Top2 DNA-gate in an open conformation, which not only reveals structural characteristics of its DNA-conducting path, but also uncovers unexpected yet functionally significant conformational changes associated with gate-opening. This structure further implicates Top2's preference for a left-handed DNA braid and allows the construction of a model representing the initial entry of another DNA duplex into the DNA-gate. Steered molecular dynamics calculations suggests the Top2-catalyzed DNA passage may be achieved by a rocker-switch-type movement of the DNA-gate

STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data

Longitudinal neuroimaging data plays an important role in mapping the neural developmental profile of major neuropsychiatric and neurodegenerative disorders and normal brain. The development of such developmental maps is critical for the prevention, diagnosis, and treatment of many brain-related diseases. The aim of this paper is to develop a spatio-temporal Gaussian process (STGP) framework to accurately delineate the developmental trajectories of brain structure and function, while achieving better prediction by explicitly incorporating the spatial and temporal features of longitudinal neuroimaging data. Our STGP integrates a functional principal component model (FPCA) and a partition parametric space-time covariance model to capture the medium-to-large and small-to-medium spatio-temporal dependence structures, respectively. We develop a three-stage efficient estimation procedure as well as a predictive method based on a kriging technique. Two key novelties of STGP are that it can efficiently use a small number of parameters to capture complex non-stationary and non-separable spatio-temporal dependence structures and that it can accurately predict spatio-temporal changes. We illustrate STGP using simulated data sets and two real data analyses including longitudinal positron emission tomography data from the Alzheimers Disease Neuroimaging Initiative (ADNI) and longitudinal lateral ventricle surface data from a longitudinal study of early brain development

Modulation of Locomotion and Reproduction by FLP Neuropeptides in the Nematode Caenorhabditis elegans

Neuropeptides function in animals to modulate most, if not all, complex behaviors. In invertebrates, neuropeptides can function as the primary neurotransmitter of a neuron, but more generally they co-localize with a small molecule neurotransmitter, as is commonly seen in vertebrates. Because a single neuron can express multiple neuropeptides and because neuropeptides can bind to multiple G protein-coupled receptors, neuropeptide actions increase the complexity by which the neural connectome can be activated or inhibited. Humans are estimated to have 90 plus neuropeptide genes; by contrast, nematodes, a relatively simple organism, have a slightly larger complement of neuropeptide genes. For instance, the nematode Caenorhabditis elegans has over 100 neuropeptide-encoding genes, of which at least 31 genes encode peptides of the FMRFamide family. To understand the function of this large FMRFamide peptide family, we isolated knockouts of different FMRFamide-encoding genes and generated transgenic animals in which the peptides are overexpressed. We assayed these animals on two basic behaviors: locomotion and reproduction. Modulating levels of different neuropeptides have strong as well as subtle effects on these behaviors. These data suggest that neuropeptides play critical roles in C. elegans to fine tune neural circuits controlling locomotion and reproduction