Search

Drug recalls may impact treatment plans or access to suitable therapies. Thus, they inadvertently affect treatment outcomes. We aimed to examine the impact of recalls on patients' safety using pantoprazole-containing products recall as a case study in terms of the occurrence of potential drug-drug interactions (pDDIs). This retrospective study used de-identified electronic health records of adult patients who had a prescription for oral proton pump inhibitors (PPIs) including pantoprazole, esomeprazole, lansoprazole, or omeprazole from April 2020 through September 2021 from a large tertiary care hospital. The study outcome definition was the prevalence of pDDIs in PPIs users before and after the recall date (March 2021). Changes in the prevalence of pDDIs were modeled using interrupted time-series. The rate ratio of pDDIs in the 12 months before and 6 months after the recall was modeled using negative binomial regression. A total of 1,826 pDDIs were identified, and the median monthly prevalence of pDDI before the recall was 102.5 which increased to 115.5 after the recall. A change in the level of pDDIs occurred immediately after the recall date, followed by a gradual decrease over time. The rate of pDDIs was 69% higher after the recall compared to the baseline (rate ratio 1.69; 95% confidence interval, 0.75–1.91). Recall of pantoprazole-containing products was associated with a higher rate of pDDIs. However, the prevalence of pDDIs gradually decreased over time. We highlight the importance of planning of recall process and coordinating all potential stakeholders to avoid potential harms. Word count: 1450. [ABSTRACT FROM AUTHOR]

Object recognition memory (ORM) allows identification of previously encountered items and is therefore crucial for remembering episodic information. In rodents, reactivation during recall in the presence of a novel object destabilizes ORM and initiates a Zif268 and protein synthesis-dependent reconsolidation process in the hippocampus that links the memory of this object to the reactivated recognition trace. Hippocampal NMDA receptors (NMDARs) modulate Zif268 expression and protein synthesis and regulate memory stability but their possible involvement in the ORM destabilization/reconsolidation cycle has yet to be analyzed in detail. We found that, in adult male Wistar rats, intra dorsal-CA1 administration of the non-subunit selective NMDAR antagonist AP5, or of the GluN2A subunit-containing NMDAR antagonist TCN201, 5 min after an ORM reactivation session in the presence of a novel object carried out 24 h post-training impaired retention 24 h later. In contrast, pre-reactivation administration of the GluN2B subunit-containing NMDAR antagonist RO25–6981 had no effect on ORM recall or retention but impeded the amnesia caused by Zif268 silencing and protein synthesis inhibition in dorsal CA1. Our results indicate that GluN2B-containing hippocampal NMDARs are necessary for ORM destabilization whereas GluN2A-containing NMDARs are involved in ORM reconsolidation, and suggest that modulation of the relative activity of these receptor subtypes during recall regulates ORM persistence. [ABSTRACT FROM AUTHOR]

Connected consciousness, assessed by response to command, occurs in at least 5% of general anaesthetic procedures and perhaps more often in young people. Our primary objective was to establish the incidence of connected consciousness after tracheal intubation in young people aged 18–40 yr. The secondary objectives were to assess the nature of these responses, identify relevant risk factors, and determine their relationship to postoperative outcomes. This was an international, multicentre prospective cohort study using the isolated forearm technique to assess connected consciousness shortly after tracheal intubation. Of 344 enrolled subjects, 338 completed the study (mean age, 30 [standard deviation, 6.3] yr; 232 [69%] female). Responses after intubation occurred in 37/338 subjects (11%). Females (13%, 31/232) responded more often than males (6%, 6/106). In logistic regression, the risk of responsiveness was increased with female sex (odds ratio [OR adjusted ]=2.7; 95% confidence interval [CI], 1.1–7.6; P =0.022) and was decreased with continuous anaesthesia before laryngoscopy (OR adjusted =0.43; 95% CI, 0.20–0.96; P =0.041). Responses were more likely to occur after a command to respond (and not to nonsense, 13 subjects) than after a nonsense statement (and not to command, four subjects, P =0.049). Connected consciousness occured after intubation in 11% of young adults, with females at increased risk. Continuous exposure to anaesthesia between induction of anaesthesia and tracheal intubation should be considered to reduce the incidence of connected consciousness. Further research is required to understand sex-related differences in the risk of connected consciousness. [ABSTRACT FROM AUTHOR]

In the present study, we tested whether processing information in the context of an ancestral survival scenario enhances episodic memory performance in older adults and in stroke patients. In an online study (Experiment 1), healthy young and older adults rated words according to their relevance to an ancestral survival scenario, and subsequent free recall performance was compared to a pleasantness judgment task and a moving scenario task in a within-subject design. The typical survival processing effect was replicated: Recall rates were highest in the survival task, followed by the moving and the pleasantness judgment task. Although older adults showed overall lower recall rates, there was no evidence for differences between the age groups in the condition effects. Experiment 2 was conducted in a neurological rehabilitation clinic with a sample of patients who had suffered from a stroke within the past 5 months. On the group level, Experiment 2 revealed no significant difference in recall rates between the three conditions. However, when accounting for overall memory abilities and executive function, independently measured in standardized neuropsychological tests, patients showed a significant survival processing effect. Furthermore, only patients with high executive function scores benefitted from the scenario tasks, suggesting that intact executive function may be necessary for a mnemonic benefit. Taken together, our results support the idea that the survival processing task – a well-studied task in the field of experimental psychology – may be incorporated into a strategy to compensate for memory dysfunction. [ABSTRACT FROM AUTHOR]

Predicting students' academic performance is of paramount importance to educational institutions. If students' academic performance is predicted course-wise, semester-wise and year-wise then it will be helpful for students to a great extent. In this research article, we generate twenty nine dataset with the help of students' result analysis. Datasets 1 to 9 is the datasets of students' result in first attempt while datasets 10 to 19 represent datasets of students after passing all courses of semesters and datasets 20 to 29 is overall dataset of students' result analysis. To predict the course-wise, semester-wise and year-wise performance of students, we developed a framework titled as E CSY APPS (E ducational C ourse S emester Y ear-wise A cademic P erformance Prediction S ystem) based on classification techniques and designed algorithm for analyzing students' performance in education sector. This E CSY APPS predicts the course-wise, semester-wise and year-wise grade of students. Fifteen classification algorithms such as Logistic Regression (LR), Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVM), Linear Support Vector Classification (LSVC), K-Nearest Neighbors (KNN), Gradient Boosting (GB), Adaptive Boosting (AdaBoost), Bagging, Extreme Gradient Boosting (XGBoost), Light Gradient-Boosting Machine (LightGBM), Categorical Boosting (CatBoost), Linear Discriminant Analysis (LDA), and Stochastic Gradient Descent Classifier (SGDC) are selected and applied on 29 datasets and compared on basis of performance parameters such as Accuracy, Precision, Recall, F1-score and Mean Absolute Error (MAE). These fifteen classification algorithms are under ten classifiers such as Linear Model, Naive Bayes, Tree, Support Vector Machine, Nearest Neighbors, Ensemble, xgboost, lightgbm, Discriminant Analysis and catboost. If the accuracy of two more classification algorithms for a dataset is same then in that case Precision, Recall, F1-score and Mean Absolute Error (MAE) are compared for deciding the best classification algorithm for the dataset. In this way, best classification algorithm is selected for each of 29 datasets. It is found that classifiers xgboost works best for eleven datasets while ensemble techniques Gradient Boosting and AdaBoost work best for two datasets and six datasets respectively among 29 datasets. Other classification algorithms such as Decision Tree, LightGBM, LDA, and KNN are noted to be best classification algorithm for two, four, three, and two datasets respectively. This framework is tested on new eight datasets related to students' result two methods such as K-Fold Cross-validation and Train-Validation-Test method. The results of this framework on new datasets shows that accuracy obtained on test dataset or validation dataset as compared to the accuracy obtained on old dataset is less than 6%. This framework will be helpful for students as well instructor. For students, it will help them to improve the performance of difficult courses from students'point of view in the examination while faculty can use this framework to improve pedagogical practices. [ABSTRACT FROM AUTHOR]

Data is essential for an organization to develop and make decisions efficiently and effectively. Machine learning classification algorithms are used to categorize observations into classes. The Naive Bayes (NB) classifier is a classification algorithm based on the Bayes theorem and the assumption that all predictors are independent of one another. Since this algorithm is based on probabilities, it is necessary to explore the sample distribution and feature type. This study presents an NB classifier method with enhanced performance among multidimensional and multivariate datasets, named the Naive Bayes Enrichment Method (NBEM). The NBEM is based on automated feature selection using threshold learning and the division of a dataset into sub-datasets according to the feature type. The main advantage of this method is the use of multiple NB classifiers based on different distributions and their combinations to classify a new observation. The final phase includes a weighted classification function that combines the results into a single output. This method was tested with 20 multivariate datasets and compared to other classification models and NB classifier variations. The results showed up to 76.3% improvement in the recall measure using NBEM and up to 43.9% improvement in the F1 score. Furthermore, we found that the error percentage of our method depended on the number of classes. [ABSTRACT FROM AUTHOR]

We do not memorize items in our surroundings with equal priority. Previous literature has widely shown that emotional stimuli are better remembered than neutral stimuli. However, given emotional stimuli and neutral stimuli often differ in both valence and arousal dimensions, it remains unclear whether the enhancement effects can be attributed to valence, or just to arousal. Importantly, most prior studies relied on a relatively small number of stimuli and non-emotional factors such as word length, imageability and other confounds were hard to control. To address these challenges, we analyzed multiple large databases of recognition memory and free recall tasks from previous research by items with many lexical and semantic covariates included, examining the effects of valence or arousal when controlling for each other. Our results showed a U-shaped relationship between valence and memory performance for both recognition and free recall, and a linear relationship between arousal and memory performance for both tasks. These findings showed that the memory enhancement effects can be attributed to both valence and arousal. We demonstrated these effects with generalizability across many stimuli and controlled for non-emotional factors. Together, these findings disentangle the contribution of valence and arousal in emotional memory enhancement effects and provide insights for current major theories of emotional memory. • Emotional memory enhancement can be attributed to both valence and arousal. • Valence influenced memory quadratically. • Arousal influenced memory linearly. • These effects are generalizable across stimuli and not caused by non-emotional factors. [ABSTRACT FROM AUTHOR]

Conventional complete denture treatment course requires six appointments, but modified protocol only takes four appointments. This study compared the conventional and modified protocol for complete denture fabrication regarding patient satisfaction and clinical outcomes. A total of 24 patients accepted complete denture treatment. According to complete denture treatment protocol, these patients were divided into the conventional group (group C, n = 12) and the modified group (group M, n = 12). Group C used the conventional protocol and required six appointments. Group M used the one-appointment master impression and jaw relation record technique, and it took four appointments. Data of oral health impact profile-14 (OHIP-14), satisfaction scale and the number of recalls in the first year were collected for the statistical analysis. The mean OHIP-14 scores in group C and group M were 13.79 ± 3.81 and 15.33 ± 5.25, respectively. In terms of satisfaction, the mean scores in group C and group M were 8.33 ± 0.61 points and 8.66 ± 1.13 points, respectively. There were no statistically significant differences between the group C and M in terms of participant ratings for satisfaction and OHIP-14. At the same time, the results indicated that group M significantly reduced the number of postinsertion visits (P < 0.05). In terms of OHIP-14 and patients' satisfaction, the modified treatment protocol is comparable to the conventional protocol. Based on the number of recalls in the first year, the modified treatment protocol has a better clinical outcome. [ABSTRACT FROM AUTHOR]

A problem of object detection in location and television images using threshold processing has been examined. The algorithms, that form adaptive local and global thresholds, including those selecting objects based on geometric characteristics, have been analyzed. The detection quality has been evaluated by comparing it with the standard based on ROC curves and Recall-Precision characteristics. For this purpose, Gaussian models have been used, and verification has been performed on real images. [ABSTRACT FROM AUTHOR]

Recurrent fluctuations in health states can occur as a result of long-term conditions with episodic symptoms or through side effects of cycles of treatment. Fluctuations and associated duration of symptoms can be predictable (eg, side effects of chemotherapy treatment) or unpredictable (eg, relapse in multiple sclerosis). Such recurrent fluctuations in health states can have an important impact on a person's health-related quality of life. When symptoms vary by time of day, day of the week, or during the month, it is challenging to obtain reliable health-related quality of life estimates for use in assessing cost-effectiveness of interventions. The adequacy of the quality of life estimate will be affected by (1) the standard recall period associated with the chosen measure (eg, "health today" EQ-5D, "past 4 weeks" for SF-36/SF-6D) and the way that respondents understand and make judgments about these recall periods, (2) the chosen time points for assessing health-related quality of life in relation to the fluctuations in health, and (3) the assumptions used to interpolate between measurement time points and thus calculate the quality-adjusted life-years. These issues have not received sufficient methodological attention and instead remain poorly accounted for in economic analyses. There is potential for these issues to considerably distort treatment decisions away from the optimal allocation. This article brings together evidence from health economics, psychology, and behavioral economics to explore these challenges in depth; presents the solutions that have been applied to date; and details a methodological research agenda for measuring quality-adjusted life-years in recurrent fluctuating health states. [ABSTRACT FROM AUTHOR]

Heidelberg is among the top three Salmonella enterica serovars associated with human foodborne illness in Canada. Traditional culture and antimicrobial susceptibility testing techniques can be time-consuming to identify Salmonella Heidelberg resistant to cephalosporins and fosfomycin. Rapid and accurate detection of such antibiotic-resistant Salmonella Heidelberg isolates is essential to adopt appropriate control measures. In this study, 15 Salmonella Heidelberg strains isolated from feces of Canadian broiler chickens were characterized by whole genome sequencing. Salmonella Heidelberg genomes had an average coverage of greater than 80-fold, an average of 4,761 protein-coding genes, and all belonged to multilocus sequence type ST15. Genome sequences were compared with genomes in the National Center for Biotechnology Information Pathogen Detection database (www.ncbi.nlm.nih.gov/pathogens/), including human outbreak isolates. The Canadian broiler isolates clustered with chicken isolates from the United States and an equine clinical isolate from Ontario, Canada. In agreement with their antimicrobial resistance phenotypes, several chromosomally encoded specific antimicrobial resistance genes including fosA7 and multidrug resistance efflux pump determinants were detected. An AmpC-like β-lactamase gene, blaCMY-2, linked with a quaternary ammonium compound resistance gene, sugE, on a replicon type IncI1 plasmid was detected in all 15 broiler Salmonella Heidelberg isolates. Of the 205,031 published Salmonella genomes screened in silico, 4,954 (2.4%) contained blaCMY-2, 8,143 (4.0%) contained fosA7, and 919 (0.4%) contained both resistance genes. The combination of both resistance genes (fosA7 and blaCMY-2) was detected in 64% of the Heidelberg genomes and in a small proportion of various other serovars. A PCR method was developed to detect Salmonella Heidelberg in pure culture and chicken feces based on specific primers targeting genes conferring fosfomycin (fosA7) and third-generation cephalosporin (blaCMY-2) resistance as well as the Salmonella-specific invA gene and the universal 16S rRNA genes. The PCR assay was specific and sensitive for blaCMY-2 and fosA7 harboring Salmonella Heidelberg. However, some other Salmonella serovars containing these two resistance genes could also be detected by the developed PCR method. [ABSTRACT FROM AUTHOR]

Recall of microbial-contaminated food products is an important intervention in preventing the transmission of foodborne illness. Here, we summarize the number and nature of foods recalled as a result of microbial contamination, classified by the Canadian Food Inspection Agency, for the period 1 January 2000 through 31 December 2017. A total of 10,432 food products were recalled from 2,094 recall events in Canada because of microbial contamination during this period. The meat, meat products and poultry category, followed by fishery and seafood products and nuts and edible seeds, contained the food products most commonly associated with microbial contamination. Most microbial-contaminated food products reported were recalled because of the presence bacterial pathogens. Salmonella contamination was responsible for the largest number of recall events, whereas Listeria monocytogenes contamination accounted for the greatest number of food products recalled because of microbial contamination. L. monocytogenes contamination was also most commonly associated with major food recall events, although records may be inflated because of an invested effort to prevent future L. monocytogenes outbreaks following a 2008 deli meat recall. The findings and data we present in this study will support future surveillance and analysis of microbialcontaminated food recalls in Canada. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Our objective was to identify factors impacting false positive recalls in screening mammography.Materials and Methods: We retrospectively reviewed our screening mammography database from August 31, 2015 to September 30, 2016, including full field digital mammograms (FFDM) and digital breast tomosynthesis (DBT) mammograms. False positive (FP) exams were defined as Breast Imaging-Reporting and Data System (BI-RADS) 1 or 2 assessments at diagnostic imaging with 1 year cancer-free follow-up, Breast Imaging-Reporting and Data System 3 assessment at diagnostic imaging with 2 years cancer free follow-up, or biopsy with benign pathology. True positives were defined as malignant pathology on biopsy or surgical excision. We evaluated the association of FP recalls with multiple patient-level factors and imaging features.Results: A total of 22,055 screening mammograms were performed, and 1887 patients were recalled (recall rate 8.6%). Recall rate was lower for DBT than full field digital mammograms (8.0% vs 10.6%, p < 0.001). FP results were lower if prior mammograms were available (90.8% vs 95.8%, p = 0.02), and if there was a previous benign breast biopsy (87.6% vs 92.9%, p = 0.01). Mean age for the FP group was lower than the true positive group (56.1 vs 62.9 years, p < 0.001). There were no significant differences in FP recalls based on history of high-risk lesions, family history of breast or ovarian cancer, hormone use, breast density, race, or body mass index.Conclusion: FP recalls were significantly less likely with DBT, in older women, in patients with prior mammograms available for comparison, and in patients with histories of benign breast biopsy. This study supports the importance of using DBT in the screening setting and obtaining prior mammograms for comparison. [ABSTRACT FROM AUTHOR]

Although process model discovery has been largely investigated over the past two decades, existing process discovery methods are not yet considered fully satisfactory. A particular issue is the difficulty of discovering process models with a good balance among recall (or fitness), precision, generalization, and simplicity, notably for real-world event logs. This article revisits the genetic algorithms-based X-Processes process discovery method, discussing the results of using a fitness function calculated through a harmonic mean that considers the four main metrics of process model quality used in process mining — recall, precision, generalization and simplicity. Although genetic algorithms have been used to discover process models, such methods have limitations, as do other non-genetic algorithm-based methods. X-Processes was tested with two harmonic mean options — one based on recall and precision only and another based on the four quality metrics. X-Processes showed superior effectiveness when compared to state-of-the-art process discovery methods, including one also based on genetic algorithms. The experimental results obtained for both harmonic mean options, using 12 real-world event logs, show that the overall quality of all process models discovered by X-Processes is superior to that of the baseline methods. While its execution time is longer than the other compared process discovery methods, X-Processes emerges as a solution when the need for a higher quality process model outweighs the hunger for agility. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To compare outcomes associated with breast cancer screening with digital mammography (DM) alone versus in combination with digital breast tomosynthesis (DBT) in a large representative cohort.Materials and Methods: A total of 325,729 screening mammograms from 247,431 women were analyzed, across two healthcare systems, from June 2015 to September 2017. Patient level demographic, calculated risk levels, and clinical outcomes were extracted from radiology information system and electronic medical records. Multivariable regression modeling adjusting for institution, age, breast density, and first exam was conducted to compare patient characteristics, recall rates, time to biopsy and final diagnosis, clinical outcomes, and diagnostic performance. Participating institutions and the Coordinating Center received Institutional Review Board approval for a waiver of consent to collect and link data and perform analysis.Results: A total of 194,437 (59.7%) screens were DBT versus 131,292 (40.3%) with DM. Women with dense breasts and higher calculated risk were more likely to be screened with DBT. Recall rates were lower for DBT overall (8.83% DBT vs 10.98% DM, adjusted odds ratio, 95% confidence interval = 0.85, 0.83-0.87) and across all age groups, races, and breast densities, and at facilities that used predominantly DBT (8.05%) versus predominantly DM (11.22%), or a combination (10.73%). The most common diagnostic pathway after recall was mammography and ultrasound. Women recalled from DBT were more likely to proceed directly to ultrasound. The median time to biopsy (18 vs 22 days) and final diagnosis (10 vs 13 days) was shorter for DBT. The adjusted cancer rate, cancer detection rate, and specificity were higher for DBT.Conclusion: DBT demonstrated a more efficient screening pathway and improved quality measures with lower recall rates in all patient types, reduced diagnostic mammography and shorter time to biopsy and final diagnosis. [ABSTRACT FROM AUTHOR]

Background Chemical hazard communication is intended to alert users of the potential hazards of chemicals. Hazard information needs to be understood and recalled. Recall of hazard communication is critical when the written form of the information is not available at the time it is required. Methods A cross-sectional study investigating associations between recall of chemical safety information on labels amongst 402 participants including 315 workers and 87 consumers in two provinces of South Africa. Results Respondents were predominantly male (67.7%), the median age was 37 years (IQR: 30-46 years) and less than half of the participants completed high school (47.5%). Multivariate analysis identified the following positive associations with the recall of all the label elements listing the strongest association: call appropriate services and industrial vs consumer sector (OR = 2.4; 95% CI: 1.2; 4.6 ); call appropriate services and transport vs consumer sector (OR = 4.4; 95% CI: 1.2; 16.0); flammable symbol and male vs female gender (OR = 2.3; 95% CI: 1.0; 5.3); flammable symbol and home language English vs African languages (OR = 6.6; 95% CI: 2.1; 21.2); any hazard statement and home language Afrikaans vs African languages (OR = 14.0; 95% CI: 3.6; 54.2), any first aid statement and further education vs none (OR = 3.3; 95% CI: 1.3; 8.0), correct chemical name and industry blue collar workers vs non-industry blue collar workers (OR = 2.6; 95% CI: 1.1; 6.1), correct chemical name and non-industry white collar occupations vs non-industry blue collar workers (OR = 2.7; 95% CI: 1.0; 7.1). Conclusion The study found a number of potential positive associations which influence recall of label elements of which some (e.g., sector, gender, occupation) suggest further research. Relevant policies in South Africa should ensure that the safety information on chemical labels is clearly visible to read and understandable which aids recall and the reduction in harmful chemical exposures. [ABSTRACT FROM AUTHOR]

Process mining studies ways to improve real-world processes using historical event data generated by IT systems that support business processes of organisations. Given an event log of an IT system, process discovery algorithms construct a process model representing the processes recorded in the log, while conformance checking techniques quantify how well the discovered model achieves this objective. State-of-the-art discovery and conformance techniques either completely ignore or consider but hide from the users information about the likelihood of process behaviour. That is, the vast majority of the existing process discovery algorithms construct non-stochastic aware process models. Consequently, few conformance checking techniques can assess how well such discovered models describe the relative likelihoods of traces recorded in the log or how well they represent the likelihood of future traces generated by the same system. Note that this is necessary to support process simulation, prediction and recommendation. Furthermore, stochastic information can provide business analysts with further actionable insights on frequent and rare conformance issues. This article presents precision and recall measures based on the notion of entropy of stochastic automata, which are capable of quantifying and, hence, differentiating, between frequent and rare deviations of an event log and a process model that is enriched with the information on the relative likelihoods of traces it describes. An evaluation over several real-world datasets that uses our open-source implementation of the measures demonstrates the feasibility of using our precision and recall measures in industrial settings. Finally, we propose a range of intuitive desired properties that stochastic precision and recall measures should possess, and study our and other existing stochastic-aware conformance measures with respect to these properties. • It matters how often behaviour occurs in processes, e.g. for performance, simulation, prediction, etc. • Often, this stochastic perspective is not considered by conformance checking techniques. • In this paper, we introduce two sets of stochastic recall+precision measures. • The techniques are practically feasible, though are limited to deterministic stochastic behaviour. • 14 properties for stochastic conformance measures are proposed. • We analyse existing measures using these properties. [ABSTRACT FROM AUTHOR]

Data from the recalls of meat and poultry products from 2000 through 2012 due to Salmonella contamination were used to assess the factors associated with the recovery of the recalled product and to develop quantitative models to estimate the number of illnesses prevented by recalls. The percentage of product recovered following a recall action was not dependent on establishment size, recall expansions, complexity of the distribution chain, type of distribution, amount of time between the production and recall dates, or number of pounds of product recalled. However, illness-related recalls were associated with larger amounts of recalled product, smaller percentages of recalled product recovered, a greater number of days between the production date and recall date, and nationwide distribution than were recalls that were not illness related. In addition, the detection of recall-associated illnesses appeared to be enhanced in states with strong foodborne illness investigation systems. The number of Salmonella illnesses prevented by recalls was based on the number of illnesses occurring relative to the number of pounds consumed, which was then extrapolated to the number of pounds of recalled product recovered. A simulation using a program evaluation and review technique probability distribution with illness-related recalls from 2003 through 2012 estimated that there were 19,000 prevented Salmonella illnesses, after adjusting for underdiagnosis. Recalls not associated with illnesses from 2000 through 2012 prevented an estimated additional 8,300 Salmonella illnesses, after adjusting for underdiagnosis. Although further improvements to ensure accurate and complete reporting should be undertaken, our study demonstrates that recalls are an important tool for preventing additional Salmonella illnesses. Moreover, additional training resources dedicated to public health agencies for enhancing foodborne illness detection, investigations, and rapid response and reporting would further prevent illnesses. [ABSTRACT FROM AUTHOR]

Methods to objectively evaluate performance are critical for model development. In contrast to recent advances in wildfire simulation, there has been limited attention to evaluating fire model performance. Information to validate fire models is typically limited, commonly to a few perimeter observations at a small number of points in time. We review metrics for comparing two burnt areas at a point in time: observed and predicted. These are compared in an idealised landscape and with a case study evaluating the performance of simulations of an Australian wildfire. We assessed: Shape Deviation Index (SDI), Jaccard's coefficient, F1, Sørensen's Similarity and Area Difference Index (ADI). For decomposing fit into error components (overprediction and underprediction) we assessed the partial indices of SDI and ADI, Precision and Recall. The various metrics were evaluated for their ability to represent error and their suitability for use in model improvement frameworks. [ABSTRACT FROM AUTHOR]

Ontology matching systems take a prominent position in solving semantic heterogeneity problems to facilitate sharing and reuse of ontologies. The process of generating ontology alignments through ontology matching techniques purely lies on how the concepts and relationships are modeled. This paper focuses on designing an ontology matching system in which concepts are modeled based on cognitive units of knowledge comprising of objects, attributes and relationships. The proposed cognitive based ontology matching system(COGOM) identifies semantically related concepts by aggregating the attribute similarity degree, structural similarity degree and semantic conception degree. The similarity computation is adapted from the Tversky psychological model of similarity. The proposed ontology matching system is adaptive in nature because of the cognitive based knowledge expression and the computational overhead of generating alignments is improved by forming quality clusters of semantically correlating concepts thus reducing the concept match space. The precision and recall metrics are used for evaluation of the proposed system using the benchmark data sets of OAEI 2015. [ABSTRACT FROM AUTHOR]

The implantable-cardioverter defibrillator (ICD) lead is the most vulnerable component of the ICD system. Despite advanced engineering design, sophisticated manufacturing techniques, and extensive bench, pre-clinical, and clinical testing, lead failure (LF) remains the Achilles' heel of the ICD system. ICD LF has a broad range of adverse outcomes, ranging from intermittent inappropriate pacing to proarrhythmia leading to patient mortality. ICD LF is often considered in the context of design or construction defects, but is more appropriately considered in the context of the finite service life of a mechanical component placed in chemically stressful environment and subjected to continuous mechanical stresses. This clinical review summarizes LF mechanisms, assessment, and differential diagnosis of LF, including lead diagnostics, recent prominent lead recalls, and management of LF and functioning, but recalled leads. Despite recent advances in lead technology, physicians will likely continue to need to understand how to manage patients with transvenous ICD leads. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Assess results of a prospective, single-site clinical study evaluating digital breast tomosynthesis (DBT) during baseline screening mammography. Materials and Methods: Under an institutional review board-approved Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol, consenting women between ages 34 and 56 years scheduled for their initial and/or baseline screening mammogram underwent both full field digital mammography (FFDM) and DBT. The FFDM and the FFDM plus DBT images were interpreted independently in a reader by mode balanced approach by two of 14 participating radiologists. A woman was recalled for a diagnostic work-up if either radiologist recommended a recall. We report overall recall rates and related diagnostic outcome from the 1080 participants. Proportion of recommended recalls (Breast Imaging Reporting and Data System 0) were compared using a generalized linear mixed model (SAS 9.3) with a significance level of P = .0294. Results: The fraction of women without breast cancer recommended for recall using FFDM alone and FFDM plus DBT were 412 of 1074 (38.4%) and 274 of 1074 (25.5%), respectively (P < .001). Large inter-reader variability in terms of recall reduction was observed among the 14 readers; however, 11 of 14 readers recalled fewer women using FFDM plus DBT (5 with P < .015). Six cancers (four ductal carcinomas in situ [DCIS] and two invasive ductal carcinomas [IDC]) were detected. One IDC was detected only on DBT and one DCIS cancer was detected only on FFDM, whereas the remaining cancers were detected on both modalities. Conclusions: The use of FFDM plus DBT resulted in a significant decrease in recall rates during baseline screening mammography with no reduction in sensitivity. [ABSTRACT FROM AUTHOR]

Big data problems involve more than being able to create a network that can recognize based on a big data set. Big data problems also involve being able to incorporate new information as it arrives. Rehearsing big data sets may require an inordinate amount of time. We present a localist neural network recognition method that can perform equivalent recognition to popular distributed neural networks (shown mathematically) but does not require rehearsing for learning or update. It can also be placed in deep network configuration. However, the focus of this work is not the details of deep networks. The focus is on how easy it is to create and update individual layers. This is an important bottleneck because ultimately creating and updating layers are a problem whether networks are in a deep configuration or not. We use a small laptop running matlab as a microenvironment to reveal data limits determined by limited memory and processing speed. Within this microenvironment we show our approach accepts the largest datasets. Ultimately we encountered limits of the matlab routines to generate random numbers before the limit of our algorithm. [ABSTRACT FROM AUTHOR]

An Intelligent Personal Assistant (IPA) is an agent that has the purpose of helping the user with his daily tasks. This paper is focused on IPAs for Internet of Things (IoT) environments. In this sense, a good IPA has the capability of surveying his user behaviour and suggest tasks or make decisions with the intention of simplifying the user interaction with his surroundings. With this in mind, this paper focuses on studying the accuracy of various classifiers, with the objective of finding the one that suits better the needs of an IPA for IoT. The aim is to test each algorithm with a dataset of events, that relate to past behaviours of the user, and find if there is an opportunity to notify the user that he/she may want to take an action or create an automation based on the learned behaviour. [ABSTRACT FROM AUTHOR]

The relevant documents from large data sets are retrieved with the help of ranking function in Information Retrieval system. In this paper, a new fuzzy logic based ranking function is proposed and implemented to enhance the performance of Information Retrieval system. The proposed ranking function is based on the computation of different terms of term-weighting schema such as term frequency, inverse document frequency and normalization. Fuzzy logic is used at two levels to compute relevance score of a document with respect to the query in present work. All the experiments are performed on CACM and CISI benchmark data sets. The experimental results reveal that the performance of our proposed ranking function is much better than the fuzzy based ranking function developed by Rubens along with other widely used ranking function Okapi-BM25 in terms of precision, recall and F-measure. [ABSTRACT FROM AUTHOR]

Abstract: Context: Fatigue, one of the most common side effects of chemotherapy, is typically assessed via retrospective recall (e.g., over the past week). It is unknown how such retrospective recall of fatigue correlates with daily ratings among people receiving chemotherapy. Objectives: The current study compared fatigue recorded in daily diaries with retrospective ratings using the Fatigue Symptom Inventory (FSI) in patients receiving chemotherapy for gynecologic cancer. Methods: During the week before and the week after their first infusion of chemotherapy, patients completed daily diaries at 10 AM, 2, and 6 PM and the FSI at the end of each week. Results: FSI and diary ratings of peak, lowest, and average fatigue were significantly correlated (P < 0.001). When peak, end, average, and variance diary ratings were regressed separately on the average FSI item, each was significant pre-chemotherapy (P < 0.01) and post-chemotherapy (P < 0.05). However, when entered into a stepwise regression model, only the average fatigue diary rating was retained, explaining 52% of the variance pre-chemotherapy and 54% of the variance post-chemotherapy average FSI item (P < 0.001). Conclusion: The FSI keyed to the past week accurately reflects daily ratings of fatigue among patients receiving chemotherapy. This study has important implications, as completing retrospective ratings of fatigue may be less burdensome for cancer patients than daily assessments. [Copyright &y& Elsevier]

Abstract: We investigated the precision of orientation representations with two tasks, change detection and recall. Previously change detection has been measured only with relatively large orientation changes compared to psychophysical thresholds. In the first experiment, we measured the observers’ ability (d′) to detect small changes in orientation (5–30°) with 1–4 Gabor items. With one item even a 10° change was well detected (average d′=2.5). As the amount of change increased to 30°, the d′ increased to 5.2. When the number of items was increased, the d′s gradually decreased. In the second experiment, we used a recall task and the observers adjusted the orientation of a probe Gabor to match the orientation of a Gabor held in the memory. The standard deviation (s.d.) of errors was calculated from the Gaussian distribution fitted to the data. As the number of items increased from 1 to 6, the s.d. increased from 8.6° to 19.6°. Even with six items, the observers did not make any random adjustments. The results show a square root relation between the d′/s.d. and the number of items. The d′ in change detection is directly proportional to the square root of (1/n) and the orientation change. The increase of the s.d. in recall task is inversely proportional to square root of (1/n). The results suggest that limited resources and precision of representations, without additional assumptions, determine the memory performance. [Copyright &y& Elsevier]

Abstract: A ‘smart space’ is one that automatically identifies and tracks its occupants using unobtrusive biometric modalities such as face, gait, and voice in an unconstrained fashion. Information retrieval in a smart space is concerned with information about the location of people at various points in time. Towards this end, we abstract a smart space by a probabilistic state transition system in which each state records the probabilities of presence of a set of individuals who are present in various zones of the smart space. We formulate a data model based upon an occupancy relation with a real-valued probability attribute and describe some of the spatio-temporal queries in SQL and CLP(R), focusing on the computation of probabilities, an aspect that is novel to this model. We define concepts of precision and recall to quantify the performance of this model based on its ability to answer various spatio-temporal queries and discuss results from our experimental prototype. [Copyright &y& Elsevier]

Abstract: Due to the tremendous growth of network based services, intrusion detection has emerged as an important technique for network security. While variety of security techniques are being developed and a lot of research is going on intrusion detection, but the field lacks an integrated approach with high detection rate (recall) and precision for minority attacks namely R2L and U2R. However, the recall and precision goals are often conflicting and attacking them simultaneously may not work well, especially when some of the classes are rare. This paper presents a novel layered approach with multi-classifier by combining naïve bayes classifier (NBC) and naive bayes tree (NBTree) to improve detection rate and precision of minority class without hurting the performance of majority class. We identify important reduced feature set for each attack separately, to form layered approach. The proposed approach scales up the recall and precision for major as well as minor attacks, and keeps the false positives at acceptable level in intrusion detection. [Copyright &y& Elsevier]

Image Retrieval has always been an area of extensive research. Many efficient retrieval algorithms have already been proposed. Text based image retrieval system got replaced and Content Based Image Retrieval (CBIR) came into being. CBIR, more efficient than text based image retrieval, has already been implemented by several techniques and researches are going on to increase the efficiency. This paper proposes a new technique of incorporating visual attention model to segment and extract the ROI from an image and then use the result for image retrieval purposes. The main advantage of this concept lies in the improvement of the performance of this retrieval scheme in terms of two parameters: Precision and Recall. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: The aim of this study was to retrospectively compare the interpretive performance of synthetically reconstructed two-dimensional images in combination with digital breast tomosynthesis (DBT) versus full-field digital mammography (FFDM) plus DBT. Materials and Methods: Ten radiologists trained in reading tomosynthesis examinations interpreted retrospectively, under two modes, 114 mammograms. One mode included the directly acquired full-field digital mammograms combined with DBT, and the other included synthetically reconstructed projection images combined with DBT. The reconstructed images do not require additional radiation exposure. The two modes were compared with respect to sensitivity, namely, recommendation to recall a breast with either a pathology-proven cancer (n = 48) or a high-risk lesion (n = 6), and specificity, namely, no recommendation to recall a breast not depicting an abnormality (n = 144) or depicting only benign abnormalities (n = 30). Results: The average sensitivity for FFDM with DBT was 0.826, compared to 0.772 for synthetic FFDM with DBT (difference, 0.054; P = .017 and P = .053 for fixed and random reader effects, respectively). The proportions of breasts with no or benign abnormalities recommended to be recalled were virtually the same: 0.298 and 0.297 for the two modalities, respectively (95% confidence intervals for the difference, −0.028 to 0.036 and −0.070 to 0.066 for fixed and random reader effects, respectively). Sixteen additional clusters of microcalcifications (“positive” breasts) were missed by all readers combined when interpreting the mode with synthesized images versus FFDM. Conclusions: Lower sensitivity with comparable specificity was observed with the tested version of synthetically generated images compared to FFDM, both combined with DBT. Improved synthesized images with experimentally verified acceptable diagnostic quality will be needed to eliminate double exposure during DBT-based screening. [ABSTRACT FROM AUTHOR]

Abstract: We discuss smart environments that identify and track their occupants using unobtrusive recognition modalities such as face, gait, and voice. In order to alleviate the inherent limitations of recognition, we propose spatio-temporal reasoning techniques based upon an analysis of the occupant tracks. The key technical idea underlying our approach is to determine the identity of a person based upon information from a track of events rather than a single event. We abstract a smart environment by a probabilistic state transition system in which each state records a set of individuals who are present in various zones of the smart environment. An event abstracts a recognition step and the transition function defines the mapping between states upon the occurrence of an event. We define the concepts of ‘precision’ and ‘recall’ to quantify the performance of the smart environment. We provide experimental results to show performance improvements from spatio-temporal reasoning. Our conclusion is that the state transition system is an effective abstraction of a smart environment and the application of spatial-temporal reasoning enhances its overall performance. [Copyright &y& Elsevier]

Abstract: This study focused on ConAgra''s communication strategies utilized during its peanut butter and pot pie product recalls. A content analysis revealed that ConAgra handled each recall differently, with little evidence of organizational learning. The use of strategic ambiguity during the peanut butter recall enabled ConAgra to respond more successfully to consumers than during the pot pie recall. [Copyright &y& Elsevier]

Abstract: Context: Choosing an appropriate recall period for symptom assessment in a clinical trial is dependent on the design and purpose of the trial. Objective: To examine the effects of recall on symptom severity ratings by comparing ratings made using 24-hour and seven-day recall periods of the MD Anderson Symptom Inventory (MDASI). Methods: Forty-two patients in their third to eighth week of chemoradiation rated their symptoms using the MDASI on two separate occasions (T1 and T2), one week apart. At T1, patients were randomly assigned to rate symptoms using either a 24-hour or a seven-day recall. At T2, patients rated symptoms using the recall period not used at their first visit. Results: Comparing the 24-hour and seven-day recall periods, the correlation coefficient for total symptom severity was 0.888. All correlation coefficients for symptom severity items were >0.7 except for distress (r =0.67). The percentages of moderate to severe symptoms (rated ≥5) were consistent for both recall periods, with no significant difference between recall periods in the prevalence of moderate to severe symptoms. Cronbach α coefficients for both 24-hour and seven-day recalls were >0.8. Symptoms from both recall periods were more severe for patients with poorer performance status. Twenty patients were cognitively debriefed; 70% thought that the seven-day recall was “more appropriate” for the MDASI, but 85% did not think that recall period would influence their answers. Conclusion: This study demonstrated that the MDASI in a seven-day recall format has psychometric properties consistent with the 24-hour recall version, which may promote its use in future cancer clinical trials and may inform the choice of recall period when symptoms are outcome measures. [ABSTRACT FROM AUTHOR]

Summary: Female survivors of Hodgkin''s lymphoma (HL) treated with mantle radiotherapy experience increased breast cancer risk related to radiation dose and age at diagnosis. In 2003, the Department of Health (DoH) in the UK recalled patients to explain this risk and offer screening. The aims of this paper are to describe women''s emotional responses and knowledge of their personal risk following the recall. Women were interviewed before risk counselling and breast screening (Time 1, n=56) and again following screening and results (Time 2, n=50). Questionnaire measures of quality of life, anxiety, depression and cancer worries were completed at Time 2. No cases of breast cancer were identified. After the recall, 64% had learned more about late effects and 76% were reassured about their health. All but one woman intended to attend future screening. Women are keen to take advantage of screening and experience relatively little distress. [Copyright &y& Elsevier]

Abstract: The impact of looking into the camera during a presentation over a video link (resulting in the perception of mutual gaze) on information recall was investigated. In a face-to-face context mutual gaze has been shown to facilitate the encoding and subsequent recall of information [Fry, R., Smith, G.F., 1975. The effects of feedback and eye contact on performance of a digit-coding task. J. Soc. Psychol. 96, 145–146; Otteson, J.D., Otteson, C.R., 1980. Effect of teacher''s gaze on children''s story recall. Percept. Motor Skill. 50, 35–42; Sherwood, J.V., 1988. Facilitative effects of gaze upon learning. Percept. Motor Skill. 64 (3 Part 2), 1275–1278]. One explanation for these findings is that gaze acts as an arousal stimulus, which increases attentional focus and therefore enhances memory [Kelley, D.H., Gorham, J., 1988. Effects of immediacy on recall of information. Commun. Edu. 37(3), 198–207]. Two studies were conducted in order to test whether gazing at the camera during video-mediated presentations resulted in similar benefits as mutual gaze in a face-to-face context. In study 1 a confederate presented information about two fictitious soap products. In one condition, the confederate gazed at the camera for 30% of the presentation, therefore giving the participants the impression that he was gazing in their direction. In the other condition the confederate did not gaze at the camera. Participants viewed the sales presentations from both conditions. In the condition where gaze was directed at the camera, participants recalled significantly more information about the sales presentation. Study 2 employed the same pre-recorded sales presentations used in study 1, however they were delivered to the participants under audio-only conditions (therefore, the image was switched off). Results from study 2 indicated no recall differences between the two conditions. Findings from these studies would seem to indicate that the perception of gaze aversion over a video link (a consequence of the salesman not looking into the camera) has a negative impact on information recall. This has practical implications for video-mediated presentations. In a distance learning environment lecturers could be advised to look into the camera in order to promote more efficient learning in students. [Copyright &y& Elsevier]

Abstract: Self-report ratings of pain intensity are ubiquitous in research and clinical practice. In addition to rating their current pain, patients are often asked to provide ratings to represent pain intensity over several days or weeks. Few data are available that provide insight into how people understand and accomplish this recall task. This study describes the results of structured interviews with 106 rheumatology patients with chronic pain about how they arrived at their ratings of pain intensity on a visual analog scale referenced to the past week. Most patients were unable to coherently articulate how they derived their ratings. Moreover, there was no consistency across patients. A variety of different strategies were identified that guided their responses. These results support the concern about the meaning and validity of retrospective recall ratings. Recall of pain, a seemingly simple task, is a deceptively more complex phenomenon. Efforts to improve the measurement of recalled pain need to be explored. Improving instructional sets, clearer specification of the dimensions of pain being targeted, avoiding use of a single item to measure pain, improved description of intended reference groups, and determining the length of time that patients are able to remember pain and limiting recall periods are reasonable methods that need to be explored. Perspective: These results emphasize our lack of a full understanding of the meaning of the information elicited by commonly used pain recall questions. They point to the potential importance of clearly specifying what qualities of pain are sought and how the patient should summarize them over the reporting period. [Copyright &y& Elsevier]

• X-rays and computed tomography (CT) for Covid-19 detection. • Convolutional Neural Network (CNN), for automated detection and classification. • CNN is the most used method for pattern recognition and image classification. • Covid-19 Classification and Detection. Covid-19 (Coronavirus Disease-2019) is the most recent coronavirus-related disease that has been announced as a pandemic by the World Health Organization (WHO). Furthermore, it has brought the whole planet to a halt as a result of the worldwide introduction of lockdown and killed millions of people. While this virus has a low fatality rate, the problem is that it is highly infectious, and as a result, it has infected a large number of people, putting a strain on the healthcare system, hence, Covid-19 identification in patients has become critical. The goal of this research is to use X-rays images and computed tomography (CT) images to introduce a deep learning strategy based on the Convolutional Neural Network (CNN) to automatically detect and identify the Covid-19 disease. We have implemented two different classifications using CNN, i.e., binary and multiclass classification. A total of 3,877 images dataset of CT and X-ray images has been utilised to train the model in binary classification, out of which the 1,917 images are of Covid-19 infected individuals. An overall accuracy of 99.64%, recall (or sensitivity) of 99.58%, the precision of 99.56%, F1-score of 99.59%, and ROC of 100% has been observed for the binary classification. For multiple classifications, the model has been trained using a total of 6,077 images, out of which 1,917 images are of Covid-19 infected people, 1,960 images are of normal healthy people, and 2,200 images are of pneumonia infected people. An accuracy of 98.28%, recall (or sensitivity) of 98.25%, the precision of 98.22%, F1-score of 98.23%, and ROC of 99.87% has been achieved for the multiclass classification using the proposed method. On the currently available dataset, the our proposed model produced the desired results, and it can assist healthcare workers in quickly detecting Covid-19 positive patients. [ABSTRACT FROM AUTHOR]

This study examined the effect of matching musical emotion and the mood of the listener on working memory and free recall in normal aging. Memory measures were taken at baseline in healthy young and older participants, and, following a happy or sad mood induction, again after exposure to both mood-matching and -mismatching music in a counterbalanced repeated measures design. Compared to baseline, [i] recall was greater following mood-matching than mood-mismatching music in both groups, and was reduced following mood-mismatching music in older adults, [ii] working memory was greater in the mood-matching condition, but did not differ from baseline in the mismatching condition. The results have significant implications for the increasingly popular forms of intervention involving music used with older populations experiencing cognitive decline. • The effect of mood-matching music on digit span and recall in aging was examined. • Measures were taken following exposure to mood-matching or -mismatching music. • Digit span and recall were improved in both groups following mood-matching music. • Recall was reduced in older adults following mood-mismatching music. • The study contributes novel findings supporting use of music interventions in aging. [ABSTRACT FROM AUTHOR]

Recent approaches to the management of dementia have focused mainly on continual preventive treatment. In this study, we investigated whether intake of 297 mg docosahexaenoic acid (DHA) and 137 mg eicosapentaenoic acid (EPA) per day, which is a smaller amount than in previous reports, would maintain higher cognitive function in healthy elderly people. Eighty-seven participants were enrolled in this 12-month randomized, double-blind, placebo-controlled trial. Cognitive function test, blood biochemical analysis and anthropometry were conducted at baseline, 6 and 12 months of DHA beverage intake. Intake of DHA-enriched milk beverage for 6 and 12 months significantly increased erythrocyte plasma membrane DHA and EPA levels. Furthermore, intake of DHA-enriched milk beverage for 12 months protected against age-related cognitive decline. The preventive mechanism of this small amount of DHA is not known. Thus, further investigation is needed to reveal the mechanism underlying its role in cognitive function. Trial registration: UMIN Clinical Trial Registry, UMIN000031699. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses and evaluates the case of Johnson and Johnson''s crisis management. In an attempt to analyze the case, the paper overviews Johnson and Johnson''s Tylenol product tampering in the 1980s and its recent phantom recall of Children''s Motrin. The assessment of the company''s crisis management was done using the anticipatory model of crisis management (AMCM). Conclusions drawn from this assessment put Johnson and Johnson in a different spotlight than it had enjoyed during its earlier crisis management efforts. Implications for organizational crisis management efforts are also presented. [Copyright &y& Elsevier]