Growth and Production of Golden Shiner, Notemigonous crysoleucas, Under Different Stocking Densities and Feeding Rates

Experiments on the effects of stocking densities and feeding rates on growth and production of golden shiner were conducted under laboratory conditions. The stocking densities were 20, 28 and 36 fry per 60 gal of water. The fish in tanks with 28 fry were fed at 1, 3 and 5% feeding rates and the rest were fed at 5% feeding rate. A 5% feeding rate was found to be essential for good production. The stocking density of 20 fry (400 lb/acre production) with 5% feeding rate yielded better growth in weight and length and better production than the rest of the experimental conditions

From Failing Hands. By John D. Feerick

From Failing Hands, aptly provocative in its title, and scholarly and entertaining throughout its several hundred pages, presents the drama, the history, and the legal and political problems involved in presidential succession in the United States

Triethylphosphite as a network forming agent enhances in-vitro biocompatibility and corrosion protection of hybrid organic-inorganic sol-gel coatings for Ti6Al4V alloys

The biocompatibility and life of metallic implants can be enhanced through improving the biocompatibility and corrosion protection characteristics of the coatings used with these materials. In this study, triethylphosphite (TEP) was used to introduce phosphorus into organic-inorganic hybrid silica based sol gel coatings prepared using γ-methacryloxypropyltrimethoxysilane and tetramethylorthosilicate. Addition of TEP dramatically increased the rate of intermolecular condensation and resulted in materials showing greater cross linking. Protein (fibrinogen) uptake, osteoblast in vitro biocompatibility and corrosion resistance was enhanced in coatings containing TEP. Although higher concentrations of phosphorus supported the greatest improvement in biocompatibility, a compromise in the phosphorus concentration used would be required if corrosion resistance was most desirable parameter for optimisation. Films prepared by dip coating on Ti6Al4V alloys from these sols offer a promising alternative to wholly metallic prostheses

Development of Machine-Learning Algorithms to Predict Attainment of Minimal Clinically Important Difference After Hip Arthroscopy for Femoroacetabular Impingement Yield Fair Performance and Limited Clinical Utility

\ua9 2023 The Author(s). Purpose: To determine whether machine learning (ML) techniques developed using registry data could predict which patients will achieve minimum clinically important difference (MCID) on the International Hip Outcome Tool 12 (iHOT-12) patient-reported outcome measures (PROMs) after arthroscopic management of femoroacetabular impingement syndrome (FAIS). And secondly to determine which preoperative factors contribute to the predictive power of these models. Methods: A retrospective cohort of patients was selected from the UK\u27s Non-Arthroplasty Hip Registry. Inclusion criteria were a diagnosis of FAIS, management via an arthroscopic procedure, and a minimum follow-up of 6 months after index surgery from August 2012 to June 2021. Exclusion criteria were for non-arthroscopic procedures and patients without FAIS. ML models were developed to predict MCID attainment. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). Results: In total, 1,917 patients were included. The random forest, logistic regression, neural network, support vector machine, and gradient boosting models had AUROC 0.75 (0.68-0.81), 0.69 (0.63-0.76), 0.69 (0.63-0.76), 0.70 (0.64-0.77), and 0.70 (0.64-0.77), respectively. Demographic factors and disease features did not confer a high predictive performance. Baseline PROM scores alone provided comparable predictive performance to the whole dataset models. Both EuroQoL 5-Dimension 5-Level and iHOT-12 baseline scores and iHOT-12 baseline scores alone provided AUROC of 0.74 (0.68-0.80) and 0.72 (0.65-0.78), respectively, with random forest models. Conclusions: ML models were able to predict with fair accuracy attainment of MCID on the iHOT-12 at 6-month postoperative assessment. The most successful models used all patient variables, all baseline PROMs, and baseline iHOT-12 responses. These models are not sufficiently accurate to warrant routine use in the clinic currently. Level of Evidence: Level III, retrospective cohort design; prognostic study

A Decade Of Starspot Activity On The Eclipsing Short-Period RS Canum Venaticorum Star WY Cancri: 1988-1997

We present optical photometry of the short-period eclipsing RS CVn system WY Cancri for the years 1988–1997. For each light curve, we model the distortion waves in order to study the behavior of starspots in this system. After removing the spot effects f

A new method for ranking academic journals in accounting and finance

Given the many and varied uses to which journal rankings are put, interest in ranking journal 'quality' is likely to persist. Unfortunately, existing methods of constructing such rankings all have inherent limitations. This paper proposes a new (complementary) approach, based on submissions to RAE 2001, which is not restricted to a pre-defined journal set and, importantly, is based on quality choice decisions driven by economic incentives. For three metrics, submissions to RAE 2001 are compared with the available set of publications to provide evidence on the perception of journal quality, a fourth metric is based on the overall RAE grades, and an overall ranking is produced

Enhancing home health mobile phone app usability through general smartphone training: usability and learnability case study.

peer-reviewedEach year, millions of older adults fall, with more than 1 out of 4 older people experiencing a fall annually, thereby causing a major social and economic impact. Falling once doubles oneâ s chances of falling again, making fall prediction an important aspect of preventative strategies. In this study, 22 older adults aged between 65 and 85 years were trained in the use of a smartphone-based fall prediction system. The system is designed to continuously assess fall risk by measuring various gait and balance parameters using a smart insole and smartphone, and is also designed to detect falls. The use case of the fall prediction system in question required the users to interact with the smartphone via an app for device syncing, data uploads, and checking system status. The objective of this study was to observe the effect that basic smartphone training could have on the user experience of a group that is not technically proficient with smartphones when using a new connected health system. It was expected that even short rudimentary training could have a large effect on user experience and therefore increase the chances of the group accepting the new technology. All participants received training on how to use the system smartphone app; half of the participants (training group) also received extra training on how to use basic functions of the smartphone, such as making calls and sending text messages, whereas the other half did not receive this extra training (no extra training group). Comparison of training group and no extra training group was carried out using metrics such as satisfaction rating, time taken to complete tasks, cues required to complete tasks, and errors made during tasks. The training group fared better in the first 3 days of using the system. There were significant recorded differences in number of cues required and errors committed between the two groups. By the fourth and fifth day of use, both groups were performing at the same level when using the system. Supplementary basic smartphone training may be critical in trials where a smartphone appâ based system for health intervention purposes is being introduced to a population that is not proficient with technology. This training could prevent early technology rejection and increase the engagement of older participants and their overall user experience with the system.PUBLISHEDpeer-reviewe

Spatial mapping of hepatitis C prevalence in recent injecting drug users in contact with services.

In developed countries the majority of hepatitis C virus (HCV) infections occur in injecting drug users (IDUs) with prevalence in IDUs often high, but with wide geographical differences within countries. Estimates of local prevalence are needed for planning services for IDUs, but it is not practical to conduct HCV seroprevalence surveys in all areas. In this study survey data from IDUs attending specialist services were collected in 52/149 sites in England between 2006 and 2008. Spatially correlated random-effects models were used to estimate HCV prevalence for all sites, using auxiliary data to aid prediction. Estimates ranged from 14% to 82%, with larger cities, London and the North West having the highest HCV prevalence. The methods used generated robust estimates for each area, with a well-identified spatial pattern that improved predictions. Such models may be of use in other areas of study where surveillance data are sparse