Approach Success Research Articles

일반유아의 도전행동 개선을 위한 개별화교육 지원팀의 효과

Objectives The purpose of this study was to identify the competencies of occupational therapists as members of the individualized education team and to apply individualized education to children exhibiting challenging behaviors, thereby reducing the children's challenging behaviors and alleviating the educational difficulties faced by classroom teachers. Methods This 7-week study involved a 3-year-old boy in D Metropolitan City, aiming to create an individualized education plan through consultations with a specialized team including an occupational therapist and other professionals. Using ABC behavior charts and rating scales, we established and implemented short and long-term goals. The homeroom teacher applied these strategies three times a week, following guidelines designed to address the child's challenging behaviors. Results Following the intervention, notable improvements were observed in the child's behavior, with significant reductions in challenge behaviors and anxiety levels, as tracked by the ABC behavior chart and rating scales. Short-term goals showed marked progress, demonstrating the effectiveness of the tailored strategies. Positive feedback from the homeroom teacher and director highlighted the structured approach's success in addressing the child's needs and the potential benefits of professional guidance in educational settings. Conclusions The role of the individualized education support team for challenging behaviors in typical children was found to be effective in reducing challenging behaviors, and the necessity of the occupational therapist's role as a member of the individualized education team was confirmed. This study is a pilot study focusing on a single child, and future research aims to expand to various children to examine the impact of occupational therapists on challenging behaviors in typical children.

INTERWEAVING INDONESIAN LOCAL WISDOMS AND SYNCHRONIZED VIRTUAL LEARNING: STUDENTS’ EXPERIENCE IN ESP

The research delves into integrating Indonesian local wisdom, specifically Pancasila, within synchronized virtual learning for English for Specific Purposes (ESP), aiming to unveil students' experiences and assess the impact on presentation skill development. Thirty students participated in a 13-session Business English presentation course, with Pancasila embedded in the virtual learning mode. Data encompassed closed questionnaires and pretest/post-test scores, analyzed qualitatively and quantitatively. The findings underscore the intervention's efficacy, notably enhancing students' comprehension of Pancasila's cultural significance and augmenting their presentation skills. Notably, improvements were observed in structure, delivery, and gesture, affirming the approach's success in deepening cultural understanding while refining practical abilities. Quantitative analysis revealed shifts in presentation skill scores pre and post-intervention. While medium scores declined, low and high score categories exhibited marked changes, indicative of substantial advancements in presentation proficiency across skill domains. In conclusion, merging Pancasila into synchronized virtual learning yielded notable benefits, aligning cultural content with skill-focused education. This integration not only enriched cultural appreciation but also honed crucial presentation skills. These outcomes accentuate the potential of targeted educational strategies in harmonizing cultural knowledge and skill development within higher education settings, fostering holistic learning experiences. The study advocates for continued exploration and implementation of similar integrative approaches, emphasizing their value in enhancing both cultural understanding and practical skill acquisition among students in specialized learning contexts.

Vision Transformers for Breast Cancer Human Epidermal Growth Factor Receptor 2 Expression Staging without Immunohistochemical Staining

Accurate staging of human epidermal growth factor receptor 2 (HER2) expression is vital for evaluating breast cancer treatment efficacy. However, it typically involves costly and complex immunohistochemical staining, along with hematoxylin and eosin staining. This work presents customized vision transformers for staging HER2 expression in breast cancer using only hematoxylin and eosin-stained images. The proposed algorithm comprised three modules: a localization module for weakly localizing critical image features using spatial transformers, an attention module for global learning via vision transformers, and a loss module to determine proximity to a HER2 expression level based on input images by calculating ordinal loss. Results, reported with 95% CIs, reveal the proposed approach's success in HER2 expression staging: area under the receiver operating characteristic curve, 0.9202±0.01; precision, 0.922±0.01; sensitivity, 0.876±0.01; and specificity, 0.959±0.02 over fivefold cross-validation. Comparatively, this approach significantly outperformed conventional vision transformer models and state-of-the-art convolutional neural network models (P<0.001). Furthermore, it surpassed existing methods when evaluated on an independent test data set. This work holds great importance, aiding HER2 expression staging in breast cancer treatment while circumventing the costly and time-consuming immunohistochemical staining procedure, thereby addressing diagnostic disparities in low-resource settings and low-income countries.

Basis transform in linear switched system models from input–output data

SummaryThis article addresses the problem of basis correction in the context of linear switched‐system (LSS) identification from input–output data. It is often the case that identification algorithms for the LSSs from input–output data operate locally. The local submodel estimates, identified individually by subspace algorithms from the input‐output data, reside in different‐state bases, which mandates performing a basis correction that facilitates their coherent patching for the ultimate goal of performing output predictions for arbitrary inputs and switching sequences. We formulate a persistence of excitation condition for the inputs and the switching sequences that guarantees the presented approach's success. These conditions are mild in nature, which proves the practicality of the devised algorithm. We supplement the theoretical findings with an elaborating numerical simulation example.

Photoalkylation/-arylation of ortho-Diketones with Unactivated Organic Halides

A new method for conducting a reductive alkylation/arylation of 1,2-diketones using visible light and unactivated organic halides is presented in this article. This technique does not require a photocatalyst and employs Et3N, a tertiary amine, as a promoter. This amine aids in generating a ketyl radical and an α-aminoalkyl radical, which engages in a C-X bond activation via a halogen atom transfer process (XAT). This approach's success hinges on utilizing Et3N as the promoter. This article's mild and straightforward protocol allows for significantly expanding organic halide substrates, including primary, secondary, and aromatic organic halides and various functional groups.

Methodological Reflections of a Student- and Community-based Partnership on Operationalizing a Community-based Participatory Research Model: Recommendations for Building, Securing, and Sustaining Partnerships.

Community-based participatory research (CBPR) is an approach that values community expertise and ownership in creating knowledge. This approach's success is challenged by inherent cultural imbalances, making it difficult to sustain partnerships and build from what has been learned from a project as it develops. As student researchers and community members, we reflected on the challenges in CBPR and gave guidance to future novice researchers pursuing CBPR. From the application of an initial CBPR model as a framework to our partnership, we propose empirical avenues to continuously adapt the CBPR approach. A CBPR partnership between McGill's Family Medicine Graduate Student Society and Share the Warmth, a community-based organization aiming to fight poverty and hunger, was formed to collaboratively assess a music program offered in a socioeconomically disadvantaged community. The partnership process was based on a model that we conceptualized in three phases of our framework: building, securing, and sustaining. We reflect on the facilitators and challenges of this project and propose solutions to overcome identified barriers within the context of our partnership. We highlight the importance of integrating student partners in the community, reevaluating formal research agreements, and coordinating the transition of new partners in this adaptive CBPR model. We argue that this systematic and reflexive process has made the model especially useful as a framework for student and community partnerships. We propose adaptive components to the CBPR model. Our recommendations could help other partnerships cultivate CBPR to be more applicable in community health research.

Formational bounds of link prediction in collaboration networks

Link prediction in collaboration networks is often solved by identifying structural properties of existing nodes that are disconnected at one point in time, and that share a link later on. The maximally possible recall rate or upper bound of this approach's success is capped by the proportion of links that are formed among existing nodes embedded in these properties. Consequentially, sustained ties as well as links that involve one or two new network participants are typically not predicted. The purpose of this study is to highlight formational constraints that need to be considered to increase the practical value of link prediction methods for collaboration networks. In this study, we identify the distribution of basic link formation types based on four large-scale, over-time collaboration networks, showing that current link predictors can maximally anticipate around 25% of links that involve at least one prior network member. This implies that for collaboration networks, increasing the accuracy of computational link prediction solutions may not be a reasonable goal when the ratio of collaboration ties that are eligible to the classic link prediction process is low.

Synthesis of divide and conquer parallelism for loops

Divide-and-conquer is a common parallel programming skeleton supported by many cross-platform multithreaded libraries, and most commonly used by programmers for parallelization. The challenges of producing (manually or automatically) a correct divide-and-conquer parallel program from a given sequential code are two-fold: (1) assuming that a good solution exists where individual worker threads execute a code identical to the sequential one, the programmer has to provide the extra code for dividing the tasks and combining the partial results (i.e. joins), and (2) the sequential code may not be suitable for divide-and-conquer parallelization as is, and may need to be modified to become a part of a good solution. We address both challenges in this paper. We present an automated synthesis technique to synthesize correct joins and an algorithm for modifying the sequential code to make it suitable for parallelization when necessary. This paper focuses on class of loops that traverse a read-only collection and compute a scalar function over that collection. We present theoretical results for when the necessary modifications to sequential code are possible, theoretical guarantees for the algorithmic solutions presented here, and experimental evaluation of the approach's success in practice and the quality of the produced parallel programs.

Learning in Harmonic Serialism and the necessity of a richer base

This paper reassesses the hypothesis that early phonotactic learning of constraint-based grammars relies on the Identity Map – i.e. it uses observed surface forms as the inputs which cause errors and drive learning via constraint reranking. We argue that this approach's success is closely tied to Optimality Theory's fully parallel grammatical evaluation. In the constraint-based derivational framework of Harmonic Serialism (HS; McCarthy 2000, 2007b), reliance on observed surface forms as inputs can block the discovery of ‘hidden rankings’ between markedness constraints, preventing the learner from discovering a restrictive grammar. This paper illustrates the problem, using a pattern of positional vowel restrictions in Punu (Kwenzi Mikala 1980), and considers the role of various learning assumptions. We conclude that hidden rankings are a fundamental obstacle to restrictive error-driven learning in any HS-like framework, and that learning in such frameworks inevitably requires consideration of some unattested surface forms as inputs, even at the earliest learning stages.

Hearing loss among survivors of childhood brain tumors treated with an irradiation‐sparing approach

Intensive, irradiation-sparing chemotherapy regimens for malignant brain tumors have improved survival and neurocognitive outcomes in very young children. Platinum compounds are pivotal to this approach's success but are associated with hearing loss that markedly reduces quality of life for survivors. The purpose of this study was to determine the prevalence and severity of ototoxicity associated with Head Start and similar irradiation-sparing regimens. A retrospective cohort study was conducted of children treated for malignant brain tumors at Children's Hospital Los Angeles using irradiation-sparing regimens. Patient and treatment characteristics were ascertained. Primary outcomes were post-treatment hearing status, need for hearing aids, and hearing threshold change. Twenty-nine patients were evaluable. The most common diagnosis was medulloblastoma (n = 14). The median age at diagnosis was 2.0 years (range, 0.2-9.2). Median time from diagnosis to most recent hearing assessment was 1.1 years (mean 2.4; range, 0.2-17.5). Cumulative cisplatin and carboplatin dose was 281 ± 88 mg/m(2) and 1,205 ± 277 mg/m(2) , respectively. All patients had aminoglycoside exposure. Following treatment, 18 patients (62.1%) had abnormal hearing and 11 (37.9%) required hearing aids. At 4,000 Hz, statistically significant hearing loss was documented in the range of 30-40 dB. While eliminating cranial irradiation has dramatically improved survival and neurocognitive and neuroendocrine outcomes in this population, clinically significant hearing loss is now the leading late effect due to the necessity of platinum-based chemotherapy. Our results document the need for audiometric monitoring and developing otoprotective strategies in this vulnerable population.

Brain volumetry: An active contour model-based segmentation followed by SVM-based classification

In this paper a novel automatic approach to identify brain structures in magnetic resonance imaging (MRI) is presented for volumetric measurements. The method is based on the idea of active contour models and support vector machine (SVM) classifiers. The main contributions of the presented method are effective modifications on brain images for active contour model and extracting simple and beneficial features for the SVM classifier. The segmentation process starts with a new generation of active contour models, i.e., vector field convolution (VFC) on modified brain images. VFC results are brain images with the least non-brain regions which are passed on to the SVM classification. The SVM features are selected according to the structure of brain tissues, gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). SVM classifiers are trained for each brain tissue based on the set of extracted features. Although selected features are very simple, they are both sufficient and tissue separately effective. Our method validation is done using the gold standard brain MRI data set. Comparison of the results with the existing algorithms is a good indication of our approach's success.

Team Product Reviews: A Means of Improving Product Quality and Acceptance

Characteristics of both the life cycles and development processes of products and “systems” are surprisingly similar. These similarities offer a unique opportunity for the transfer of successful approaches from one discipline to the other. In this article, Kenneth Kozar describes a technique called team product reviews that he has used successfully in improving the quality and organizational acceptance of emerging systems. The article links the technique to new products development practices, identifies a variety of factors critical to the approach's success, and argues that the team review process helps to assure quality and user acceptance. In addition, the article provides guidelines for proper review behavior and includes examples of both successful and unsuccessful implementations of the technique. This cross‐disciplinary sharing represents an attempt to avoid missed deadlines, overrun budgets, and destructive human behavior during the new products development process.

Team product reviews: A means of improving product quality and acceptance

Characteristics of both the life cycles and development processes of products and “systems” are surprisingly similar. These similarities offer a unique opportunity for the transfer of successful approaches from one discipline to the other. In this article, Kenneth Kozar describes a technique called team product reviews that he has used successfully in improving the quality and organizational acceptance of emerging systems. The article links the technique to new products development practices, identifies a variety of factors critical to the approach's success, and argues that the team review process helps to assure quality and user acceptance. In addition, the article provides guidelines for proper review behavior and includes examples of both successful and unsuccessful implementations of the technique. This cross-disciplinary sharing represents an attempt to avoid missed deadlines, overrun budgets, and destructive human behavior during the new products development process.