885 research outputs found
Electronic structure of pristine and Ni-substituted LaFeO3 from near edge x-ray absorption fine structure experiments and first-principles simulations
ISSN:2643-156
The benefits of growth for Indonesian Workers
Indonesia's adopted development model has proved to be the most successful in alleviating poverty and benefiting workers in developing countries. The government's development efforts focused on agriculture, education, and transport infrastructure. It emphasized providing productive employment opportunities and gradually improving the labor quality through education and training. The wage, employment, and income growth rates were left to market forces. Although the rapid growth of labor-intensive manufacturing has led to more jobs and higher wages benefiting workers, workers employed in these industries have expressed growing dissatisfaction. They complain about problems of child labor, the denial of centrally mandated wages and benefits to workers, poor working conditions, and the abuse of young female workers. The government has tried to improve worker's wages and working conditions by centrally mandating higher labor standards, relying principally on minimum wages. Enforcement has improved and, despite low compliance, minimum wages are beginning to bite. Indonesians are debating whether they need labor intensive industries and whether it is a mistake to base Indonesia's growth on cheap labor. They argue that if labor is more expensive, manufacturers must substitute some capital for labor. However, if labor-intensive industries are rejected, the capacity of the economy to absorb plentiful workers will be reduced. The main alternatives are to push up wages now, or to let wages be determined by market forces and strengthen institutions that could improve working conditions, such as labor unions. The author recommends maintaining flexible labor markets and allowing market forces to set the pace of change, while strengthening labor unions.Environmental Economics&Policies,Public Health Promotion,Labor Policies,Health Monitoring&Evaluation,Work&Working Conditions,Environmental Economics&Policies,Health Monitoring&Evaluation,Banks&Banking Reform,Work&Working Conditions,Municipal Financial Management
Efficient inference of convolutional neural networks on general purpose hardware using weight repetition
Deep Neural Networks (DNNs) have begun to permeate all corners of electronic society due to their high accuracy and machine efficiency per operation. Recent work has shown how weights within and across DNN filters have large degrees of repetition due to the pigeonhole principle and modern weight quantization schemes, and that this weight repetition can be harnessed improve DNN inference efficiency in an accelerator/ASIC context. This thesis develops new techniques so that weight repetition leads to an efficiency gain on general-purpose and programmable SIMD-based architectures such as CPUs equipped with vector extensions. We show how to write high-performance software that does not require hardware modifications and can cope with the irregularity introduced by weight repetition schemes. Overall, our highly parallel software kernel achieves up to 1:51 speedup in runtime of inference over state-of-the-art baseline.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Rohit Agrawal, accepted the attached license on 2019-04-23 at 21:40.The student, Rohit Agrawal, submitted this Thesis for approval on 2019-04-23 at 21:43.This Thesis was approved for publication on 2019-04-24 at 15:53.DSpace SAF Submission Ingestion Package generated from Vireo submission #13851 on 2019-08-22 at 16:23:40Made available in DSpace on 2019-08-23T20:48:24Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-04-24Embargo set by: Seth Robbins for item 112373
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There is a lack of quality clinical and laboratory data on co-infections among malaria patients despite several published systematic reviews of the literature
Vibhor Agrawal et al, There is a lack of quality clinical and laboratory data on co-infections among malaria patients despite several published systematic reviews of the literature, Tropical Doctor (, ) pp. . Copyright © 2022. DOI: 10.1177/00494755221136178. Users who receive access to an article through a repository are reminded that the article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference. For permission to reuse an article, please follow our Process for Requesting Permission. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing [email protected]
Session reports for SIGCOMM 2010
This document collects together reports of the sessions from the 2010 ACM SIGCOMM Conference, the annual conference of the ACM Special Interest Group on Data Communication (SIGCOMM) on the applications, technologies, architectures, and protocols for computer communication.</jats:p
Role of Risk Stratification and Genetics in Sudden Cardiac Death
Sudden cardiac death (SCD) is a major public health issue due to its increasing incidence in the general population and the difficulty in identifying high-risk individuals. Nearly 300,000-350,000 patients in the United States and 4- to 5 million patients in the world die from SCD. Coronary artery disease and advanced heart failure are the main etiology for SCD. Ischemia of any cause precipitates lethal arrhythmias, and ventricular tachycardia and ventricular fibrillation are the most common lethal arrhythmias precipitating SCD. Pulse-less electrical activity, brady-arrhythmia and electromechanical dissociation also result in SCD. Most sudden cardiac deaths occur out-of-the-hospital setting, so it is difficult to estimate the public burden, which results in overestimating the incidence of SCD. The insufficiency and limited predictive value of various indicators and criteria for SCD result in the increasing incidences. As a result, there is a need to develop better risk stratification criteria and find modifiable variables to decrease the incidence. Primary and secondary prevention and treatment of SCD need further research. This critical review is focused on the etiology, risk factors, prognostic factors and importance of risk stratification of SCD.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author
Water Birds: Compositional collaboration with clarinets, wireless sensors, and RTcmix
"Water Birds" is an interactive composition for Bb and bass clarinet, computer music and wireless sensor system by Mara Helmuth and Rebecca Danard. A wireless sensor network with infra-red sensors responds to the clarinetist’s movements, and sends data into MaxMSP for signal processing control. The wireless sensor configuration was developed by Jung Hyun Jun, Talmai Oliveira, Amitabh Mishra, Ahmad Mostafa and Dharma Agrawal, and extended for this project in collaboration with Helmuth. MaxMSP Mxj Java objects were created to receive data from the programmed tmote sensors. Helmuth’s score consists of four sound-generating ideas. Her Max patch and RTcmix scripts process the clarinet sound with spectral delays through the rtcmix~ plugin for Max5. Danard created a working score solidifying her decisions about materials played and order of events. Helmuth and Danard’s interactive compositional process allowed to piece to evolve organically into a work commenting on the interaction of people, nature and technology.Conference PaperPre-prin
Deep learning methods for real-time corneal and needle segmentation in volumetric OCT scans
Deep lamellar anterior keratoplasty (DALK) is a promising cornea transplant procedure, which mitigates the risks associated with the commonly used alternative penetrating keratoplasty. In DALK, a surgeon must insert a needle into the cornea to a precise depth and inject an air bubble to separate the stroma and endothelial layer. Optical coherence tomography (OCT) is used to help surgeons judge the needle insertion depth. However, the needle obscures the part of the cornea underneath it, making it difficult to estimate needle insertion depth. In this thesis, deep learning methods are explored for cornea and needle segmentation to automatically compute needle insertion depth from volumetric OCT scans. A simple post-processing step is applied to the mask produced by the deep neural networks to determine the coordinates of the top and bottom corneal boundaries and the needle tip. We compare the performance of 2D and 3D networks on this task. Our experiments consistently showed that all networks perform well on cornea segmentation in scans without a needle, and 3D networks perform better in scans with a needle. We also show that these deep learning methods perform better than existing graph-theory methods on this task and can segment in real-time when deployed using the NVIDIA TensorRT framework.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-05-01The student, Harsh Agrawal, accepted the attached license on 2021-04-22 at 16:20.The student, Harsh Agrawal, submitted this Thesis for approval on 2021-04-22 at 16:48.This Thesis was approved for publication on 2021-04-26 at 11:33.DSpace SAF Submission Ingestion Package generated from Vireo submission #16168 on 2021-09-16 at 17:01:48Made available in DSpace on 2021-09-17T02:34:13Z (GMT). No. of bitstreams: 2
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Enzymatic hydrolysis and fermentation of soy flour to produce ethanol and soy protein concentrate with increased polyphenols
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-12-01The student, Ruchir Agrawal, accepted the attached license on 2021-10-14 at 18:47.The student, Ruchir Agrawal, submitted this Thesis for approval on 2021-10-14 at 22:16.This Thesis was approved for publication on 2021-10-19 at 15:30.DSpace SAF Submission Ingestion Package generated from Vireo submission #17162 on 2022-04-06 at 17:16:47Made available in DSpace on 2022-04-29T21:42:56Z (GMT). No. of bitstreams: 2
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Previous issue date: 2021-10-19Embargo set by: Seth Robbins for item 123321
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Lift date: 2024-04-29T21:46:25Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123321
Lift date: 2024-04-29T21:47:53Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I OnlyDefatted soybean flour (DSF) is a protein-rich ingredient; however, it contains 30-35% carbohydrates, which is made up in parts by sucrose, flatulence-causing oligosaccharides, and water-insoluble cell-wall polysaccharides. A process was developed to produce soy protein concentrates (SPC) by substantially hydrolyzing these carbohydrates with the help of enzymes into water-soluble saccharides and monomeric sugars, which were simultaneously utilized by Saccharomyces cerevisiae for fermentation into ethanol. The enzyme mixture consisted of a cellulase blend, pectinase blend, and α-galactosidase. The effect of process time on SPC protein concentration, overall protein recovery, carbohydrate hydrolysis, yeast growth, ethanol concentration, and total polyphenol concentration of SPC and hydrolysate were evaluated. Control and enzymes-only (EO) systems were maintained in conjunction with the enzymes + yeast (EY) system to individually assess the impact of isoelectric precipitation of soy proteins and enzymatic hydrolysis of carbohydrates without yeasts in the production of SPC. After 12.25 hours of EY process, 100 g of dry DSF produced 68.45 g dry SPC containing 72.23 ± 0.25% protein and 384 mL hydrolysate containing 9.76 ± 0.05 mg/mL ethanol. Protein recovery from DSF in the form of SPC was 84.4 ± 0.4%. Viable yeast count steadily declined from 1.6 ± 0.1×106 CFU/mL slurry at the start of the process to 7.9 ± 1.3×105 CFU/mL slurry after 12.25 hours. Flatulence causing raffinose-series-oligosaccharides were completely hydrolyzed into their monomeric sugars during this process. Total soluble carbohydrates in the EY treatment were consistently lower than control and EO treatment, suggesting that the yeasts were able to ferment sugars as they were becoming available. Total polyphenol concentration (TPC) of SPC increased more than twofold from 1.21 ± 0.04 mg gallic acid equivalent (GAE)/g dry SPC in control to 3.06 ± 0.03 mg GAE/g dry SPC in EY treatment. Similarly, hydrolysate TPC increased twofold from 179 ± 1 μg/mL in control to 371 ± 6 μg/mL in EY treatment. Thus, this novel process led to a protein and polyphenol-rich and reduced-carbohydrate SPC along with polyphenol and ethanol-containing hydrolysate
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