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66. Researcher or Crowd Member? Why not both! The Open Research Knowledge Graph for Applying and Communicating CrowdRE Research

Author

Karras, Oliver, Groen, Eduard C., Khan, Javed Ali, and Auer, Sören

Subjects
Computer Science - Digital Libraries, Computer Science - Software Engineering
Abstract

In recent decades, there has been a major shift towards improved digital access to scholarly works. However, even now that these works are available in digital form, they remain document-based, making it difficult to communicate the knowledge they contain. The next logical step is to extend these works with more flexible, fine-grained, semantic, and context-sensitive representations of scholarly knowledge. The Open Research Knowledge Graph (ORKG) is a platform that structures and interlinks scholarly knowledge, relying on crowdsourced contributions from researchers (as a crowd) to acquire, curate, publish, and process this knowledge. In this experience report, we consider the ORKG in the context of Crowd-based Requirements Engineering (CrowdRE) from two perspectives: (1) As CrowdRE researchers, we investigate how the ORKG practically applies CrowdRE techniques to involve scholars in its development to make it align better with their academic work. We determined that the ORKG readily provides social and financial incentives, feedback elicitation channels, and support for context and usage monitoring, but that there is improvement potential regarding automated user feedback analyses and a holistic CrowdRE approach. (2) As crowd members, we explore how the ORKG can be used to communicate scholarly knowledge about CrowdRE research. For this purpose, we curated qualitative and quantitative scholarly knowledge in the ORKG based on papers contained in two previously published systematic literature reviews (SLRs) on CrowdRE. This knowledge can be explored and compared interactively, and with more data than what the SLRs originally contained. Therefore, the ORKG improves access and communication of the scholarly knowledge about CrowdRE research. For both perspectives, we found the ORKG to be a useful multi-tool for CrowdRE research., Comment: Accepted for publication at 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)

Published
2021

78. MYOD-SKP2 axis boosts tumorigenesis in fusion negative rhabdomyosarcoma by preventing differentiation through p57Kip2 targeting

Author

Pomella, Silvia, Cassandri, Matteo, D’Archivio, Lucrezia, Porrazzo, Antonella, Cossetti, Cristina, Phelps, Doris, Perrone, Clara, Pezzella, Michele, Cardinale, Antonella, Wachtel, Marco, Aloisi, Sara, Milewski, David, Colletti, Marta, Sreenivas, Prethish, Walters, Zoë S., Barillari, Giovanni, Di Giannatale, Angela, Milano, Giuseppe Maria, De Stefanis, Cristiano, Alaggio, Rita, Rodriguez-Rodriguez, Sonia, Carlesso, Nadia, Vakoc, Christopher R., Velardi, Enrico, Schafer, Beat W., Guccione, Ernesto, Gatz, Susanne A., Wasti, Ajla, Yohe, Marielle, Ignatius, Myron, Quintarelli, Concetta, Shipley, Janet, Miele, Lucio, Khan, Javed, Houghton, Peter J., Marampon, Francesco, Gryder, Berkley E., De Angelis, Biagio, Locatelli, Franco, and Rota, Rossella

Published
2023
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81. Discovery of pyrrolo[2,1-f][1,2,4]triazine-based inhibitors of adaptor protein 2-associated kinase 1 for the treatment of pain

Author

Dzierba, Carolyn D., Dasgupta, Bireshwar, Karageorge, George, Kostich, Walter, Hamman, Brian, Allen, Jason, Esposito, Kim M., Padmanabha, Ramesh, Grace, James, Lentz, Kimberley, Morrison, John, Morgan, Daniel, Easton, Amy, Bourin, Clotilde, Browning, Marc R., Rajamani, Ramkumar, Good, Andrew, Parker, Dawn D., Muckelbauer, Jodi K., Khan, Javed, Camac, Daniel, Ghosh, Kaushik, Halan, Vivek, Lippy, Jonathan S., Santone, Kenneth S., Denton, R. Rex, Westphal, Ryan, Bristow, Linda J., Conway, Charles M., Bronson, Joanne J., and Macor, John E.

Published
2023
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89. Identifying and Modeling Security Threats for IoMT Edge Network using Markov Chain and Common Vulnerability Scoring System (CVSS)

Author

Allouzi, Maha Ali and Khan, Javed I.

Subjects
Computer Science - Cryptography and Security
Abstract

In this work, we defined an attack vector for networks utilizing the Internet of Medical Things (IoMT) devices and compute the probability distribution of IoMT security threats based on Markov chain and Common Vulnerability Scoring System (CVSS). IoMT is an emerging technology that improves patients' quality of life by permitting personalized e-health services without restrictions on time and site. The IoMT consists of embedded objects, sensors, and actuators that transmit and receive medical data. These Medical devices are vulnerable to different types of security threats, and thus, they pose a significant risk to patient's privacy and safety. Because security is a critical factor for successfully merging IoMT into pervasive healthcare systems, there is an urgent need for new security mechanisms to prevent threats on the IoMT edge network. Toward this direction, the first step is defining an attack vector that an attacker or unauthorized user can take advantage of to penetrate and tamper with medical data. In this article, we specify a threat model for the IoMT edge network. We identify any vulnerabilities or weaknesses within the IoMT network that allow unauthorized privileges and threats that can utilize these weaknesses to compromise the IoMT edge network. Finally, we compute the probability distribution of IoMT threats based on the Markov transition probability matrix.

Published
2021

90. Genomic and Transcriptomic Analysis of Relapsed and Refractory Childhood Solid Tumors Reveals a Diverse Molecular Landscape and Mechanisms of Immune Evasion

Author

Byron, Sara A, Hendricks, William PD, Nagulapally, Abhinav B, Kraveka, Jacqueline M, Ferguson, William S, Brown, Valerie I, Eslin, Don E, Mitchell, Deanna, Cornelius, Albert, Roberts, William, Isakoff, Michael S, Oesterheld, Javier E, Wada, Randal K, Rawwas, Jawhar, Neville, Kathleen, Zage, Peter E, Harrod, Virginia L, Bergendahl, Genevieve, VanSickle, Elizabeth, Dykema, Karl, Bond, Jeffrey, Chou, Hsien-Chao, Wei, Jun S, Wen, Xinyu, Reardon, Hue V, Roos, Alison, Nasser, Sara, Izatt, Tyler, Enriquez, Daniel, Hegde, Apurva M, Cisneros, Faith, Christofferson, Austin, Turner, Bryce, Szelinger, Szabolcs, Keats, Jonathan J, Halperin, Rebecca F, Khan, Javed, Saulnier Sholler, Giselle L, and Trent, Jeffrey M

Subjects
Genetics, Pediatric, Cancer, Rare Diseases, Human Genome, Pediatric Cancer, Clinical Research, Good Health and Well Being, Adolescent, Adult, Antineoplastic Combined Chemotherapy Protocols, Biomarkers, Tumor, Child, Child, Preschool, Drug Resistance, Neoplasm, Female, Follow-Up Studies, Gene Expression Regulation, Neoplastic, Humans, Immune Evasion, Infant, Longitudinal Studies, Male, Mutation, Neoplasm Recurrence, Local, Neoplasms, Prognosis, Survival Rate, Transcriptome, Young Adult, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Children with treatment-refractory or relapsed (R/R) tumors face poor prognoses. As the genomic underpinnings driving R/R disease are not well defined, we describe here the genomic and transcriptomic landscapes of R/R solid tumors from 202 patients enrolled in Beat Childhood Cancer Consortium clinical trials. Tumor mutational burden (TMB) was elevated relative to untreated tumors at diagnosis, with one-third of tumors classified as having a pediatric high TMB. Prior chemotherapy exposure influenced the mutational landscape of these R/R tumors, with more than 40% of tumors demonstrating mutational signatures associated with platinum or temozolomide chemotherapy and two tumors showing treatment-associated hypermutation. Immunogenomic profiling found a heterogenous pattern of neoantigen and MHC class I expression and a general absence of immune infiltration. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology clusters associated with development, immune signaling, and cellular signaling pathways. While the landscapes of these R/R tumors reflected those of their corresponding untreated tumors at diagnosis, important exceptions were observed, suggestive of tumor evolution, treatment resistance mechanisms, and mutagenic etiologies of treatment. SIGNIFICANCE: Tumor heterogeneity, chemotherapy exposure, and tumor evolution contribute to the molecular profiles and increased mutational burden that occur in treatment-refractory and relapsed childhood solid tumors.

Published
2021

91. Cavitation-Based Processes for Water and Wastewater Treatment

Author

Fedorov, Kirill, Cako, Elvana, Dinesh, Kumaravel, Soltani, Reza Darvishi Cheshmeh, Wang, Zhaohui, Khan, Javed Ali, Boczkaj, Grzegorz, Barceló, Damià, Series Editor, de Boer, Jacob, Editorial Board Member, Kostianoy, Andrey G., Series Editor, Garrigues, Philippe, Editorial Board Member, Hutzinger, Otto, Founding Editor, Gu, Ji-Dong, Editorial Board Member, Jones, Kevin C., Editorial Board Member, Knepper, Thomas P., Editorial Board Member, Negm, Abdelazim M., Editorial Board Member, Newton, Alice, Editorial Board Member, Nghiem, Duc Long, Editorial Board Member, Garcia-Segura, Sergi, Editorial Board Member, and Nasr, Mahmoud, editor

Published
2023
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92. A Research-Practice Partnership Approach for Co-Designing a Culturally Responsive Computer Science Curriculum for Upper Elementary Students

Author

Novak, Elena and Khan, Javed I.

Abstract

Implementing computer science education in an elementary classroom is at the forefront of computing education. Nevertheless, the literature on K-12 Computer Science (CS) education offers limited guidance for developing elementary CS curricula that lead to multiple career paths through project-based learning. Particularly, more research is needed on culturally responsive elementary school computing that leverages students' cultural references to create a more equitable CS education that acknowledges one's identity, culture, or background in the curriculum planning. This paper offers an approach for designing culturally responsive computing for upper elementary students from a highly diverse, low socio-economic school district using a research-practice approach. The approach can be adapted for other schools that face unique diversity and curricular challenges.

Published
2022
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