Awareness, interest, and preferences of primary care providers in using point-of-care cancer screening technology

Well-developed point-of-care (POC) cancer screening tools have the potential to provide better cancer care to patients in both developed and developing countries. However, new medical technology will not be adopted by medical providers unless it addresses a population’s existing needs and end-users’ preferences. The goals of our study were to assess primary care providers’ level of awareness, interest, and preferences in using POC cancer screening technology in their practice and to provide guidelines to biomedical engineers for future POC technology development. A total of 350 primary care providers completed a one-time self-administered online survey, which took approximately 10 minutes to complete. A $50 Amazon gift card was given as an honorarium for the first 100 respondents to encourage participation. The description of POC cancer screening technology was provided in the beginning of the survey to ensure all participants had a basic understanding of what constitutes POC technology. More than half of the participants (57%) stated that they heard of the term “POC technology” for the first time when they took the survey. However, almost all of the participants (97%) stated they were either “very interested” (68%) or “somewhat interested” (29%) in using POC cancer screening technology in their practice. Demographic characteristics such as the length of being in the practice of medicine, the percentage of patients on Medicaid, and the average number of patients per day were not shown to be associated with the level of interest in using POC. These data show that there is a great interest in POC cancer screening technology utilization among this population of primary care providers and vast room for future investigations to further understand the interest and preferences in using POC cancer technology in practice. Ensuring that the benefits of new technology outweigh the costs will maximize the likelihood it will be used by medical providers and patients

Sampling Considerations for Disease Surveillance in Wildlife Populations

Disease surveillance in wildlife populations involves detecting the presence of a disease, characterizing its prevalence and spread, and subsequent monitoring. A probability sample of animals selected from the population and corresponding estimators of disease prevalence and detection provide estimates with quantifiable statistical properties, but this approach is rarely used. Although wildlife scientists often assume probability sampling and random disease distributions to calculate sample sizes, convenience samples (i.e., samples of readily available animals) are typically used, and disease distributions are rarely random. We demonstrate how landscape-based simulation can be used to explore properties of estimators from convenience samples in relation to probability samples. We used simulation methods to model what is known about the habitat preferences of the wildlife population, the disease distribution, and the potential biases of the convenience-sample approach. Using chronic wasting disease in free-ranging deer (Odocoileus virginianus) as a simple illustration, we show that using probability sample designs with appropriate estimators provides unbiased surveillance parameter estimates but that the selection bias and coverage errors associated with convenience samples can lead to biased and misleading results. We also suggest practical alternatives to convenience samples that mix probability and convenience sampling. For example, a sample of land areas can be selected using a probability design that oversamples areas with larger animal populations, followed by harvesting of individual animals within sampled areas using a convenience sampling method

Developing shape change-based fashion prototyping strategies:Enhancing computational thinking in fashion practice and creativity

Emerging technologies enable fluid and versatile material forms of fashionable wearables and e-textiles, with experts in engineering and material science proposing numerous strategies for dynamic textile and garment structures to satisfy various needs. Nevertheless, a critical gap remains in developing practical fashion prototyping strategies that fuse with computational thinking to challenge current norms and envision the future of fashion. This study introduces shape change-based fashion prototyping as a design strategy for dynamic expressions and affordances to inspire fashion practitioners’ interdisciplinary endeavors. We present three studio-based practices as case studies to demonstrate how shape-changing mechanisms including servo motors, shape memory alloys, and pneumatics, spur new fashion construction skills and broaden the scope of potential applications. By doing so, this study contributes to material and conceptual innovation, creating pathways for the seamless integration of technologies from conceptualization, and implementation to envision. Our findings shed light on design possibilities and challenges and offer design recommendations that guide future endeavors. The implications of our research underscore the importance of adopting a relational approach to design variables, emphasize the value of fostering shared vocabulary between fashion and technical design, and highlight the transformative potential of shape-changing prototyping in reshaping the intricate body-material relationship.</p

cis-regulatory circuits regulating NEK6 kinase overexpression in transformed B cells Are super-enhancer independent

Alterations in distal regulatory elements that control gene expression underlie many diseases, including cancer. Epigenomic analyses of normal and diseased cells have produced correlative predictions for connections between dysregulated enhancers and target genes involved in pathogenesis. However, with few exceptions, these predicted cis-regulatory circuits remain untested. Here, we dissect cis-regulatory circuits that lead to overexpression of NEK6, a mitosis-associated kinase, in human B cell lymphoma. We find that only a minor subset of predicted enhancers is required for NEK6 expression. Indeed, an annotated super-enhancer is dispensable for NEK6 overexpression and for maintaining the architecture of a B cell-specific regulatory hub. A CTCF cluster serves as a chromatin and architectural boundary to block communication of the NEK6 regulatory hub with neighboring genes. Our findings emphasize that validation of predicted cis-regulatory circuits and super-enhancers is needed to prioritize transcriptional control elements as therapeutic targets

Energy and Cost Saving of a Photovoltaic-Phase Change Materials (PV-PCM) System through Temperature Regulation and Performance Enhancement of Photovoltaics

The current research seeks to maintain high photovoltaic (PV) efficiency and increased operating PV life by maintaining them at a lower temperature. Solid-liquid phase change materials (PCM) are integrated into PV panels to absorb excess heat by latent heat absorption mechanism and regulate PV temperature. Electrical and thermal energy efficiency analysis of PV-PCM systems is conducted to evaluate their effectiveness in two different climates. Finally costs incurred due to inclusion of PCM into PV system and the resulting benefits are discussed in this paper. The results show that such systems are financially viable in higher temperature and higher solar radiation environment

Half-quantum vortices on c-axis domain walls in chiral p-wave superconductors

Chiral superconductors are two-fold degenerate and domains of opposite chirality can form, separated by domain walls. There are indications of such domain formation in the quasi two-dimensional putative chiral $p$-wave superconductor Sr$_2$RuO$_4$, yet no experiment has explicitly resolved individual domains in this material. In this work, $c$-axis domain walls lying parallel to the layers in chiral $p$-wave superconductors are explored from a theoretical point of view. First, using both a phenomenological Ginzburg-Landau and a quasiclassical Bogoliubov-deGennes approach, a consistent qualitative description of the domain wall structure is obtained. While these domains are decoupled in the isotropic limit, there is a finite coupling in anisotropic systems and the domain wall can be treated as an effective Josephson junction. In the second part, the formation and structure of half-quantum vortices (HQV) on such $c$-axis domain walls are discussed.Comment: 14 pages, 12 figures; to be submitted to NJ

Human Action Recognition in Videos Using Transfer Learning

A variety of systems focus on detecting the actions and activities performed by humans, such as video surveillance and health monitoring systems. However, published labelled human action datasets for training supervised machine learning models are limited in number and expensive to produce. The use of transfer learning for the task of action recognition can help to address this issue by transferring or re-using the knowledge of existing trained models, in combination with minimal training data from the new target domain. Our focus in this paper is an investigation of video feature representations and machine learning algorithms for transfer learning for the task of action recognition in videos in a multi-class environment. Using four labelled datasets from the human action domain, we apply two SVM-based transfer-learning algorithms: adaptive support vector machine (A-SVM) and projective model transfer SVM (PMT-SVM). For feature representations, we compare the performance of two widely used video feature representations: space-time interest points (STIP) with Histograms of Oriented Gradients (HOG) and Histograms of Optical Flow (HOF), and improved dense trajectory (iDT) to explore which feature is more suitable for action recognition from videos using transfer learning. Our results show that A-SVM and PMT-SVM can help transfer action knowledge across multiple datasets with limited labelled training data; A-SVM outperforms PMT-SVM when the target dataset is derived from realistic non-lab environments; iDT has a greater ability to perform transfer learning in action recognition