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Obeid, Iyad ; Picone, Joseph ; Selesnick, Ivan (Ed.)The Neural Engineering Data Consortium (NEDC) is developing a large open source database of high-resolution digital pathology images known as the Temple University Digital Pathology Corpus (TUDP) . Our long-term goal is to release one million images. We expect to release the first 100,000 image corpus by December 2020. The data is being acquired at the Department of Pathology at Temple University Hospital (TUH) using a Leica Biosystems Aperio AT2 scanner  and consists entirely of clinical pathology images. More information about the data and the project can be found in Shawki et al. . We currently have a National Science Foundation (NSF) planning grant  to explore how best the community can leverage this resource. One goal of this poster presentation is to stimulate community-wide discussions about this project and determine how this valuable resource can best meet the needs of the public. The computing infrastructure required to support this database is extensive  and includes two HIPAA-secure computer networks, dual petabyte file servers, and Aperio’s eSlide Manager (eSM) software . We currently have digitized over 50,000 slides from 2,846 patients and 2,942 clinical cases. There is an average of 12.4 slides per patient and 10.5 slides per casemore »
Functional Resistance Training to Improve Knee Strength and Function After Acute Anterior Cruciate Ligament Reconstruction: A Case Study
Thigh muscle weakness after anterior cruciate ligament reconstruction (ACLR) can persist after returning to activity. While resistance training can improve muscle function, “nonfunctional” training methods are not optimal for inducing transfer of benefits to activities such as walking. Here, we tested the feasibility of a novel functional resistance training (FRT) approach to restore strength and function in an individual with ACLR.
FRT would improve knee strength and function after ACLR.
Level of Evidence:
A 15-year-old male patient volunteered for an 8-week intervention where he performed 30 minutes of treadmill walking, 3 times per week, while wearing a custom-designed knee brace that provided resistance to the thigh muscles of his ACLR leg. Thigh strength, gait mechanics, and corticospinal and spinal excitability were assessed before and immediately after the 8-week intervention. Voluntary muscle activation was evaluated immediately after the intervention.
Knee extensor and flexor strength increased in the ACLR leg from pre- to posttraining (130 to 225 N·m [+74%] and 44 to 88 N·m [+99%], respectively) and increases in between-limb extensor and flexor strength symmetry (45% to 92% [+74%] and 47% to 72% [+65%], respectively) were also noted. After the intervention, voluntary muscle activation in the ACLR legmore »
A full 8 weeks of FRT that targeted both quadriceps and hamstring muscles lead to improvements in strength and gait, suggesting that FRT may constitute a promising and practical alternative to traditional methods of resistance training.
FRT may serve as a viable approach to improve knee strength and function after ACL reconstruction.
Obeid, I. (Ed.)The Neural Engineering Data Consortium (NEDC) is developing the Temple University Digital Pathology Corpus (TUDP), an open source database of high-resolution images from scanned pathology samples , as part of its National Science Foundation-funded Major Research Instrumentation grant titled “MRI: High Performance Digital Pathology Using Big Data and Machine Learning” . The long-term goal of this project is to release one million images. We have currently scanned over 100,000 images and are in the process of annotating breast tissue data for our first official corpus release, v1.0.0. This release contains 3,505 annotated images of breast tissue including 74 patients with cancerous diagnoses (out of a total of 296 patients). In this poster, we will present an analysis of this corpus and discuss the challenges we have faced in efficiently producing high quality annotations of breast tissue. It is well known that state of the art algorithms in machine learning require vast amounts of data. Fields such as speech recognition , image recognition  and text processing  are able to deliver impressive performance with complex deep learning models because they have developed large corpora to support training of extremely high-dimensional models (e.g., billions of parameters). Other fields that do notmore »
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Undergraduate research has emerged as a high-impact approach that can be used to enhance student engagement and to enrich student learning experiences. It is observed in the literature that undergraduate research can have an impact on student retention, and possibly attract women and ethnic minorities to science-related disciplines while playing an important role in the determination of career paths for participating students. While there are multiple studies on the impact of undergraduate research in social sciences and sciences, there is limited literature in the engineering disciplines. The limited volume of literature may be attributed to multiple reasons such as a significant emphasis on mathematics and science in the first two years of engineering curriculum, a strict sequential degree path, and a lack of flexibility in the program requirements. Engineering students often report difficulty in relating the theoretical content of the first few semesters to actual engineering applications. This study proposes the introduction of undergraduate research as a possible means of overcoming these student perceptions by introducing students to well-defined research projects at an early stage of their undergraduate degree program. The primary focus of this study is to understand student perceptions about the efficacy of undergraduate research in the engineeringmore »