Simple Device For Facilitating Surgical Illumination

Ergonomic problems associated with illumination systems in various medical applications including surgeries, dentistry and other diagnostic processes have been the subject of concern for medical professionals. These problems include difficulties in finding a well-lit wound, time to time adjustment of light, illumination intensity, generation of heat and interruption due to formation of shadows etc. Therefore, there is need for improvement in illumination system with major focus on minimizing the need and efforts for repositioning the luminaire. Present work provides user friendly, efficient and greener surgical illumination device. The designed prototype for better illumination provides direct, shadow-less illumination with its proper sterilization using ethylene oxide sterilization. The designed prototype is better used over the gloves as it provides proper intensity and less diffusivity. There are different prototypes designed for different applications including normal illumination ring, illumination ring with a shaft movement of light, a ring with adjustable light intensity etc. The cell viability assay showed no significant impact of light on cells and tissues

Design of a Scalable and Optimized LED Grow-light System Driven by a High Efficiency DC-DC Power Converter

University of Minnesota M.S.E.E. thesis.May 2019. Major: Electrical/Computer Engineering. Advisor: Ned Mohan. 1 computer file (PDF); viii, 62 pages + 2 supplementary filesUncertainty in weather pattern adversely affects agriculture and results in food scarcity and food deserts in some regions of our planet. This has promoted research in the field of plant growth in controlled environment. The concept of artificial sunlight is significant in regions like Minnesota which don’t get strong sunlight over the year and have an extremely cold climate. Modern LEDs called Grow-lights which have sufficiently high radiometric power output are replacing HID halogen lamps for such light. Despite the easy commercial availability of LED Grow-light systems, there is a need for scalable end-to-end system design with independent control over light spectrum channels so that it can used for any crop. An LED Grow-light system driven by an efficient buck based 4 channel DC-DC power converter with low current ripple which provides light from the PAR spectrum with controlled intensity was designed and simulated using Matlab Simulink. Hardware implementation of the system was done with the help of a micro-controller and Sciamble Workbench software developed at University of Minnesota

Interaction of recombinant factor VIII and the nonionic surfactant Tween 80 at interfaces

The role of the nonionic surfactant Tween 80 on the behavior of the therapeutic recombinant protein Factor VIII (rFVIII) was investigated at solid/liquid and air/water interfaces. In order to provide a model system to compare results obtained for the complicated rFVIII-Tween system, a well-characterized globular protein lysozyme was used. The experimental scheme involved the introduction of the protein and Tween to the adsorption substrate in different manners, either lysozyme Tween together or in sequence as lysozyme followed by Tween or vice versa. It was observed that the addition of Tween together with lysozyme reduced the amounts adsorbed at hydrophobic surfaces, while no such reduction was observed on hydrophilic surfaces. A high Tween concentration was required to effect the removal of the lysozyme molecules from the hydrophobic surface and Tween was not effective in removing lysozyme from the hydrophilic surface at any concentration. These results suggest that the Tween-surface interaction is important in determining lysozyme adsorption. Similar observations were made for the rFVIII-Tween system at hydrophobic and hydrophilic silica interfaces. In this case, the presence of interfacial and solution Tween together resulted in complete prevention of rFVIII adsorption. Electrostatic forces were observed to be play an important role in rFVIII adsorption. The rFVIII-Tween interactions at solid interfaces were also evaluated using intrinsic fluorescence and biological activity measurements. Results obtained with respect rFVIII adsorbed mass, and structure or biological activity change upon adsorption, were evaluated in parallel. This parallel evaluation suggested that rFVIII adsorption on hydrophilic, negatively charged surfaces is likely to be highly ordered and oriented in a manner that retains the solvent accessibility of the active sites in rFVIII. On the other hand, rFVIII may adsorb to hydrophobic surfaces in different orientations, with a likelihood of surface induced unfolding. rFVIII-Tween interaction at the air/water interface was investigated separately. Surface tension data recorded for rFVIII-Tween mixtures suggested that Tween dominated the air/water interface as the Tween concentration was increased. Reduced interface-induced unfolding was observed at high Tween concentrations. These results were also thought to contribute to the reduction in rFVIII aggregation typically observed as a result of exposure to the air/water interface

Postsecondary Students\u27 Perceptions of Water Issues and Water-Related Educational Interests

We conducted a nonexperimental, descriptive study to better understand Oklahoma State University students\u27 perceptions of water issues and relevant learning preferences using a 56-item survey instrument we based on the 2008 Water Issues in Oklahoma survey. In total, 103 agriculture students participated in our survey. Clean drinking water was their top concern, but few understood potential risks to water supplies. Additionally, participants expressed only modest interest in learning more about water issues. They indicated that they preferred learning via digital media and traditional fact sheets and expressed little interest in learning via apps, in-person events, and newspaper articles. Our results have implications for delivering water education programs to younger college-educated adults

My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks

The research on code-mixed data is limited due to the unavailability of dedicated code-mixed datasets and pre-trained language models. In this work, we focus on the low-resource Indian language Marathi which lacks any prior work in code-mixing. We present L3Cube-MeCorpus, a large code-mixed Marathi-English (Mr-En) corpus with 10 million social media sentences for pretraining. We also release L3Cube-MeBERT and MeRoBERTa, code-mixed BERT-based transformer models pre-trained on MeCorpus. Furthermore, for benchmarking, we present three supervised datasets MeHate, MeSent, and MeLID for downstream tasks like code-mixed Mr-En hate speech detection, sentiment analysis, and language identification respectively. These evaluation datasets individually consist of manually annotated \url{~}12,000 Marathi-English code-mixed tweets. Ablations show that the models trained on this novel corpus significantly outperform the existing state-of-the-art BERT models. This is the first work that presents artifacts for code-mixed Marathi research. All datasets and models are publicly released at https://github.com/l3cube-pune/MarathiNLP

Spread Love Not Hate: Undermining the Importance of Hateful Pre-training for Hate Speech Detection

Pre-training large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. Although this method has proven to be effective for many domains, it might not always provide desirable benefits. In this paper, we study the effects of hateful pre-training on low-resource hate speech classification tasks. While previous studies on the English language have emphasized its importance, we aim to augment their observations with some non-obvious insights. We evaluate different variations of tweet-based BERT models pre-trained on hateful, non-hateful, and mixed subsets of a 40M tweet dataset. This evaluation is carried out for the Indian languages Hindi and Marathi. This paper is empirical evidence that hateful pre-training is not the best pre-training option for hate speech detection. We show that pre-training on non-hateful text from the target domain provides similar or better results. Further, we introduce HindTweetBERT and MahaTweetBERT, the first publicly available BERT models pre-trained on Hindi and Marathi tweets, respectively. We show that they provide state-of-the-art performance on hate speech classification tasks. We also release hateful BERT for the two languages and a gold hate speech evaluation benchmark HateEval-Hi and HateEval-Mr consisting of manually labeled 2000 tweets each. The models and data are available at https://github.com/l3cube-pune/MarathiNLP

Document Automation Architectures: Updated Survey in Light of Large Language Models

This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically creating and integrating input from different sources and assembling documents conforming to defined templates. There have been reviews of commercial solutions of DA, particularly in the legal domain, but to date there has been no comprehensive review of the academic research on DA architectures and technologies. The current survey of DA reviews the academic literature and provides a clearer definition and characterization of DA and its features, identifies state-of-the-art DA architectures and technologies in academic research, and provides ideas that can lead to new research opportunities within the DA field in light of recent advances in generative AI and large language models.Comment: The current paper is the updated version of an earlier survey on document automation [Ahmadi Achachlouei et al. 2021]. Updates in the current paper are as follows: We shortened almost all sections to reduce the size of the main paper (without references) from 28 pages to 10 pages, added a review of selected papers on large language models, removed certain sections and most of diagrams. arXiv admin note: substantial text overlap with arXiv:2109.1160

Issues concerning Landowner Management Plan Adoption Decisions: A Recursive Bivariate Probit Approach

Despite the likely benefits of having a written forest management plan, a small number of landowners in the United States have the one. A recursive bivariate probit model was used to identify the possible relationship between landowners’ decision to obtain a management plan and their interest in future timber harvesting. Our study results based on recursive bivariate model suggest that landowners having larger land ownerships, longer forest ownership tenure, and higher education were more likely to have a forest management plan and future timber harvesting interest. While the landowners having interest for wildlife management were also interested to have a written management plan, they did not prefer to harvest in future. Study results indicate that written management plan means more than a timber harvesting strategy to landowners in general. Many elderly landowners with a low level of income and less formal education and those having small or medium sized tracts of forestland are less likely to own a written management plan. Therefore, this group requires special attention in various government sponsored forest management related extension activities. Future research on understanding landowner perception behind written management plan is recommended

Literature Survey on Employee Activity Tracking Tool in an Intranet based System for Security and Performance Evaluation

In the digital world aided by Networked Computers, it is a daunting task toenforce security measures, especially when the data is potentially confidential to the firm at hand. With high efficiency systems in place, like firewalls and honey pots, to negate any attack over the network, the perpetrators now concentrate on breaking the weaker links in any organization, the employees. For an enterprise it is very important for employer to have a performance evaluation of his employees and to detect insider attacks and to keep company's data safe and prevent leaking of the companies secure data. An employee activity tool is a tool which allows an employer to track the activities of an employee in his working environment. The employee activity tool is based on remote administration concept. This tool will have a platform on which various plug-in can be written. The employee activity tracking tool will be multiplatform. The loss of productivity and intellectual theft are major concerns in any organization. In this paper we have studied various operations to be performed needed to be performed to enforce security measures against insider attack and to track and increase employee?s productivity