The efect of disinfectant solutions on the durability of the bond between resin based cement and non-precious metal alloy

This study evaluated the effect of disinfectants on the tensile bond strength of Nickel-Chromium alloy bonded with resin cement. 180 pairs of Nickel-Chromium dumbbells were prepared. The dumbbells were divided into 3 groups (n=60), which received one of the following treatments: Sandblasted only (control), sandblasted and Perform®-ID or sandblasted and sodium hypochlorite (SH) before bonding with resin cement. All bonded specimens were stored in distilled water for 24 h and half of the specimens were subsequently thermocycled (500 cycles) before debonding. Tensile bond strength was recorded and each dumbbell was examined for failure mode. Two-way ANOVA analysis indicated that overall there was a statistically significant difference between 24 h and thermocycling test, but no differences between sandblasted only, sandblasted and Perform-ID or sandblasted and SH groups. Post-ANOVA contrasts indicated that only the sandblasted and SH group showed a significant difference between the 24 h and thermocycling test. Disinfectants did not significantly decrease tensile bond strength between Nickel-Chromium dumbbells bonded with resin cement

The efect of disinfectant solutions on the durability of the bond between resin based cement and non-precious metal alloy

This study evaluated the effect of disinfectants on the tensile bond strength of Nickel-Chromium alloy bonded with resin cement. 180 pairs of Nickel-Chromium dumbbells were prepared. The dumbbells were divided into 3 groups (n=60), which received one of the following treatments: Sandblasted only (control), sandblasted and Perform®-ID or sandblasted and sodium hypochlorite (SH) before bonding with resin cement. All bonded specimens were stored in distilled water for 24 h and half of the specimens were subsequently thermocycled (500 cycles) before debonding. Tensile bond strength was recorded and each dumbbell was examined for failure mode. Two-way ANOVA analysis indicated that overall there was a statistically significant difference between 24 h and thermocycling test, but no differences between sandblasted only, sandblasted and Perform-ID or sandblasted and SH groups. Post-ANOVA contrasts indicated that only the sandblasted and SH group showed a significant difference between the 24 h and thermocycling test. Disinfectants did not significantly decrease tensile bond strength between Nickel-Chromium dumbbells bonded with resin cement

A comparison of 4 predictive models of calving assistance and difficulty in dairy heifers and cows

peer-reviewedThe aim of this study was to build and compare predictive models of calving difficulty in dairy heifers and cows for the purpose of decision support and simulation modeling. Models to predict 3 levels of calving difficulty (unassisted, slight assistance, and considerable or veterinary assistance) were created using 4 machine learning techniques: multinomial regression, decision trees, random forests, and neural networks. The data used were sourced from 2,076 calving records in 10 Irish dairy herds. In total, 19.9 and 5.9% of calving events required slight assistance and considerable or veterinary assistance, respectively. Variables related to parity, genetics, BCS, breed, previous calving, and reproductive events and the calf were included in the analysis. Based on a stepwise regression modeling process, the variables included in the models were the dam's direct and maternal calving difficulty predicted transmitting abilities (PTA), BCS at calving, parity; calving assistance or difficulty at the previous calving; proportion of Holstein breed; sire breed; sire direct calving difficulty PTA; twinning; and 2-way interactions between calving BCS and previous calving difficulty and the direct calving difficulty PTA of dam and sire. The models were built using bootstrapping procedures on 70% of the data set. The held-back 30% of the data was used to evaluate the predictive performance of the models in terms of discrimination and calibration. The decision tree and random forest models omitted the effect of twinning and included only subsets of sire breeds. Only multinomial regression and neural networks explicitly included the modeled interactions. Calving BCS, calving difficulty PTA, and previous calving assistance ranked as highly important variables for all 4 models. The area under the receiver operating characteristic curve (ranging from 0.64 to 0.79) indicates that all of the models had good overall discriminatory power. The neural network and multinomial regression models performed best, correctly classifying 75% of calving cases and showing superior calibration, with an average error in predicted probability of 3.7 and 4.5%, respectively. The neural network and multinomial regression models developed are both suitable for use in decision-support and simulation modeling

Mini-AFTERc: a controlled pilot trial of a nurse-led psychological intervention for fear of breast cancer recurrence

Funding: The study was funded by the Chief Scientist Ofce (CSO), which is part of the Scottish Government Health Directorates (reference: HIPS/17/57).Objectives   To determine the feasibility and acceptability of implementing the Mini-AFTERc intervention. Design   Non-randomised cluster-controlled pilot trial. Setting  Four NHS out-patient breast cancer centres in Scotland. Participants  Ninety-two women who had successfully completed primary treatment for breast cancer were screened for moderate levels of fear of cancer recurrence (FCR). Forty-five were eligible (17 intervention and 28 control) and 34 completed 3-month follow-up (15 intervention and 21 control). Intervention   Mini-AFTERc, a single brief (30 min) structured telephone discussion with a specialist breast cancer nurse (SBCN) trained to target the antecedents of FCR. Outcomes   Feasibility and acceptability of Mini-AFTERc and the study design were assessed via recruitment, consent, retention rates, patient outcomes (measured at baseline, 2, 4, and 12 weeks), and post-study interviews with participants and SBCNs, which were guided by Normalisation Process Theory. Results   Mini-AFTERc was acceptable to patients and SBCNs. SBCNs believe the implementation of Mini-AFTERc to be feasible and an extension of discussions that already happen routinely. SBCNs believe delivery, however, at the scale required would be challenging given current competing demands for their time. Recruitment was impacted by variability in the follow-up practices of cancer centres and COVID-19 lockdown. Consent and follow-up procedures worked well, and retention rates were high. Conclusions   The study provided invaluable information about the potential challenges and solutions for testing the Mini-AFTERc intervention more widely where limiting high FCR levels is an important goal following recovery from primary breast cancer treatment.Publisher PDFPeer reviewe

A comparison of machine learning techniques for predicting insemination outcome in Irish dairy cows

Abstract. Reproductive performance has an important effect on economic efficiency in dairy farms with short yearly periods of breeding. The individual factors affecting the outcome of an artificial insemination have been extensively researched in many univariate models. In this study, these factors are analysed in combination to create a comprehensive multivariate model of conception in Irish dairy cows. Logistic regression, Naïve Bayes, Decision Tree learning and Random Forests are trained using 2,723 artificial insemination records from Irish research farms. An additional 4,205 breeding events from commercial dairy farms are used to evaluate and compare the performance of each data mining technique. The models are assessed in terms of both discrimination and calibration ability. The logistic regression model was found to be the most useful model for predicting insemination outcome. This model is proposed as being appropriate for use in decision support and in general simulation of Irish dairy cows

A comparison of machine learning techniques for predicting insemination outcome in Irish dairy cows

peer-reviewedReproductive performance has an important effect on economic efficiency in dairy farms with short yearly periods of breeding. The individual factors affecting the outcome of an artificial insemination have been extensively researched in many univariate models. In this study, these factors are analysed in combination to create a comprehensive multivariate model of conception in Irish dairy cows. Logistic regression, Naive Bayes, Decision Tree learning and Random Forests are trained using 2,723 artificial insemination records from Irish research farms. An additional 4,205 breeding events from commercial dairy farms are used to evaluate and compare the performance of each data mining technique. The models are assessed in terms of both discrimination and calibration ability. The logistic regression model was found to be the most useful model for predicting insemination outcome. This model is proposed as being appropriate for use in decision support and in general simulation of Irish dairy cows

Correction to. Magnetic resonance imaging for clinical management of rectal cancer: Updated recommendations from the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus meeting

Objectives: To update the 2012 ESGAR consensus guidelines on the acquisition, interpretation and reporting of magnetic resonance imaging (MRI) for clinical staging and restaging of rectal cancer. Methods Fourteen abdominal imaging experts from the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) participated in a consensus meeting, organised according to an adaptation of the RAND-UCLA Appropriateness Method. Two independent (non-voting) Chairs facilitated the meeting. 246 items were scored (comprising 229 items from the previous 2012 consensus and 17 additional items) and classified as ‘appropriate’ or ‘inappropriate’ (defined by ≥ 80 % consensus) or uncertain (defined by < 80 % consensus). Results: Consensus was reached for 226 (92 %) of items. From these recommendations regarding hardware, patient preparation, imaging sequences and acquisition, criteria for MR imaging evaluation and reporting structure were constructed. The main additions to the 2012 consensus include recommendations regarding use of diffusion-weighted imaging, criteria for nodal staging and a recommended structured report template. Conclusions: These updated expert consensus recommendations should be used as clinical guidelines for primary staging and restaging of rectal cancer using MRI

Establishing an international computational network for librarians and archivists

Research and experimentation are underway in libraries, archives, and research institutions on various digital strategies, including computational methods and tools, to manage "Collections as Data." This involves new ways for librarians and archivists to manage, preserve, and provide access to their digital collections. A major component in this ongoing process is the education and training needed by information professionals to function effectively in the 21st century. Accessible and transferable infrastructure is a key requirement in creating a network of collaboration for information professionals to fully realize the full potential of managing "Collections as Data." Elements needed include: 1. Open source research and educational platforms to remove barriers to access to curation tools and resources. These are needed to deliver and share computational educational programs. 2. Creation of a Cloud-based student-learning environment. 3. Development of Open Source software architectures that use computational infrastructure. 4. Exploration of new pedagogies for educating librarians and archivists in computational methods and tools. 5. Establishment of a community of practice for developing collaborative projects, and liaising with the wider international iSchool community and practitioners in the field. Our "Blue Sky" proposal seeks to explore a number of these challenges (infrastructure, computation, collaboration, learning) that stimulate the iSchool research community and have the potential to jumpstart international collaborative networks. The goal is to establish an international computational network for supporting librarians and archivists, akin to the existing Sloan Foundation funded "Data Curation Network", which seeks to model a cross-institutional staffing approach for curating research data in digital repositories.Ope

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]