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Frontiers in Psychology 2024Nowadays there are multiple ways to perceive music, from attending concerts (live) to listening to recorded music through headphones (medial). In between there are many...
Nowadays there are multiple ways to perceive music, from attending concerts (live) to listening to recorded music through headphones (medial). In between there are many mixed modes, such as playback performances. In empirical music research, this plurality of performance forms has so far found little recognition. Until now no measuring instrument has existed that could adequately capture the differences in perception and aesthetic judgment. The purpose of our empirical investigation was to capture all dimensions relevant to such an assessment. Using 3D-simulations and dynamic binaural synthesis, various live and medial situations were simulated. A qualitative survey was conducted at the Department of Audio Communication of the Technical University of Berlin (TU Berlin). With the help of the repertory grid technique, a data pool of approximately 400 attribute pairs was created and individual rating data were collected. Our first study served to create a semantic differential. In a second study, this semantic differential was evaluated. The development of the semantic differential was carried out by first using a mixed-method approach to qualitative analysis according to grounded theory. Thereafter, a principal component analysis reduced the attribute pairs to 67 items in four components. The semantic differential consists of items concerning acoustic, visual and audio-visual interaction as well as items with an overarching assessment of the stimuli. The evaluation study, comprising 45 participants (23 male and 22 female, = 42.56 years, = 17.16) who rated 12 stimuli each, reduced the items to 61 and resulted in 18 subscales and nine single items. Because the survey used simulations, the social component may be underrepresented. Nevertheless, the questionnaire we created enables the evaluation of music performances (especially for classical concerts) in a new scope, thus opening many opportunities for further research. For example, in a live concert context, we observed not only that seating position influences the judgment of sound quality but also that visual elements influence immersion and felt affect. In the future, the differential could be reviewed for a larger stimulus pool, extended or used modularly for different research questions.
PubMed: 38629034
DOI: 10.3389/fpsyg.2024.1339168 -
BMC Medical Imaging Apr 2024Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized...
BACKGROUND
Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours.
METHODS
We randomised data from 849 patients with ovarian tumours into training and testing sets in a ratio of 8:2. The regions of interest on the US images were segmented and handcrafted radiomics features were extracted and screened. We applied the one-versus-rest method in multiclass classification. We inputted the best features into machine learning (ML) models and constructed a radiomic signature (Rad_Sig). US images of the maximum trimmed ovarian tumour sections were inputted into a pre-trained convolutional neural network (CNN) model. After internal enhancement and complex algorithms, each sample's predicted probability, known as the deep transfer learning signature (DTL_Sig), was generated. Clinical baseline data were analysed. Statistically significant clinical parameters and US semantic features in the training set were used to construct clinical signatures (Clinic_Sig). The prediction results of Rad_Sig, DTL_Sig, and Clinic_Sig for each sample were fused as new feature sets, to build the combined model, namely, the deep learning radiomic signature (DLR_Sig). We used the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) to estimate the performance of the multiclass classification model.
RESULTS
The training set included 440 benign, 44 borderline, and 196 malignant ovarian tumours. The testing set included 109 benign, 11 borderline, and 49 malignant ovarian tumours. DLR_Sig three-class prediction model had the best overall and class-specific classification performance, with micro- and macro-average AUC of 0.90 and 0.84, respectively, on the testing set. Categories of identification AUC were 0.84, 0.85, and 0.83 for benign, borderline, and malignant ovarian tumours, respectively. In the confusion matrix, the classifier models of Clinic_Sig and Rad_Sig could not recognise borderline ovarian tumours. However, the proportions of borderline and malignant ovarian tumours identified by DLR_Sig were the highest at 54.55% and 63.27%, respectively.
CONCLUSIONS
The three-class prediction model of US-based DLR_Sig can discriminate between benign, borderline, and malignant ovarian tumours. Therefore, it may guide clinicians in determining the differential management of patients with ovarian tumours.
Topics: Humans; Female; Deep Learning; Radiomics; Ovarian Neoplasms; Ultrasonography; Algorithms; Retrospective Studies
PubMed: 38622546
DOI: 10.1186/s12880-024-01251-2 -
Heliyon Apr 2024To better meet the emotional needs of older residents and to improve the design of age-friendly indoor interface forms, this study uses Kansei engineering as the...
To better meet the emotional needs of older residents and to improve the design of age-friendly indoor interface forms, this study uses Kansei engineering as the theoretical basis for an exploration of the mapping relationship between emotional needs and interface forms. First, we collected spatial interface forms through in-home research, and using focus groups, we summarized and produced test samples for interface forms; at the same time, we screened out adjective word pairs that could fully represent the emotional needs of older people in the city of Jinan, drawing on expert interviews; then, we invited 500 older adults living in Jinan all year to evaluate each interface form using representative adjective word pairs as the emotional evaluation criteria, following the semantic differential method. Subsequently, the participants were invited to evaluate and score the interface form samples using representative adjective word pairs as the standard of emotional evaluation, employing the semantic differential method. Finally, the evaluation scores were input into SPSS software for the Kruskal-Wallis test to explore the relationships between various interface forms and emotional needs. The experimental results showed that the assessment scoring results for each interface form in each set of pairs of adjectives that differed significantly, where each interface had a clear emotional tendency. This study successfully established a mapping model for matching indoor interface forms with emotional needs in age-friendly housing in Jinan. These findings can provide a reference for future practice of designing residential indoor interface forms to match the emotional needs of older people in Jinan.
PubMed: 38601559
DOI: 10.1016/j.heliyon.2024.e29129 -
The Western Journal of Emergency... Mar 2024Despite the importance of peer review to publications, there is no generally accepted approach for editorial evaluation of a peer review's value to a journal editor's...
INTRODUCTION
Despite the importance of peer review to publications, there is no generally accepted approach for editorial evaluation of a peer review's value to a journal editor's decision-making. The graduate medical education editors of the Special Issue in Educational Research & Practice (Special Issue) developed and studied the holistic editor's scoring rubric (HESR) with the objective of assessing the quality of a review and an emphasis on the degree to which it informs a holistic appreciation for the submission under consideration.
METHODS
Using peer-review guidelines from several journals, the Special Issue's editors formulated the rubric as descriptions of peer reviews of varying degree of quality from the ideal to the unacceptable. Once a review was assessed by each editor using the rubric, the score was submitted to a third party for blinding purposes. We compared the performance of the new rubric to a previously used semantic differential scale instrument. Kane's validity framework guided the evaluation of the new scoring rubric around three basic assumptions: improved distribution of scores; relative consistency rather than absolute inter-rater reliability across editors; and statistical evidence that editors valued peer reviews that contributed most to their decision-making.
RESULTS
Ninety peer reviews were the subject of this study, all were assessed by two editors. Compared to the highly skewed distribution of the prior rating scale, the distribution of the new scoring rubric was bell shaped and demonstrated full use of the rubric scale. Absolute agreement between editors was low to moderate, while relative consistency between editor's rubric ratings was high. Finally, we showed that recommendations of higher rated peer reviews were more likely to concur with the editor's formal decision.
CONCLUSION
Early evidence regarding the HESR supports the use of this instrument in determining the quality of peer reviews as well as its relative importance in informing editorial decision-making.
Topics: Humans; Pilot Projects; Reproducibility of Results; Peer Review; Education, Medical, Graduate; Emergency Medicine
PubMed: 38596927
DOI: 10.5811/westjem.18432 -
Alzheimer's Research & Therapy Apr 2024Differential diagnosis among subjects with Primary Progressive Aphasia (PPA) can be challenging. Structural MRI can support the clinical profile. Visual rating scales...
INTRODUCTION
Differential diagnosis among subjects with Primary Progressive Aphasia (PPA) can be challenging. Structural MRI can support the clinical profile. Visual rating scales are a simple and reliable tool to assess brain atrophy in the clinical setting. The aims of the study were to establish to what extent the visual rating scales could be useful in the differential diagnosis of PPA, to compare the clinical diagnostic impressions derived from routine MRI interpretations with those obtained using the visual rating scale and to correlate results of the scales in a voxel-based morphometry (VBM) analysis.
METHOD
Patients diagnosed with primary progressive aphasia (PPA) according to current criteria from two centers-Ospedale Maggiore Policlinico of Milan and Hospital Clínic de Barcelona-were included in the study. Two blinded clinicians evaluated the subjects MRIs for cortical atrophy and white matter hyperintensities using two protocols: routine readings and the visual rating scale. The diagnostic accuracy between patients and controls and within PPA subgroups were compared between the two protocols.
RESULTS
One hundred fifty Subjects were studied. All the scales showed a good to excellent intra and inter-rater agreement. The left anterior temporal scale could differentiate between semantic PPA and all other variants. The rater impression after the protocol can increase the accuracy just for the logopenic PPA. In the VBM analysis, the scores of visual rating scales correlate with the corresponding area of brain atrophy.
CONCLUSION
The Left anterior temporal rating scale can distinguish semantic PPA from other variants. The rater impression after structured view improved the diagnostic accuracy of logopenic PPA compared to normal readings. The unstructured view of the MRI was reliable for identifying semantic PPA and controls. Neither the structured nor the unstructured view could identify the nonfluent and undetermined variants.
Topics: Humans; Brain; Aphasia, Primary Progressive; Magnetic Resonance Imaging; Positron-Emission Tomography; Atrophy
PubMed: 38582927
DOI: 10.1186/s13195-024-01442-7 -
Brain Communications 2024The posterior cingulate cortex (PCC) is a key hub of the default mode network underlying autobiographical memory retrieval, which falters early in the progression of...
The posterior cingulate cortex (PCC) is a key hub of the default mode network underlying autobiographical memory retrieval, which falters early in the progression of Alzheimer's disease (AD). We recently performed RNA sequencing of post-mortem PCC tissue samples from 26 elderly Rush Religious Orders Study participants who came to autopsy with an ante-mortem diagnosis of no cognitive impairment but who collectively displayed a range of Braak I-IV neurofibrillary tangle stages. Notably, cognitively unimpaired subjects displaying high Braak stages may represent cognitive resilience to AD pathology. Transcriptomic data revealed elevated synaptic and ATP-related gene expression in Braak Stages III/IV compared with Stages I/II, suggesting these pathways may be related to PCC resilience. We also mined expression profiles for small non-coding micro-RNAs (miRNAs), which regulate mRNA stability and may represent an underexplored potential mechanism of resilience through the fine-tuning of gene expression within complex cellular networks. Twelve miRNAs were identified as differentially expressed between Braak Stages I/II and III/IV. However, the extent to which the levels of all identified miRNAs were associated with subject demographics, neuropsychological test performance and/or neuropathological diagnostic criteria within this cohort was not explored. Here, we report that a total of 667 miRNAs are significantly associated (rho > 0.38, < 0.05) with subject variables. There were significant positive correlations between miRNA expression levels and age, perceptual orientation and perceptual speed. By contrast, higher miRNA levels correlated negatively with semantic and episodic memory. Higher expression of 15 miRNAs associated with lower Braak Stages I-II and 47 miRNAs were associated with higher Braak Stages III-IV, suggesting additional mechanistic influences of PCC miRNA expression with resilience. Pathway analysis showed enrichment for miRNAs operating in pathways related to lysine degradation and fatty acid synthesis and metabolism. Finally, we demonstrated that the 12 resilience-related miRNAs differentially expressed in Braak Stages I/II versus Braak Stages III/IV were predicted to regulate mRNAs related to amyloid processing, tau and inflammation. In summary, we demonstrate a dynamic state wherein differential PCC miRNA levels are associated with cognitive performance and post-mortem neuropathological AD diagnostic criteria in cognitively intact elders. We posit these relationships may inform miRNA transcriptional alterations within the PCC relevant to potential early protective (resilience) or pathogenic (pre-clinical or prodromal) responses to disease pathogenesis and thus may be therapeutic targets.
PubMed: 38572270
DOI: 10.1093/braincomms/fcae082 -
A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops.Frontiers in Plant Science 2024Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing...
Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant . On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene and the polyphenotype gene were verified via a literature search. Furthermore, the wheat gene was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.
PubMed: 38571713
DOI: 10.3389/fpls.2024.1361716 -
Frontiers in Systems Neuroscience 2024Primary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and...
INTRODUCTION
Primary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and non-fluent/agrammatic (nfvPPA) variants. Diagnosing and classifying PPA patients represents a complex challenge that requires the integration of multimodal information, including clinical, biological, and radiological features. Structural neuroimaging can play a crucial role in aiding the differential diagnosis of PPA and constructing diagnostic support systems.
METHODS
In this study, we conducted a white matter texture analysis on T1-weighted images, including 56 patients with PPA (31 svPPA and 25 nfvPPA), and 53 age- and sex-matched controls. We trained a tree-based algorithm over combined clinical/radiomics measures and used Shapley Additive Explanations (SHAP) model to extract the greater impactful measures in distinguishing svPPA and nfvPPA patients from controls and each other.
RESULTS
Radiomics-integrated classification models demonstrated an accuracy of 95% in distinguishing svPPA patients from controls and of 93.7% in distinguishing svPPA from nfvPPA. An accuracy of 93.7% was observed in differentiating nfvPPA patients from controls. Moreover, Shapley values showed the strong involvement of the white matter near left entorhinal cortex in patients classification models.
DISCUSSION
Our study provides new evidence for the usefulness of radiomics features in classifying patients with svPPA and nfvPPA, demonstrating the effectiveness of an explainable machine learning approach in extracting the most impactful features for assessing PPA.
PubMed: 38562661
DOI: 10.3389/fnsys.2024.1324437 -
Scientific Reports Apr 2024This study aimed to investigate the effects of reproducing an ultrasonic sound above 20 kHz on the subjective impressions of water sounds using psychological and...
This study aimed to investigate the effects of reproducing an ultrasonic sound above 20 kHz on the subjective impressions of water sounds using psychological and physiological information obtained by the semantic differential method and electroencephalography (EEG), respectively. The results indicated that the ultrasonic component affected the subjective impression of the water sounds. In addition, regarding the relationship between psychological and physiological aspects, a moderate correlation was confirmed between the EEG change rate and subjective impressions. However, no differences in characteristics were found between with and without the ultrasound component, suggesting that ultrasound does not directly affect the relationship between subjective impressions and EEG energy at the current stage. Furthermore, the correlations calculated for the left and right channels in the occipital region differed significantly, which suggests functional asymmetry for sound perception between the right and left hemispheres.
Topics: Sound; Hearing; Electroencephalography; Auditory Perception; Acoustic Stimulation
PubMed: 38561365
DOI: 10.1038/s41598-024-57749-w -
PloS One 2024Android malware is becoming more common, and its invasion of smart devices has brought immeasurable losses to people's lives. Most existing Android malware detection...
Android malware is becoming more common, and its invasion of smart devices has brought immeasurable losses to people's lives. Most existing Android malware detection methods extract Android features from the original application files without considering the high-order hidden information behind them, but these hidden information can reflect malicious behaviors. To solve this problem, this paper proposes Z2F, a detection framework based on multidimensional Android feature extraction and graph neural networks for Android applications. Z2F first extracts seven types of Android features from the original Android application and then embeds them into a heterogeneous graph. On this basis, we design 12 kinds of meta-structures to analyze different semantic spaces of heterogeneous graphs, mine high-order hidden semantic information, and adopt a multi-layer graph attention mechanism to iteratively embed and update information. In this paper, a total of 14429 Android applications were detected and 1039726 Android features were extracted, with a detection accuracy of 99.7%.
Topics: Humans; Neural Networks, Computer; Records; Semantic Differential; Semantics
PubMed: 38547074
DOI: 10.1371/journal.pone.0300975