Gas phase hydrogen permeation in alpha titanium and carbon steels

Commercially pure titanium and heats of Armco ingot iron and steels containing from 0.008-1.23 w/oC were annealed or normalized and machined into hollow cylinders. Coefficients of diffusion for alpha-Ti and alpha-Fe were determined by the lag-time technique. Steady state permeation experiments yield first power pressure dependence for alpha-Ti and Sievert's law square root dependence for Armco iron and carbon steels. As in the case of diffusion, permeation data confirm that alpha-titanium is subject to at least partial phase boundary reaction control while the steels are purely diffusion controlled. The permeation rate in steels also decreases as the carbon content increases. As a consequence of Sievert's law, the computed hydrogen solubility decreases as the carbon content increases. This decreases in explained in terms of hydrogen trapping at carbide interfaces. Oxidizing and nitriding the surfaces of alpha-titanium membranes result in a decrease in the permeation rate for such treatment on the gas inlet surfaces but resulted in a slight increase in the rate for such treatment on the gas outlet surfaces. This is explained in terms of a discontinuous TiH2 layer

Learning signals of adverse drug-drug interactions from the unstructured text of electronic health records.

Drug-drug interactions (DDI) account for 30% of all adverse drug reactions, which are the fourth leading cause of death in the US. Current methods for post marketing surveillance primarily use spontaneous reporting systems for learning DDI signals and validate their signals using the structured portions of Electronic Health Records (EHRs). We demonstrate a fast, annotation-based approach, which uses standard odds ratios for identifying signals of DDIs from the textual portion of EHRs directly and which, to our knowledge, is the first effort of its kind. We developed a gold standard of 1,120 DDIs spanning 14 adverse events and 1,164 drugs. Our evaluations on this gold standard using millions of clinical notes from the Stanford Hospital confirm that identifying DDI signals from clinical text is feasible (AUROC=81.5%). We conclude that the text in EHRs contain valuable information for learning DDI signals and has enormous utility in drug surveillance and clinical decision support

Gossypiboma: a surgical menace

Gossypiboma is a rare yet devastating complication. It may be a sequela to any kind of surgical procedure, however intra-abdominal surgeries are commonly implicated as the cause for this entity. In chronic cases, it may even lead to severe morbidity. We report a case of gossypiboma post vaginal hysterectomy, diagnosed and treated successfully by laparoscopy

Automatic classification of eutrophication of inland lakes from spacecraft data

The author has identified the following significant results. Spacecraft data and computer techniques can be used to rapidly map and store onto digital tapes watershed land use information. Software is now available by which this land use information can be rapidly and economically extracted from the tapes and related to coliform counts and other lake contaminants (e.g. phosphorus). These tools are basic elements for determining those land use factors and sources of nutrients that accelerate eutrophication in lakes and reservoirs

Computer Mapping of Water Quality in Saginaw Bay with LANDSAT Digital Data

The author has identified the following significant results. LANDSAT digital data and ground truth measurements for Saginaw Bay (Lake Huron), Michigan, for 31 July 1975 were correlated by stepwise linear regression and the resulting equations used to estimate invisible water quality parameters in nonsampled areas. Chloride, conductivity, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a were best correlated with the ratio of LANDSAT Band 4 to Band 5. Temperature and Secchi depth correlate best with Band 5

Examining public sentiments and attitudes toward COVID-19 vaccination: infoveillance study using Twitter posts

Background: A global rollout of vaccinations is currently underway to mitigate and protect people from the COVID-19 pandemic. Several individuals have been using social media platforms such as Twitter as an outlet to express their feelings, concerns, and opinions about COVID-19 vaccines and vaccination programs. This study examined COVID-19 vaccine–related tweets from January 1, 2020, to April 30, 2021, to uncover the topics, themes, and variations in sentiments of public Twitter users. Objective: The aim of this study was to examine key themes and topics from COVID-19 vaccine–related English tweets posted by individuals, and to explore the trends and variations in public opinions and sentiments. Methods: We gathered and assessed a corpus of 2.94 million COVID-19 vaccine–related tweets made by 1.2 million individuals. We used CoreX topic modeling to explore the themes and topics underlying the tweets, and used VADER sentiment analysis to compute sentiment scores and examine weekly trends. We also performed qualitative content analysis of the top three topics pertaining to COVID-19 vaccination. Results: Topic modeling yielded 16 topics that were grouped into 6 broader themes underlying the COVID-19 vaccination tweets. The most tweeted topic about COVID-19 vaccination was related to vaccination policy, specifically whether vaccines needed to be mandated or optional (13.94%), followed by vaccine hesitancy (12.63%) and postvaccination symptoms and effects (10.44%) Average compound sentiment scores were negative throughout the 16 weeks for the topics postvaccination symptoms and side effects and hoax/conspiracy. However, consistent positive sentiment scores were observed for the topics vaccination disclosure, vaccine efficacy, clinical trials and approvals, affordability, regulation, distribution and shortage, travel, appointment and scheduling, vaccination sites, advocacy, opinion leaders and endorsement, and gratitude toward health care workers. Reversal in sentiment scores in a few weeks was observed for the topics vaccination eligibility and hesitancy. Conclusions: Identification of dominant themes, topics, sentiments, and changing trends about COVID-19 vaccination can aid governments and health care agencies to frame appropriate vaccination programs, policies, and rollouts. [Abstract copyright: ©Ranganathan Chandrasekaran, Rashi Desai, Harsh Shah, Vivek Kumar, Evangelos Moustakas. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 15.04.2022.

Exploiting resource contention in highly mobile environments and its application to vehicular ad-hoc networks

As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques, defined two key parameters: Time Before Handover and Network Dwell Time for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments

Hotdog in bun: a recent technique for oophoropexy

Ovarian torsion is an acute gynaecological emergency. It may present at any age group, however it is more common in the reproductive years. The patient may present with a myriad of clinical features which are often non-specific posing a diagnostic dilemma. Ultrasonography is the best initial modality of imaging. Once diagnosed a surgical approach is the mainstay of treatment. Preservation of ovaries and preventing recurrence in young patients is crucial. We present a case of a young adolescent girl diagnosed with an ovarian torsion who was managed laparoscopically. Oophoropexy was done to avoid future recurrence by an emerging method called the “Hotdog in bun” technique