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In recent years, deep convolutional networks (DCNN) have gained popularity for different classification (or recognition) tasks. In this paper, three well known DCNN structures were used, i.e., AlexNet, SqueezeNet and GoogLeNet, and their classification performances in recognizing handwritten Bangla isolated characters were compared. These networks have simpler structures compared to the recent DCNNs. Experiments on a standard Bangla database revealed that the overall performance of GoogLeNet is slightly better than the other two networks. Further analysis using saliency maps of the test samples revealed the important features that are learned by the networks for classifying characters. This information led us to understand why classification of some samples fail and how to rectify these. [ABSTRACT FROM AUTHOR]

The accuracy of the recall of the severity of nausea and vomiting of pregnancy (NVP) with Pregnancy-Unique Quantification of Emesis (PUQE) questionnaire has been questioned. We aimed to compare PUQE scores of women recalling the worst episode of NVP of their current pregnancy in different gestational weeks (gwks). Total of 2343 pregnant women (gwks 7–40) were recruited. Four groups were formed according to the gwks at reply: ≤16 gwks (n = 554), ≤20 gwks (n = 1209), >20 gwks (n = 1134) and ≥24 gwks (n = 495). PUQE scores were similar between the groups. Consequently, consistency of PUQE scores across the groups endorses the useability of the PUQE questionnaire in retrospective assessment of the overall severity of NVP in different gwks, regardless of passing of the peak NVP symptoms. What is already known on this subject? Retrospective evaluation of the severity of nausea and vomiting of pregnancy (NVP) has been argued to be disposed to recall bias. Structured Pregnancy-Unique Quantification of Emesis (PUQE) questionnaire is a validated tool for assessing the severity of NVP. What do the results of this study add? When the women recalled the most severe NVP symptoms of their current pregnancy, no differences in the PUQE scores were found despite different gestational weeks at reply. Of distinct PUQE questions, women answering in early pregnancy reported longer duration of nausea than women answering in late pregnancy, but other questions were rated similarly. What the implications are of these findings for clinical practice and/or further research? Our aim was to compare the PUQE scores between the women who filled in the PUQE questionnaire in early or in late pregnancy, instructed to recall their worst symptoms in their current pregnancy. As there were no differences between the groups in total PUQE scores, our results support the application of PUQE questionnaire to assess the severity of NVP during pregnancy not only concurrent to the peak symptoms but also retrospectively. [ABSTRACT FROM AUTHOR]

Prompt diagnostics and appropriate cancer therapy necessitate the use of gene expression databases. The integration of analytical methods can enhance detection precision by capturing intricate patterns and subtle connections in the data. This study proposes a diagnostic-integrated approach combining Empirical Bayes Harmonization (EBS), Jensen–Shannon Divergence (JSD), deep learning, and contour mathematics for cancer detection using gene expression data. EBS preprocesses the gene expression data, while JSD measures the distributional differences between cancerous and non-cancerous samples, providing invaluable insights into gene expression patterns. Deep learning (DL) models are employed for automatic deep feature extraction and to discern complex patterns from the data. Contour mathematics is applied to visualize decision boundaries and regions in the high-dimensional feature space. JSD imparts significant information to the deep learning model, directing it to concentrate on pertinent features associated with cancerous samples. Contour visualization elucidates the model's decision-making process, bolstering interpretability. The amalgamation of JSD, deep learning, and contour mathematics in gene expression dataset analysis diagnostics presents a promising pathway for precise cancer detection. This method taps into the prowess of deep learning for feature extraction while employing JSD to pinpoint distributional differences and contour mathematics for visual elucidation. The outcomes underscore its potential as a formidable instrument for cancer detection, furnishing crucial insights for timely diagnostics and tailor-made treatment strategies. [ABSTRACT FROM AUTHOR]

Purpose: Free recall tasks target cognitive and linguistic processes such as episodic memory, lexical access, and retrieval. Consequently, the free recall paradigm is suitable for assessing memory deterioration caused by aging, which can be influenced by stimulus presentation modality. Hence, the present study aimed to determine if aging has an effect on visual and auditory recall abilities. Materials and Methods: Twenty young adults (mean age: 25.4 ± 0.99) and older adults (mean age: 63.3 ± 3.51) participated in the study. Participants performed a free recall task under two conditions - related and unrelated and two modalities - visual and auditory where they were instructed to recall as many items as possible with no specific order and time limit. Results: Free recall performance was calculated as the mean number of correctly recalled items. Although younger participants recalled a higher number of items, the performance across conditions and modality was variable. Conclusions: The findings of the present study revealed an age-related decline in the efficiency of episodic memory, which is crucial to remember recent events. [ABSTRACT FROM AUTHOR]

Background: Many medicine quality problems are detected after they arrive at health facilities. Thus, critically defective medicines that may pose health risks to patients need to be withheld or recalled. Aims: To investigate the withheld and recalled medicines in relation to the types of defects, their total numbers, therapeutic categories, pharmaceutical dosage forms, and country of manufacturer during the study period. Methods: A retrospective review was performed on withheld and recalled medicines published on the publicly available National Medicines Regulatory Authority (NMRA) official website in Sri Lanka between June 2018 and August 2021. Details on substandard medicines (SM) were extracted and documented. Each record of SM was individually reviewed to determine the type of defect, subsequent action taken by NMRA, therapeutic category, pharmaceutical dosage form, and country of manufacturer. Results: A total of 163 defects were identified in 143 defective medicines, among which the most common types of defects were contamination (n = 59, 36.2%), stability defects (n = 41, 25.2%), packaging and labelling defects (n = 27, 16.6%) and active pharmaceutical ingredient defects (n = 26, 15.9%). Out of 143 total defective medicines identified, anti-infectives accounted for 41.9%, while parenteral preparations (44.0%) were found to be frequently defective. Nearly 70% of the recalled and withheld medicines were of Indian origin, and some manufacturers were identified to be repeatedly involved. Conclusions: This study revealed that contamination was the most frequent cause of defective medicines, while parenteral preparations and anti-infectives were the most susceptible pharmaceutical dosage form and therapeutic category found to be substandard, respectively. In addition, the findings show that some manufacturers were accountable for repetitive withholdings and recalls, which reflects the ignorance of quality control measures and weak regulatory inspections as a violation of Good Manufacturing Practice (GMP). [ABSTRACT FROM AUTHOR]

Background: The emotion of fear bears a survival significance enabling animals to be highly vigilant in contexts of uncertainty. Expectedly, not all information available in the environment can be processed. Given that a major goal is to get rid of the source of fear in a fearful situation, the current study therefore hypothesized that information relating to the fear source would be better attended to and recalled than contextual information, which was validated by comparing participants' recall of different types of information presented in a fearful VR gaming context. Methodology: Fifty-four participants were divided into two groups and finished a specific segment of a VR game with different fear levels. Results: No significant difference in recall performance on the questions about the appearance of the fear source and the questions about the interaction with the source was observed between the fear and less-fear groups. Yet, contextual information was better recalled than information related to the fear source in both groups. Regardless of whether the contextual information was provided beforehand or not, participants still tended to focus primarily on the environment in the gameplay. Also, the immersiveness of the gameplay was positively related to participants' fear level. Discussion: The tendency of attending to contextual information was speculated to be unconditional, in line with the risk calculation observed in prey when situated in less familiar contexts. It was suggested to further validate the present primarily findings by adopting VR headset with eye-tracking function in future studies. Lastly, an understanding of fear's effect on memorization might also provide some information for developing future survival horror games. [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]

Recently, Panama wilt disease that attacks banana leaves has caused enormous economic losses to farmers. Early detection of this disease and necessary preventive measures can avoid economic damage. This paper proposes an improved method to predict Panama wilt disease based on symptoms using an agro deep learning algorithm. The proposed deep learning model for detecting Panama wilts disease is essential because it can help accurately identify infected plants in a timely manner. It can be instrumental in large-scale agricultural operations where Panama wilts disease could spread quickly and cause significant crop loss. Additionally, deep learning models can be used to monitor the effectiveness of treatments and help farmers make informed decisions about how to manage the disease best. This method is designed to predict the severity of the disease and its consequences based on the arrangement of color and shape changes in banana leaves. The present proposed method is compared with its previous methods, and it achieved 91.56% accuracy, 91.61% precision, 88.56% recall and 81.56% F1-score. [ABSTRACT FROM AUTHOR]

Written memoranda of conversations, or memcons, provide a near‐contemporaneous record of what was said in conversation, and offer important insights into the activities of high‐profile individuals. We assess the impact of writing a memcon on memory for conversation. Pairs of participants engaged in conversation and were asked to recall the contents of that conversation 1 week later. One participant in each pair memorialized the content of the interaction in a memcon shortly after the conversation. Participants who generated memcons recalled more details of the conversations than participants who did not, but the content of recall was equally and largely accurate for both participants. Remarkably, only 4.7% of the details of the conversation were recalled by both of the partners after a week delay. Contemporaneous note‐taking appears to enhance memory for conversation by increasing the amount of information remembered but not the accuracy of that information. These findings have implications for evaluating the testimony of participants on conversations with major political or legal ramifications. [ABSTRACT FROM AUTHOR]

Background: Even with all the care taken during the production process, the pharmaceutical industries are still subject to manufacturing medicines with quality deviations, generating commercialized products without the required quality and necessitating their subsequent recall from the market. The objective of this study was to evaluate the reasons that led to the recall of medicines in Brazil in the period evaluated. Methods: This is a descriptive study (using document analysis), on the recall of substandard medicines registered on the website of the National Health Surveillance Agency (ANVISA), from 2010 to 2018. The variables studied were the type of medicine (reference, generic, similar, specific, biological, herbal, simplified notification, new and radiopharmaceutical), type of pharmaceutical dosage form (solid, liquid, semi-solid and parenteral preparation), and reason for recall (Good manufacturing practices, quality and quality/good manufacturing practices). Results: A total of n = 3,056 recalls of substandard medicine were recorded. Similar medicines had a higher recall index (30.1%), followed by generics (21.3%), simplified notification (20.7%) and reference (12.2%). Different dosage forms had similar recalls: solids (35.2%), liquids (31.2%) and parenteral preparations (30.0%), with the exception of semi-solids (3.4%). The reasons for the highest occurrences were related to good manufacturing practices (58.4%) and quality (40.4%). Conclusion: The probable cause for this high number of recalls is the fact that, even with all the quality controls and processes in accordance with good manufacturing practices, errors can occur, both human and in automated processes, thus causing the release of batches that should not have been approved. In summary, it is necessary for manufacturers to implement a robust and well structured quality system in order to avoid such deviations, and it is up to ANVISA to apply greater oversight in the post marketing of these products. [ABSTRACT FROM AUTHOR]

The number of people suffering from diabetes in Taiwan has continued to rise in recent years. According to the statistics of the International Diabetes Federation, about 537 million people worldwide (10.5% of the global population) suffer from diabetes, and it is estimated that 643 million people will develop the condition (11.3% of the total population) by 2030. If this trend continues, the number will jump to 783 million (12.2%) by 2045. At present, the number of people with diabetes in Taiwan has reached 2.18 million, with an average of one in ten people suffering from the disease. In addition, according to the Bureau of National Health Insurance in Taiwan, the prevalence rate of diabetes among adults in Taiwan has reached 5% and is increasing each year. Diabetes can cause acute and chronic complications that can be fatal. Meanwhile, chronic complications can result in a variety of disabilities or organ decline. If holistic treatments and preventions are not provided to diabetic patients, it will lead to the consumption of more medical resources and a rapid decline in the quality of life of society as a whole. In this study, based on the outpatient examination data of a Taipei Municipal medical center, 15,000 women aged between 20 and 80 were selected as the subjects. These women were patients who had gone to the medical center during 2018–2020 and 2021–2022 with or without the diagnosis of diabetes. This study investigated eight different characteristics of the subjects, including the number of pregnancies, plasma glucose level, diastolic blood pressure, sebum thickness, insulin level, body mass index, diabetes pedigree function, and age. After sorting out the complete data of the patients, this study used Microsoft Machine Learning Studio to train the models of various kinds of neural networks, and the prediction results were used to compare the predictive ability of the various parameters for diabetes. Finally, this study found that after comparing the models using two-class logistic regression as well as the two-class neural network, two-class decision jungle, or two-class boosted decision tree for prediction, the best model was the two-class boosted decision tree, as its area under the curve could reach a score of 0.991, which was better than other models. [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]

The current study investigated mixed-emotional memories in groups of young, young-old, and old-old participants. We used a "word-suffix approach" to simulate the co-occurrence of positive and negative emotions. The participants engaged in a free-recall task for valenced words and mixed-emotional words (valenced words coupled with pejorative or endearment suffixes). Our results showed that the groups of older adults recalled higher numbers of suffixed words compared to their younger counterparts. Our findings highlighted older adults' tendency to perceive and remember emotionally ambivalent words to a greater extent than younger adults and showed that the young-old participants were particularly good at solving ambivalence by focusing on positive-dominant ambivalent words. [ABSTRACT FROM AUTHOR]

This paper discusses the methods the course teacher used to teach the Information Processing and Retrieval course [Course Code: 19LISC302]. A few aspects, including Chain Indexing, KWIC, Boolean operators, queries, logical relations, and recall & precision, have been highlighted here for illustration. The course teacher was able to improve the students' knowledge of the mentioned areas by using teaching methods based on the Revised Bloom's Taxonomy. The methods also made it possible to follow the students' progress. Boolean operators, queries, logical relations, and recall & precision exercises are taken into consideration for the discussions here, but chain indexing and KWIC related classroom practice formats are only supplied at Annexure-i. The course teacher created the application that is connected to logical relations (Truth Table), and the students have used it in class to practice. Various multifaceted key phrases, a few queries, the Boolean operators AND, OR, and NOT, and the Truth Table are all included in the aforementioned programme. For students to successfully obtain pertinent data from any database, they must have a solid understanding of logical ideas. Meaningful results won't be produced by executing the queries and operators automatically or blindly. Additionally, it could need extra time from information seekers. Boolean operators are used in information retrieval systems to evaluate queries. The Boolean operators are typically linked to the classes in the queries. The evaluation for each class is either True or False. To effectively use the operators in search queries and extract the necessary data, learners need be familiar with the Truth Table-related concepts. In addition, for the aforementioned subjects other than Chain Indexing and KWIC, the Revised Bloom's Taxonomy based teaching and the students' evaluation techniques have also been presented here. Wherever needed, enough screenshots of the aforementioned programme are produced. Students used a learning approach based on Revised Bloom's Taxonomy to study the concepts linked to the aforementioned themes, and they have been duly documented below. With the use of the methodologies utilised in this study, the teacher was able to glean the essential information necessary for determining the pupils' degrees of learning ability and applying that information to the necessary charts. The charts show the students' competence levels according to themes, making it simple to see the students' skill status. Realizing their ability levels is aided by each level wise clearance and their overall clearance status. Chain indexing, KWIC, logical relations, queries with Boolean operators, database sample records format, RBT levels-based evaluation format, recall, and precision are the examples of exercise forms shown in Annexure-i. Further, overall progress charts, each level wise progress charts and Student performance evaluation report are given at Annexure-ii, Annexure-iii and Annexure-iv respectively. [ABSTRACT FROM AUTHOR]

The accuracy of the recall of the severity of nausea and vomiting of pregnancy (NVP) with Pregnancy-Unique Quantification of Emesis (PUQE) questionnaire has been questioned. We aimed to compare PUQE scores of women recalling the worst episode of NVP of their current pregnancy in different gestational weeks (gwks). Total of 2343 pregnant women (gwks 7–40) were recruited. Four groups were formed according to the gwks at reply: ≤16 gwks (n = 554), ≤20 gwks (n = 1209), >20 gwks (n = 1134) and ≥24 gwks (n = 495). PUQE scores were similar between the groups. Consequently, consistency of PUQE scores across the groups endorses the useability of the PUQE questionnaire in retrospective assessment of the overall severity of NVP in different gwks, regardless of passing of the peak NVP symptoms. What is already known on this subject? Retrospective evaluation of the severity of nausea and vomiting of pregnancy (NVP) has been argued to be disposed to recall bias. Structured Pregnancy-Unique Quantification of Emesis (PUQE) questionnaire is a validated tool for assessing the severity of NVP. What do the results of this study add? When the women recalled the most severe NVP symptoms of their current pregnancy, no differences in the PUQE scores were found despite different gestational weeks at reply. Of distinct PUQE questions, women answering in early pregnancy reported longer duration of nausea than women answering in late pregnancy, but other questions were rated similarly. What the implications are of these findings for clinical practice and/or further research? Our aim was to compare the PUQE scores between the women who filled in the PUQE questionnaire in early or in late pregnancy, instructed to recall their worst symptoms in their current pregnancy. As there were no differences between the groups in total PUQE scores, our results support the application of PUQE questionnaire to assess the severity of NVP during pregnancy not only concurrent to the peak symptoms but also retrospectively. [ABSTRACT FROM AUTHOR]

Camrelizumab (SHR-1210) is a humanized IgG4 monoclonal anti-programmed cell death protein 1 (PD-1) antibody that has been shown to inhibit the binding of PD-1 to PD-L1, thereby blocking the immune escape of various types of cancer, including lung squamous cell carcinoma (LSCC). Reactive cutaneous capillary endothelial proliferation (RCCEP) is the most common adverse event in camrelizumab-treated patients. Here, we introduce a case of LSCC with recall RCCEP induced by stereotactic body radiation therapy (SBRT). A 76-year-old LSCC patient developed RCCEP when he received camrelizumab and chemotherapy. After discontinuing camrelizumab treatment, the RCCEP lesions spontaneously regressed and fell off. However, when the patient received subsequent SBRT, the RCCEP occurred again at the same sites. This case may provide clues for additional study of the immune reactivation effect of SBRT or the underlying mechanism of RCCEP. [ABSTRACT FROM AUTHOR]

Cancer is a common disease, and it takes several human lives every year. It is generally classified on the basis of the tissue from where it originates, such as carcinoma or lymphoma. However, a single tumour may possess several types of heterogeneity. Cancer management is a tedious task due to its heterogeneity. Cancer causes >50% of the total deaths in developing countries due to poor diagnosis. Breast Cancer (BC) is the most heterogeneous cancer and massive molecular data is available on it; however, classification of the information is imperative for its management. Machine learning is an evolving tool that can be used to classify heterogeneous breast cancer datasets. Objective: Proper classification of tumour diversity and diagnosis of BC using ML approaches can improve the chances of survival; effective prognosis can help clinicians recommend the right treatment. Methods: Machine learning (ML) classifiers used for classification in the study are Classification and Regression Trees Naive Bayes Classifier, Artificial Neural Networks, Support–Vector Machines and Logistic Regression. Results: ML is the most efficient tool for classifying the diversity of breast cancer datasets existing with heterogeneity in risk factors. The experimental findings show that the logistic regression model gives the highest accuracy (96.60%), with a lower error rate than other models. Conclusion: ML appears to be a powerful and practical tool for the categorisation of breast cancer. Massive data concerning breast cancer is available, and crucial features can be extracted through ML. This research paper presents a review of machine learning tools used in the extraction of vital elements of tumour categorisation proposing a prognosis. [ABSTRACT FROM AUTHOR]

The present study investigated the differences between early and late-acquired words from a second language in terms of the method of recall, speed and accuracy. This involved comparing the performance of 24 native Arabic participants on two different recall methods: picture naming vs. word definition. Each participant attended two sessions, with a 24-hour interval: a learning session, in which they learned new words, and a retrieval session, in which they performed the picture-naming and word-definition tasks while their ERP signals were recorded. The main results showed a significant main effect of age of acquisition on both accuracy and reaction time. Additionally, the N400 ERP component showed a significant interaction between age of acquisition and method of recall in the N400 values recorded in the left frontal area. Together, these findings indicate that both accuracy and reaction time measures can detect differences between early and late-acquired words, recalled through either a picture-naming or word-definition task. [ABSTRACT FROM AUTHOR]

Evidence suggests that memory is involved in making simulations and predictions about the future (i.e., future thinking), but less work has examined how the outcome of those predictions (whether events play out as predicted or expected) subsequently affects episodic memory. In this investigation, we examine whether memory is better for outcomes that are consistent with predictions, or whether memory is enhanced for outcomes that are inconsistent with predictions, after the predicted event occurs. In this experiment, participants learned a core trait associated with social targets (e.g., high in extroversion), before making predictions about behaviors targets would perform. Participants then were shown behaviors the social targets actually performed (i.e., prediction outcome), which was either consistent or inconsistent with predictions. After that, participants completed a memory test (recognition; recall) for the prediction outcomes. For recognition, the results revealed better memory for outcomes that were consistent with traits associated with targets (i.e., trait‐consistent outcomes), compared to outcomes that were inconsistent (i.e., trait‐inconsistent outcomes). Finding a memory advantage for trait‐consistent outcomes suggests that outcomes that are in line with the contents of memory (e.g., what one knows; schemas) are more readily remembered than those that are inconsistent with memory, which may reflect an adaptive memory process. For recall, memory did not differ between trait‐consistent and trait‐inconsistent outcomes. Altogether, the results of this experiment advance understanding of the reciprocal relationship between episodic memory and future thinking and show that outcome of predictions has an influence on subsequent episodic memory, at least as measured by recognition. [ABSTRACT FROM AUTHOR]

Episodic memory is the type of memory that allows the recollection of personal experiences containing information on what has happened and, also, where and when it happened. Because of its sensitivity to neurodegenerative diseases and the aging of the brain, it is considered a hallmark of Alzheimer's disease dementia (ADD). The objective of the present study was to examine episodic memory in amnestic mild cognitive impairment (aMCI) and ADD. Patients with the diagnosis of early aMCI, late aMCI, and mild ADD were evaluated using the Doors and People tool which consists of four subtests examining different aspects of episodic memory. The statistical analysis with receiver operating characteristic curves (ROC) showed the discriminant potential and the cutoffs of every subtest. Overall, the evaluation of episodic memory with the Doors and People tool can discriminate with great sensitivity between the different groups of people with AD and, especially, early aMCI, late aMCI, and mild ADD patients. [ABSTRACT FROM AUTHOR]

Introduction: Statins are a class of lipid lowering medication which can effectively lower cardiovascular mortality and morbidity by the beneficial effects in atherosclerotic cardiovascular disease. Recently, there are increasing concerns over the relationship between statins and cognitive deficits. On the contrary, some studies have indicated an improvement in memory functions with the use of statins. However, the impact of statins on cognition is still unclear. Aim: To analyse the effect of statins on cognition and memory using Mini-Mental Scale Examination (MMSE). Materials and Methods: The case control study was conducted in Department of Cardiology at PSG Institute of Medical Sciences and Research, Coimbatore, Tamil Nadu, India (tertiary care teaching hospital), from June 2019 to December 2019. Out of total 127 participants, case group included 63 adult patients of both gender, on statin therapy for at least 12 weeks duration and control group included 64 age and gender matched adults who were not on statin therapy. After obtaining a written informed consent, MMSE questionnaire was administered by a trained blinded interviewer to both groups. Pearson's correlation was done to evaluate anysignificant correlation between duration of statin therapy with MMSE and individual domain scores. Data was analysed using Statistical Package for Social Sciences (SPSS) version 24.0, and p-value <0.05 was considered significant. Results: The mean age of the cases was 61.1±7.90 years, and that of the control group was 60.6±7.68 years. Using the cut-off score of 23 to diagnose dementia, 21 (33.3%) cases and 24 (37.5%) control participants had cognitive deficits, with no statistically significant difference. The mean score of patients on statin therapy for more than one year (26.45±3.03) was higher compared to those with less than or equal to one year duration of therapy (24.48±4.11), but did not reach statistical significance. But, statistically significant difference between mean scores of cases and controls was evident in cognitive domains like registration (p-value=0.01) and recall (p-value=0.04) in addition to a significant correlation (p-value=0.03) between the duration of statin therapy and orientation score. Conclusion: This study refutes the possibility of an association of statin therapy with cognitive decline in the study population. On the other hand, the results are illustrative of a potential cognitive benefit with the use of statins. [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]

This study presents the results of two perception experiments aimed at evaluating the effect that specific patterns of disfluencies have on people listening to synthetic speech. We consider the particular case of Cultural Heritage presentations and propose a linguistic model to support the positioning of disfluencies throughout the utterances in the Italian language. A state-of-the-art speech synthesizer, based on Deep Neural Networks, is used to prepare a set of experimental stimuli and two different experiments are presented to provide both subjective evaluations and behavioural assessments from human subjects. Results show that synthetic utterances including disfluencies, predicted by a linguistic model, are identified as more natural and that the presence of disfluencies benefits the listeners' recall of the provided information. • Neural speech synthesis systems model speech phenomena in a natural-sounding way. • Neural synthesis can work as a tool to investigate human speech behaviours. • In specific contexts, speech disfluency phenomena foster listeners' recall. • Models of linguistic behaviours improve speech technological applications. [ABSTRACT FROM AUTHOR]

Biomedical images are utilized by radiologists and physicians in cases where diagnosis and recognition would be more efficient. Therefore, it is recommended to propose novel methods that can retrieve medical images with a high percentage of accuracy. A comprehensive feature selection and weighting combination method with novel learning of k-nearest neighbor artificial neural network (KNN-ANN) was introduced for retrieval of biomedical MR images. Modified Radon, and modified Hu moments operators with weighting combinational methods were proposed for achieving a higher percentage of retrieval. Moreover, these characteristics are re-composed for presenting outstanding statistic specification and spatial signals. This spatial and frequency information is obtained for all MR image datasets. The composition of shape and textural features presents robust vectors for retrieval of the biomedical database. In addition, a KNN-ANN framework is proposed and applied to measure the similarity between the query and biomedical database. The presented system achieves 90% retrieval for all types of classes. For matching features, the most similar highest priority principle with KNN is used. The image retrieved from the databases is the image which has less distance and less most-similar highest priority at KNN. The proposed algorithm is evaluated on two different databases. This novel scheme illustrates higher and better specialty in the MRI datasets. The results were compared and understood to be remarkable. [ABSTRACT FROM AUTHOR]

Background: Older cancer patients may search for health information online to prepare for their consultations. However, seeking information online can have negative effects, for instance increased anxiety due to finding incorrect or unclear information. In addition, existing online cancer information is not necessarily adapted to the needs of older patients, even though cancer is a disease often found in older individuals.Objective: The aim of this study was to systematically develop, implement and evaluate an online health information tool for older cancer patients, the Patient Navigator, providing information that complements the consultation with healthcare providers.Method: For the development and evaluation of the Patient Navigator, the four phases of the MRC framework were used. In the first and second phase the Patient Navigator was developed and pilot tested based on previous research and sub-studies. During the third phase the Patient Navigator was implemented in four Dutch hospitals. In the last phase, a pilot RCT was conducted to evaluate the Patient Navigator in terms of usage (observational tracking data), user experience (self-reported satisfaction, involvement, cognitive load, active control, perceived relevance of the tool), patient participation (observational data during consultation), and patient outcomes related to the consultation (questionnaire data regarding anxiety, satisfaction, and information recall). Recently diagnosed colorectal cancer patients (N = 45) were randomly assigned to the control condition (usual care) or the experimental condition (usual care + Patient Navigator).Results: The Patient Navigator was well used and evaluated positively. Patients who received the Patient Navigator contributed less during the consultation by using less words than patients in the control condition and experienced less anxiety two days after the consultation than patients in the control condition.Conclusion: Since the Patient Navigator was evaluated positively and decreased anxiety after the consultation, this tool is potentially a valuable addition to the consultation for patients. Usage of the Patient Navigator resulted in patients using less words during consultations, without impairing patients' satisfaction, possibly because information needs might be fulfilled by usage of the Patient Navigator. This could create the possibility to personalize communication during consultations and respond to other patient needs. [ABSTRACT FROM AUTHOR]

Objective: This study compared the recall and precision of MeSH-term versus text-word searching to better understand psychosocial MeSH terms and to provide guidance on whether to include both strategies in an information literacy session or how much time should be spent on teaching each search strategy. Methods: Using the relevant recall method, a total of 3,162 resources were considered and evaluated to form a gold standard set of 1,521 relevant resources. We compared resources discussing psychosocial aspects of children and adolescents living with type 1 diabetes using two search strategies: text-word strategy versus MeSH-term strategy. The frequency of MeSH terms, the MeSH hierarchy, and elements of each search strategy were also examined. Results: Using the 1,521 relevant articles, we found that the text-word search strategy had 54% recall, while the MeSHterm strategy had 75% recall. Also, the precision of the text-word strategy was 34.4%, while the precision of the MeSHterm strategy was 47.7%. Therefore, the MeSH-term search strategy yielded both greater recall and greater precision. The MeSH strategy was also more complicated in design and usage than the text-word strategy. Conclusions: This study demonstrates the effectiveness of text-word and MeSH search strategies on precision and recall. The combination of text-word and MeSH strategies is recommended to achieve the most comprehensive results. These results support the idea that MeSH or a similar controlled vocabulary should be taught to experienced and knowledgeable students and practitioners who require a myriad of resources for their literature searches. [ABSTRACT FROM AUTHOR]

Introduction: The effective performance of an Information Retrieval System depends on the quality with which the organization of information is performed, which will imply a retrieval of the most relevant and pertinent information, since these procedures are conditioned to each other, creating a bridge between input and output of information. Objective: To evaluate the impact of the exhaustiveness and specificity variables and the recall and precision measures, as well as the concepts of relevance and pertinence, in Information Retrieval Systems. Methodology: It is characterized as a descriptive and exploratory study, based on a narrative literature review aiming to present the different concepts, their converging and divergent points. Results: As a contribution, we present a proposal for a flow for an Information Storage and Retrieval System, centered on the user, bringing together several aspects related to measures of recall and precision, of relevance and pertinence. Conclusion: It is considered as the final contribution of this study to highlight the importance of a systemic view, in which all elements of an Information Storage and Retrieval System are in interrelation, having the user as the main element; and present the fundamental activities that are important for the training of professionals able to build consistent Systems. [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]

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal–cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (55 to 110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8 to 12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue toward mnemonic target representations. In parallel, source-localized EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal–cortical dynamics supporting the recall process. [ABSTRACT FROM AUTHOR]

Even clinically "asymptomatic" carotid stenosis is associated with multidomain cognitive impairment, gray matter (GM) atrophy, and silent lesion. However, the links between them remain unclear. Using structural MRI data, we examined GM asymmetry index (AI) and white matter hyperintensity (WMH) in 24 patients with severe asymptomatic carotid stenosis (SACS), 24 comorbidity‐matched controls, and independent samples of 84 elderly controls and 22 young adults. As compared to controls, SACS patients showed worse verbal memories, higher WMH burden, and right‐lateralized GM in posterior middle temporal and mouth‐somatomotor regions. These clusters extended to pars triangularis, lateral temporal, and cerebellar regions, when compared with young adults. Further, a full‐path of WMH burden (X), GM volume (atrophy, M1), AI (asymmetry, M2), and neuropsychological variables (Y) through a serial mediation model was analyzed. This analysis identified that left‐dominated GM atrophy and right‐lateralized asymmetry in the posterior middle temporal cortex mediated the relationship between WMH burden and recall memory in SACS patients. These results suggest that the unbalanced hemispheric atrophy in the posterior middle temporal cortex is crucial to mediating relationship between WMH burden and verbal recall memories, which may underlie accelerated aging and cognitive deterioration in patients with SACS and other vascular cognitive impairment. [ABSTRACT FROM AUTHOR]

Introduction: Some women keep on recalling intense labor pain experienced at childbirth to a degree that may negatively affect their life during the postpartum period or lead them to request a cesarean section (CS) in the subsequent delivery. This longitudinal study aimed to assess the impact of severe recalled labor pain from the previous birth on the preference for and delivery by an elective CS in the subsequent delivery. Furthermore, we investigated whether co‐occurring maternal demographic, somatic and mental health factors related to the previous and subsequent delivery, explain parts of a potential association. Material and methods: The study sample comprised 1135 parous women from the Akershus Birth Cohort. Severe recalled labor pain was assessed on a numeric rating scale at pregnancy week 17, and at pregnancy week 32, the preference for an elective CS for the subsequent delivery was assessed. Information on actual delivery by elective CS in the subsequent delivery was retrieved from the electronic birth record. Logistic regression analyses were conducted to examine the impact of severe recalled labor pain on elective CS. Results: Severe recalled labor pain at the previous birth was associated with a preference for an elective CS (odds ratio [OR] 3.57, 95% confidence interval [CI] 2.25–5.67) and actual delivery by elective CS (OR 4.71, 95% CI 2.32–9.59). This association remained statistically significant for the preference for an elective CS (adjusted OR [aOR] 2.12, 95% CI 1.24–3.62) but diminished for delivery by elective CS (aOR 2.30, 95% CI 0.99‐5.35) when adjusting for a variety of covariates. Factors related to previous childbirth such as number of years since previous birth, assisted vaginal delivery, anal sphincter lesions, overall birth experience and fear of childbirth were also linked to preference for and delivery by an elective CS. Conclusions: Women with severe recalled labor pain were about twice as likely to prefer an elective CS compared with women without severe recalled pain. For actual delivery, the significant association with severe recalled pain diminished after adjustment for covariates. However, sample size was small and, irrespective of severe recalled labor pain, preference for an elective CS was statistically significantly associated with actual delivery by elective CS. [ABSTRACT FROM AUTHOR]

Objective The Face-Name Associative Memory test (FNAME) has recently received attention as a test for early diagnosis of Alzheimer's disease. So far, however, there has been no systematic investigation of the effects of aging. Here, we aimed to assess the extent to which the FNAME performance is modulated by normal ageing. Method In a first step, we adapted the FNAME material to the Dutch population. In a second step, younger (n  = 29) and older adults (n  = 29) were compared on recall and recognition performance. Results Significant age effects on name recall were observed after the first exposure of new face-name pairs: younger adults remembered eight, whereas older adults remembered a mean of four out of twelve names. Although both age groups increased the number of recalled names with repeated face-name exposure, older adults did not catch up with the performance of the younger adults, and the age-effects remained stable. Despite of that, both age groups maintained their performance after a 30-min delay. Considering recognition, no age differences were demonstrated, and both age groups succeeded in the recognition of previously shown faces and names when presented along with distractors. Conclusions This study presents for the first time the results of different age groups regarding cross-modal associative memory performance on the FNAME. The recall age effects support the hypothesis of age-related differences in associative memory. To use the FNAME as an early cognitive biomarker, further subscales are suggested to increase sensitivity and specificity in the clinical context. [ABSTRACT FROM AUTHOR]

During a search, phrase-terms expressed in queries are presented to an information retrieval system (IRS) to find documents relevant to a topic. The IRS makes relevance judgements by attempting to match vocabulary in queries to documents. If there is a mismatch, the problem of vocabulary mismatch occurs. The aim is to examine ways of searching for documents more effectively, in order to minimise mismatches. A further aim is to understand the mechanisms of, and the differences between, human and machine-assisted, retrieval. The objective of this study was to determine whether IRS-H (an IRS using the hybrid indexing method) and human participants agree or disagree on relevancy judgments, and whether the problem of mismatching vocabulary can be solved. A collection of eighty research documents and sixty-five phrase-terms were presented to (i) IRS-H and four participants in Test 1, and (ii) IRS-H and one participant (aided by search software) in Test 2. Statistical analysis was performed using the Kappa coefficient. IRS-H and the four participants' judgements disagreed. IRS-H and the participant aided by search software judgments did agree. IRS-H solves the problem of mismatching vocabulary between a query and a document. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairments are fundamental in schizophrenia with verbal memory impairments commonly occurring not only in patients but also in unaffected genetically susceptible individuals. Deficits in verbal memory produce difficulty in problem-solving, emotional distress, and worsening of daily life skills resulting in a poor quality of life. Objectives: This study aims to evaluate the verbal memory in unaffected first-degree relatives of patients of schizophrenia in comparison to healthy controls as well as patients of schizophrenia in remission and to find correlation to symptom domains. Methods: It was a hospital-based, descriptive, cross-sectional case-control study. Three groups (n=40, each group) of patients, first-degree relatives, and controls were taken. Subjects were screened for mental retardation and remission was ascertained in the patient group by the Positive and Negative Syndrome Scale (PANSS). Rye's Auditory Verbal Learning (RAVL) test was used to assess verbal leaning. Results: Verbal memory impairments were significant both in patients and unaffected first-degree relatives. Further, these impairments showed a strong correlation to negative symptoms. Conclusion: Significant (p<0.05) verbal learning impairments were noted in patients and first-degree relatives which showed a correlation to negative symptoms. [ABSTRACT FROM AUTHOR]

Classification tree is a widely used machine learning method. It has multiple implementations as R packages; rpart, ctree, evtree, tree and C5.0. The details of these implementations are not the same, and hence their performances differ from one application to another. We are interested in their performance in the classification of cells using the single-cell RNA-Sequencing data. In this paper, we conducted a benchmark study using 22 Single-Cell RNA-sequencing data sets. Using cross-validation, we compare packages' prediction performances based on their Precision, Recall, F1-score, Area Under the Curve (AUC). We also compared the Complexity and Run-time of these R packages. Our study shows that rpart and evtree have the best Precision; evtree is the best in Recall, F1-score and AUC; C5.0 prefers more complex trees; tree is consistently much faster than others, although its complexity is often higher than others. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to evaluate the effectiveness of Parsijoo, Yooz, and Rismoon search engines to determine the efficient search engine to retrieve relevant documents to users. Methodology: This research was an applied evaluative study. The population of this research consists of three sections: Persian search engines, simulated work tasks (thematic title), and participants (students). In this study, three search engines, Parsijoo, Yooz, and Rismoon, were selected for evaluation. Also, 32 subject headings were selected from the list of Persian subject headings, and then, based on them, simulated work tasks were compiled. 192 students of Ferdowsi University of Mashhad were asked to search the information created from the simulated work tasks in the relevant search engines, then copy the relevant URL and register it in the search form. The 192 students of Ferdowsi University of Mashhad were asked to enter the information required from the simulated work tasks in the relevant search engines, then copy the relevant URL and register it in the search form. Finally, when an URL was chosen more often by students as a relevant website, it was given a higher relevance score. Findings: Findings showed that the three search engines including Parsijoo, Yooz, and Rismoon had a significant difference in the metrics of normalized discounted cumulative gain, and precision, but no significant difference was observed between the three search engines in the recall metric. The general findings of the study also showed that the effectiveness (mean of normalized discounted cumulative gain, precision, and recall) of the search engines was significantly different. In addition, at a 95 percent confidence level, the effectiveness of Parsijoo about 42 percent to 45 percent; Yooz about 43 percent to 46 percent; and Rismoon about 15 percent to 17 percent are estimated. Our estimate indicates that the Rismoon search engine is performing poorly. Also, the effectiveness of Yooz search engine is slightly higher than Parsijoo search engine. Conclusion: Each of Parsijoo, Yooz, and Rismoon search engines has their own policies, capabilities and strategies; hence the effectiveness of each of them is different. Users are advised to use efficient search engine to get the information they want. In this regard, Yooz, Parsijoo, and Rismoon search engines are the most efficient, respectively. In addition, policymakers of Parsijoo, Yooz, and Rismoon search engines are also recommended revising hardware equipment, retrieval algorithms, user interfaces, and information display methods. Finally, it can be concluded that despite the low age of native search engines, the effectiveness of both Yooz and Parsijoo search engines is at a satisfactory level. [ABSTRACT FROM AUTHOR]

Background: Benchmarking the performance of complex analytical pipelines is an essential part of developing Lab Developed Tests (LDT). Reference samples and benchmark calls published by Genome in a Bottle (GIAB) consortium have enabled the evaluation of analytical methods. The performance of such methods is not uniform across the different genomic regions of interest and variant types. Several benchmarking methods such as hap.py, vcfeval, and vcflib are available to assess the analytical performance characteristics of variant calling algorithms. However, assessing the performance characteristics of an overall LDT assay still requires stringing together several such methods and experienced bioinformaticians to interpret the results. In addition, these methods are dependent on the hardware, operating system and other software libraries, making it impossible to reliably repeat the analytical assessment, when any of the underlying dependencies change in the assay. Here we present a scalable and reproducible, cloud-based benchmarking workflow that is independent of the laboratory and the technician executing the workflow, or the underlying compute hardware used to rapidly and continually assess the performance of LDT assays, across their regions of interest and reportable range, using a broad set of benchmarking samples. Results: The benchmarking workflow was used to evaluate the performance characteristics for secondary analysis pipelines commonly used by Clinical Genomics laboratories in their LDT assays such as the GATK HaplotypeCaller v3.7 and the SpeedSeq workflow based on FreeBayes v0.9.10. Five reference sample truth sets generated by Genome in a Bottle (GIAB) consortium, six samples from the Personal Genome Project (PGP) and several samples with validated clinically relevant variants from the Centers for Disease Control were used in this work. The performance characteristics were evaluated and compared for multiple reportable ranges, such as whole exome and the clinical exome. Conclusions: We have implemented a benchmarking workflow for clinical diagnostic laboratories that generates metrics such as specificity, precision and sensitivity for germline SNPs and InDels within a reportable range using whole exome or genome sequencing data. Combining these benchmarking results with validation using known variants of clinical significance in publicly available cell lines, we were able to establish the performance of variant calling pipelines in a clinical setting. [ABSTRACT FROM AUTHOR]

Objective: To summarise the existing evidence of development, validation and current status of utilisation of dish-based dietary assessment tools.Design: Scoping review.Setting: Systematic search using PubMed and Web of Science.Results: We identified twelve tools from seventy-four eligible publications. They were developed for Koreans (n 4), Bangladeshis (n 2), Iranians (n 1), Indians/Malays/Chinese (n 1), Japanese (n 3) and Chinese Americans (n 1). Most tools (10/12) were composed of a dish-based FFQ. Although the development process of a dish list varied among the tools, six studies classified mixed dishes based on the similarity of their characteristics such as food ingredients and cooking methods. Tools were validated against self-reported dietary information (n 9) and concentration biomarkers (n 1). In the eight studies assessing the differences between the tool and a reference, the mean (or median) intake of energy significantly differed in five studies, and 26-83 % of nutrients significantly differed in eight studies. Correlation coefficients for energy ranged from 0·15 to 0·87 across the thirteen studies, and the median correlation coefficients for nutrients ranged from 0·12 to 0·77. Dish-based dietary assessment tools were used in fifty-nine studies mainly to assess diet-disease relationships in target populations.Conclusions: Dish-based dietary assessment tools have exclusively been developed and used for Asian-origin populations. Further validation studies, particularly biomarker-based studies, are needed to assess the applicability of tools. [ABSTRACT FROM AUTHOR]

Background: The intrapartum period is a time of high mortality risk for newborns and mothers. Numerous interventions exist to minimize risk during this period. Data on intervention coverage are needed for health system improvement. Maternal report of intrapartum interventions through surveys is the primary source of coverage data, but they may be invalid or unreliable.Methods: We assessed the reliability of maternal report of delivery and immediate newborn care for a sample of home and health facility births in Sarlahi, Nepal. Mothers were visited as soon as possible following delivery (< 72 h) and asked to report circumstances of labor and delivery. A subset was revisited 1-24 months after delivery and asked to recall interventions received using standard household survey questions. We assessed the reliability of each indicator by comparing what mothers reported immediately after delivery against what they reported at the follow-up survey. We assessed potential variation in reliability of maternal report by characteristics of the mother, birth event, or intervention prevalence.Results: One thousand five hundred two mother/child pairs were included in the reliability study, with approximately half of births occurring at home. A higher proportion of women who delivered in facilities reported "don't know" when asked to recall specific interventions both initially and at follow-up. Most indicators had high observed percent agreement, but kappa values were below 0.4, indicating agreement was primarily due to chance. Only "received any injection during delivery" demonstrated high reliability among all births (kappa: 0.737). The reliability of maternal report was typically lower among women who delivered at a facility. There was no difference in reliability based on time since birth of the follow-up interview. We observed over-reporting of interventions at follow-up that were more common in the population and under-reporting of less common interventions.Conclusions: This study reinforces previous findings that mothers are unable to report reliably on many interventions within the peripartum period. Household surveys which rely on maternal report, therefore, may not be an appropriate method for collecting data on coverage of many interventions during the peripartum period. This is particularly true among facility births, where many interventions may occur without the mother's full knowledge. [ABSTRACT FROM AUTHOR]

The recall was, until recent decades, a tool of direct democracy that was hardly known or used outside the United States. However, the crisis of representation and of the party system that several Latin American countries suffered led to recover the recall as an additional form of citizen participation and control that could boost receptivity and responsibility of elected authorities. In only three decades, the recall has moved from being barely known to spreading to the most important Latin American countries and becoming one of the distinctive features of the region. In this work we present a comparative study of the recall in Argentina, Colombia and the Republic of Peru, where it was limited to regional and local authorities. We also analyse the recall of local legislators and authorities by decision of the political parties and popular vote in Panama; the recall in Ecuador, Venezuela and Bolivia, where this institution has spread to all elected offices, including the president of the republic; and the recall of the president and governors of the federal entities of Mexico after the constitutional reform promoted by López Obrador. This work ends by assessing the institutional designs of the recall, where we emphasize the tension between draft legislation and its conditions for implementation. [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]

Context: Advertising campaigns promoting gambling are ubiquitous. Studies indicate that problem gamblers (PG) are more influenced by these messages. they recall, incite and trigger more gambling behavior. These studies focus on specific populations (youth or PG). The purpose of this study is to understand how gambling advertising and prevention campaigns impact (from exposure to behavior) individuals depending on the severity of gambling. Method: An online questionnaire was relayed by gambling operators, and through social networks. It assessed gambling severity (CPGI), recall of gambling advertisement, to what extent they felt incited and self-reported gambling behavior, as well as socio-demographic variables. Among the respondents to the questionnaire, volonteers took part in a virtual reality experiment (VR), reproducing an urban public space, including advertising campaigns. It measured the exposure to posters by eye-tracking. Results: The questionnaire was completed by 2089 participants (PG = 2%) and 36 participated in the VR experiment. Results from the questionnaire suggest that PG remember more about the campaigns (p<0.05), are more incited (p<0.001), and to engage in gambling behavior (p<0.001). The VR experiment suggest similar behavior among gamblers and non-gamblers, as well as better immediate recall (p=0.01). Discussion: These results demonstrate the impact of advertising campaigns according to the severity of gambling, showing a similar behavior during exposure, but leading to a better recall, which can be related to an easier encoding of this message in memory. These results emphasize the importance of developing ecological experimental protocols and understanding the impact of advertising campaigns on gamblers more globally. [ABSTRACT FROM AUTHOR]

The current paper presents two experiments investigating the effect of presence versus absence of compulsory number marking in a native language on a speaker's ability to recall number information from photos. In Experiment 1, monolingual English and Japanese adults were shown a sequence of 110 photos after which they were asked questions about the photos. We found that the English participants showed a significantly higher accuracy rate for questions testing recall for number information when the correct answer was "2" (instead of "1") than Japanese participants. In Experiment 2, English and Japanese adults engaged in the same task as in Experiment 1 with an addition that explored reasons for the results found in Experiment 1. The results of Experiment 2 were in line with the results of Experiment 1, but also suggested that the results could not be attributed to differences in guessing patterns between the two groups or the type of linguistic constructions used in the test situations. The current study suggests that native language affects speakers' ability to recall number information from scenes and thus provides evidence for the Whorfian hypothesis. [ABSTRACT FROM AUTHOR]

The Deese-Roediger-McDermott paradigm has long shown that individuals will falsely recall a critical lure (Deese, 1959; Roediger Sc McDermott, 1995). Roediger and McDermott (1995) attributed this false recall to activation and monitoring. During encoding, individuals activate information related to the critical lure, then monitoring processes during retrieval fail to identify that die critical lure was activated internally, leading to recall of the critical lure. In the present study, we examined the effect of the serial position of the strongest associates on false recall and recognition of the critical lure. Using a with in-subjects design, participants were exposed to 10 lists of words via MediaLab. Each list placed highly associated words at either the beginning, middle, or end of the list. After each list, participants completed a recall task followed by a recognition task. Results showed that participants recalled the critical lure significantly more often when high associates were at the beginning of the list (p = .002, η = .07), but serial position had no effect on recognition (p = .13, η = .03). Recognition levels showed that, regardless of the serial position of the strongest associates, participants recognized the critical lure at similar proportions. High recall of the critical lure when strong associates were at the beginning of the list can be attributed to the higher likelihood of activation spreading to the lure when the participant is studying the list. Furthermore, there is a decreased likelihood of accurate source monitoring due to the early activation of the lure during study. [ABSTRACT FROM AUTHOR]

Background: Medication errors have been identified as the most common preventable cause of adverse events. The lack of granularity in medication error terminology has led pharmacovigilance experts to rely on information in individual case safety reports' (ICSRs) codes and narratives for signal detection, which is both time consuming and labour intensive. Thus, there is a need for complementary methods for the detection of medication errors from ICSRs. The aim of this study is to evaluate the utility of two natural language processing text mining methods as complementary tools to the traditional approach followed by pharmacovigilance experts for medication error signal detection.Methods: The safety surveillance advisor (SSA) method, I2E text mining and University of Copenhagen Center for Protein Research (CPR) text mining, were evaluated for their ability to extract cases containing a type of medication error where patients extracted insulin from a prefilled pen or cartridge by a syringe. A total of 154,209 ICSRs were retrieved from Novo Nordisk's safety database from January 1987 to February 2018. Each method was evaluated by recall (sensitivity) and precision (positive predictive value).Results: We manually annotated 2533 ICSRs to investigate whether these contained the sought medication error. All these ICSRs were then analysed using the three methods. The recall was 90.4, 88.1 and 78.5% for the CPR text mining, the SSA method and the I2E text mining, respectively. Precision was low for all three methods ranging from 3.4% for the SSA method to 1.9 and 1.6% for the CPR and I2E text mining methods, respectively.Conclusions: Text mining methods can, with advantage, be used for the detection of complex signals relying on information found in unstructured text (e.g., ICSR narratives) as standardised and both less labour-intensive and time-consuming methods compared to traditional pharmacovigilance methods. The employment of text mining in pharmacovigilance need not be limited to the surveillance of potential medication errors but can be used for the ongoing regulatory requests, e.g., obligations in risk management plans and may thus be utilised broadly for signal detection and ongoing surveillance activities. [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]

Background: Integrated care is an increasingly important principle for organising healthcare. Integrated care models show promise in reducing resource wastage and service fragmentation whilst improving the accessibility, patient-centredness and quality of care for patients. Those needing reliable access to the growing research evidence base for integrated care can be frustrated by search challenges reflective of the topic's complexity. The aim of this study is to report the empirical development and validation of two search filters for rapid and effective retrieval of integrated care evidence in PubMed. One filter is optimised for recall and the other for precision.Methods: An Expert Advisory Group comprising international integrated care experts guided the study. A gold standard test set of citations was formed from screening Handbook Integrated Care chapter references for relevance. This set was divided into a Term Identification Set (20%) for determining candidate terms using frequency analysis; a Filter Development Set (40%) for testing performance of term combinations; and a Filter Validation Set (40%) reserved for confirming final filter performance. In developing the high recall filter, recall was steadily increased while maintaining precision at ≥50%. Similarly, the high precision filter sought to maximise precision while keeping recall ≥50%. For each term combination tested, an approximation of precision was obtained by reviewing the first 100 citations retrieved in Medline for relevance.Results: The gold standard set comprised 534 citations. The search filter optimised for recall ('Broad Integrated Care Search') achieved 86.0-88.3% recall with corresponding low precision (47-53%). The search filter optimised for precise searching ('Narrow Integrated Care Search') demonstrated precision of 73-95% with recall reduced to between 55.9 and 59.8%. These filters are now available as one-click URL hyperlinks in the website of International Foundation for Integrated Care.Conclusions: The Broad and Narrow Integrated Care Search filters provide potential users, such as policy makers and researchers, seamless, reliable and ongoing access to integrated care evidence for decision making. These filters were developed according to a rigorous and transparent methodology designed to circumvent the challenges of information retrieval posed by this complex, multifaceted topic. [ABSTRACT FROM AUTHOR]

This study investigated age differences in false memory for visual scenes and the effect of immediate recall on subsequent recognition. Eighty children (7–9 years), 74 adolescents (14–16 years), 92 young adults (19–26 years) and 82 older adults (50–80 years) studied four visual scenes and then took a recognition test after either a free-recall task or a filler task. Results showed an age-related decline in false recognition for visual scenes, but this trend was eliminated when participants were asked to free-recall before recognition. Prior recall decreased false recognition in children, but increased false recognition in older adults. Across the lifespan, adolescents had the loosest criterion, children had the lowest false recall, and prior recall increased true recognition in older adults. [ABSTRACT FROM AUTHOR]