Creating an Inclusive, Vibrant Learning Environment within a Large, Software Engineering program - Experiential Learning Experiences Created for Students, Faculty, and Senior Design Coaches & Sponsors This present...
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Creating an Inclusive, Vibrant Learning Environment within a Large, Software Engineering program - Experiential Learning Experiences Created for Students, Faculty, and Senior Design Coaches & Sponsors This presentation describes several initiatives currently underway within a large software engineering (SE) department at a private university within the northeast US to positively affect levels of inclusiveness within the department's learning environment. Information gathered from faculty, staff, student interviews and focus group discussions, as well as a department goal to improve female freshmen retention in the SE major motivated the SE department chair, departmental academic advisors and faculty, and the college's women in computing director to launch this set of aligned activities in collaboration with the NSF ADVANCE funded program (NSF #1209115) at the university level. The resulting activities ideally enhance diversity and inclusion for students from all underrepresented groups in the program with a focus on groups based on gender. Four experiential learning experiences have been created and concurrently implemented within the SE department to promote an inclusive academic environment. These include: (1) faculty targeted discussions and summer readings, (2) an interactive workshop designed for all first year SE students, (3) a workshop created for the coaches and sponsors, most of who are not regular RIT employees, who directly mentor student teams for the two‐semester senior project course, and (4) the development of a resource flowchart which supports students, faculty, and staff in maintaining an inclusive learning environment within the department. The approach used in creating each is adaptive and the four resulting products are multi‐faceted in regards to target audience, modality of learning experience, and composition of creation team. Furthermore, we will discuss key metrics aligned with the department's goal to measure impacts resulting from these
The cytokine granulocyte-macrophage-colony stimulating factor (GM-CSF) possesses the capacity to differentiate monocytes into macrophages (MØs) with opposing functions, namely, proinflammatory M1-like MØs an...
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The cytokine granulocyte-macrophage-colony stimulating factor (GM-CSF) possesses the capacity to differentiate monocytes into macrophages (MØs) with opposing functions, namely, proinflammatory M1-like MØs and immunosuppressive M2-like MØs. Despite the importance of these opposing biological outcomes, the intrinsic mechanism that regulates the functional polarization of MØs under GM-CSF signaling remains elusive. Here, we showed that GM-CSF-induced MØ polarization resulted in the expression of cytokine-inducible SH2-containing protein (CIS) and that CIS deficiency skewed the differentiation of monocytes toward immunosuppressive M2-like MØs. CIS deficiency resulted in hyperactivation of the JAK-STAT5 signaling pathway, consequently promoting downregulation of the transcription factor Interferon Regulatory Factor 8 (IRF8). Loss- and gain-of-function approaches highlighted IRF8 as a critical regulator of the M1-like polarization program. In vivo, CIS deficiency induced the differentiation of M2-like macrophages, which promoted strong Th2 immune responses characterized by the development of severe experimental asthma. Collectively, our results reveal a CIS-modulated mechanism that clarifies the opposing actions of GM-CSF in MØ differentiation and uncovers the role of GM-CSF in controlling allergic inflammation.
During the coronavirus disease 2019(COVID-19)pandemic,the Japanese government implemented several infection control measures,such as states of emergency(SoE)and school closures,and encouraged universal masking and han...
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During the coronavirus disease 2019(COVID-19)pandemic,the Japanese government implemented several infection control measures,such as states of emergency(SoE)and school closures,and encouraged universal masking and hand *** activity restrictions and improved hygiene were found to be associated with declines in the incidence of infuenza during the 2019–2020 winter season[1].Prior studies have found that the incidence of seven pediatric infections,such as pharyngoconjunctivitis and varicella,decreased during and after the school closures in Japan[2].As activity restrictions continue to be lifted,there is growing concern that pediatric infections may suddenly return given that the pool of susceptible children increased during the pandemic[3].In this study,we use national infectious disease sentinel data from January 2012 to October 2021 to assess changes in the reported number of pediatric infections in Japan during the COVID-19 *** hypothesize that the reporting of many infectious diseases decreased during the early stages of the pandemic but ultimately returned to normal when activity restrictions were lifted.
The main treatment modality for oropharyngeal cancer (OPC) is radiotherapy, where accurate segmentation of the primary gross tumor volume (GTVp) is essential. However, accurate GTVp segmentation is challenging due to ...
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Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant s...
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This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of '...
Background Advancements in Large Language Models (LLMs) hold transformative potential in healthcare, however, recent work has raised concern about the tendency of these models to produce outputs that display racial or...
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Hierarchical clustering, a traditional clustering method, has been getting attention again. Among several reasons, a credit goes to a recent paper by Dasgupta in 2016 that proposed a cost function that quantitatively ...
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ISBN:
(纸本)9781665445993
Hierarchical clustering, a traditional clustering method, has been getting attention again. Among several reasons, a credit goes to a recent paper by Dasgupta in 2016 that proposed a cost function that quantitatively evaluates hierarchical clustering trees. An important question is how to combine this recent advance with existing successful clustering methods. In this paper, we propose a hierarchical clustering method to minimize the cost function of clustering tree by incorporating existing clustering techniques. First, we developed an ensemble tree-search method that finds an integrated tree with reduced cost by integrating multiple existing hierarchical clustering methods. Second, to operate on large and arbitrary shape data, we designed an efficient hierarchical clustering framework, called integrating divisive and ensemble-agglomerate (IDEA) by combining it with advanced clustering techniques such as nearest neighbor graph construction, divisive-agglomerate hybridization, and dynamic cut tree. The IDEA clustering method showed better performance in minimizing Dasgupta's cost and improving accuracy (adjusted rand index) over existing cost-minimization-based, and density-based hierarchical clustering methods in experiments using arbitrary shape datasets and complex biology-domain datasets.
Background: Automated MRI analysis is limited by low resolution, lack of standardized signal intensity values, and variability in acquisition protocols. Purpose: To develop and evaluate a deep learning model for multi...
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Background: Automated MRI analysis is limited by low resolution, lack of standardized signal intensity values, and variability in acquisition protocols. Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial MRI scans from the UK Biobank, 221 in-house MRI scans, and 1228 CT scans from the TotalSegmentator dataset. A human-in-the-loop annotation workflow was employed, leveraging cross-modality transfer learning from an existing CT segmentation model to segment 40 anatomical structures. The annotation process began with a model based on transfer learning between CT and MR, which was iteratively refined based on manual corrections to predicted segmentations, until the entire training dataset was annotated. The model's performance was evaluated on MRI examinations obtained from the German National Cohort (NAKO) study (n=900) from the AMOS22 dataset (n=60) and from the TotalSegmentator-MRI test data (n=29). The Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) were used to assess segmentation quality, stratified by organ and scan type. The model and its weights will be open-sourced. Results: MRSegmentator demonstrated high accuracy for well-defined organs (lungs: DSC 0.96, heart: DSC 0.94) and organs with anatomic variability (liver: DSC 0.96, kidneys: DSC 0.95). Smaller structures showed lower accuracy (portal/splenic veins: DSC 0.64, adrenal glands: DSC 0.69). On external validation using NAKO data, mean DSC ranged from 0.85 ± 0.08 for T2-HASTE to 0.91 ± 0.05 for in-phase sequences. The model generalized well to CT, achieving mean DSC of 0.84 ± 0.11 on AMOS CT data. Conclusion: MRSegmentator accurately segments 40 anatomical structures in MRI across diverse datasets and imaging protocols, with additional generalizability to CT images. This open-source model will provide a valuable tool for automated multi-organ segmentation in medical
Esophageal dysmotility is identified as a contraindication to lung transplantation at some centers due to increased risks of acute rejection, pulmonary infection, and chronic lung allograft dysfunction. Phosphodiester...
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Esophageal dysmotility is identified as a contraindication to lung transplantation at some centers due to increased risks of acute rejection, pulmonary infection, and chronic lung allograft dysfunction. Phosphodiesterase-type 5 inhibitors (PDE5i) are a cornerstone pharmacotherapy for pulmonary arterial hypertension (PAH) and are known to exert off-target effects that may impact lung transplant candidacy, including impaired esophageal contractility and decreased lower esophageal sphincter tone. We report 2 patients with PAH who were initially declined listing for lung transplantation due to iatrogenic esophageal dysmotility induced by PDE5is. Upon discontinuation of PDE5i therapy, these patients experienced significant improvement in esophageal motility within 14 days and met the criteria for transplant listing at their centers. Recognizing and mitigating the off-target effects of PDE5i medications is critical for maximizing access to transplant for patients with PAH.
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