Acoustic Scenery Recognition Using CWT and Deep Neural Network

The development of acoustic scenes recognition systems has been a topic of extensive research due to its applications in several fields of science and engineering. This paper proposes an environmental system in which firstly a time-frequency representation is obtained using the Continuous Wavelet Transform (CWT). The time frequency representation is then represented as a color image using the Viridis color map, which is then inserted into a Deep Neural Network (DNN) to carry out the classification task. Evaluation results using several public data bases show that proposed scheme provides a classification performance better than the performance provided by other previously proposed schemes.

Motor Organization in Schizencephaly: Outcomes of Transcranial Magnetic Stimulation and Diffusion Tensor Imaging of Motor Tract Projections Correlate with the Different Domains of Hand Function

Objective. Schizencephaly is a rare congenital malformation that causes motor impairment. To determine the treatment strategy, each domain of the motor functions should be appropriately evaluated. We correlated a color map of diffusion tensor imaging (DTI) and transcranial magnetic stimulation (TMS) with the hand function test (HFT) to identify the type of hand function that each test (DTI and TMS) reflects. Further, we attempted to demonstrate the motor neuron organization in schizencephaly. Method. This retrospective study was conducted on 12 patients with schizencephaly. TMS was conducted in the first dorsal interosseous (FDI), biceps (BB), and deltoid muscles of the upper extremity, and contralateral MEP (cMEP) and ipsilateral MEP (iMEP) were recorded. The HFT included the grip strength, box and block (B&B), and 9-hole peg test. The schizencephalic cleft was confirmed using magnetic resonance imaging, and the corticospinal tract (CST) was identified using the color map of DTI. The symmetry indices for the peduncle and CST at pons level were calculated as the ratios of the cross-sectional area of the less-affected side and that of the more-affected side. Result. In the more-affected hemisphere TMS, no iMEP was obtained. In the less-affected hemisphere TMS, the iMEP response was detected in 9 patients and cMEP in all patients, which was similar to the pattern observed in unilateral lesion. Paretic hand grip strength was strongly correlated with the presence of iMEP ( p = 0.044 ). The symmetry index of the color map of DTI was significantly correlated with the B&B ( p = 0.008 , R 2 = 0.416 ), whereas the symmetry index of the peduncle was not correlated with all HFTs. Conclusion. In patients with schizencephaly, the iMEP response rate is correlated with the hand function related to strength, while the symmetricity of the CST by the color map of DTI is correlated with the hand function associated with dexterity. Additionally, we suggest the possible motor organization pattern of schizencephaly following interhemispheric competition.

Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication

Nowadays color in scientific visualizations is standard and extensively used to group, highlight or delineate different parts of data in visualizations. The rainbow color map (also known as jet color map) is famous for its appealing use of the full visual spectrum with impressive changes in chroma and luminance. Besides attracting attention, science has for decades criticized the rainbow color map for its non-linear and erratic change of hue and luminance along the data variation. The missed uniformity causes a misrepresentation of data values and flaws in science communication. The rainbow color map is scientifically incorrect and hardly decodable for a considerable number of people due to color vision deficiency (CVD) or other vision impairments. Here we aim to raise awareness of how widely used the rainbow color map still is in hydrology. To this end, we perform a paper survey scanning for color issues in around 1000 scientific publications in three different journals including papers published between 2005 and 2020. In this survey, depending on the journal, 16 %–24 % of the publications have a rainbow color map and around the same ratio of papers (18 %–29 %) uses red–green elements often in a way that color is the only possibility to decode the visualized groups of data. Given these shares, there is a 99.6 % chance to pick at least one visual problematic publication in 10 randomly chosen papers from our survey. To overcome the use of the rainbow color maps in science, we propose some tools and techniques focusing on improvement of typical visualization types in hydrological science. We give guidance on how to avoid, improve and trust color in a proper and scientific way. Finally, we outline an approach how the rainbow color map flaws should be communicated across different status groups in science.

Ultrasound Elastography for the Evaluation of Lymph Nodes

The differential diagnosis of lymphadenopathy is important for predicting prognosis, staging, and monitoring the treatment, especially for cancer patients. Conventional computed tomography and magnetic resonance imaging characterize lymph node (LN) with disappointing sensitivity and specificity. Conventional ultrasound with the advantage of high resolution has been widely used for the LN evaluation. Ultrasound elastography (UE) using color map or shear wave velocity can non-invasively demonstrate the stiffness and homogeneity of both the cortex and medulla of LNs and can detect early circumscribed malignant infiltration. There is a need of a review to comprehensively discuss the current knowledge of the applications of various UE techniques in the evaluation of LNs. In this review, we discussed the principles of strain elastography and shear wave-based elastography, and their advantages and limitations in the evaluation of LNs. In addition, we comprehensively introduced the applications of various UE techniques in the differential diagnosis of reactive LNs, lymphoma, metastatic LNs, and other lymphadenopathy. Moreover, the applications of endoscopic UE and endobronchial UE are also discussed, including their use for improving the positive rate of diagnosis of fine-needle aspiration biopsy.

Rainbow colors distort and mislead research in hydrology – guidance for better visualizations and science communication

Nowadays color in scientific visualizations is standard and extensively used to group, highlight or delineate different parts of data in visualizations. The rainbow color map (also known as jet color map) is famous for its appealing use of the full visual spectrum with impressive changes in chroma and luminance. Beside attracting attention, science has for decades criticized the rainbow color map for its non-linear and erratic change of hue and luminance along the data variation. The missed uniformity causes a misrepresentation of data values and flaws in science communication. The rainbow color map is scientifically incorrect and hardly decodable for a considerable number of people due to color-vision deficiency (CVD) or other vision impairments. Here we aim to raise awareness how widely used the rainbow color maps still is in hydrology. To this end we perform a paper survey scanning for color issues in around 1000 scientific publications in three different journals including papers published between 2005 and 2020. In this survey, depending on the journal, 16–24 % of the publications have a rainbow color map and around the same ratio of papers (18–29 %) use red-green elements often in a way that color is the only possibility to decode the visualized groups of data. Given these shares, there is a 99.6 % chance to pick at least one visual problematic publication in 10 randomly chosen papers from our survey. To overcome the use of the rainbow color maps in science, we propose some tools and techniques focusing on improvement of typical visualization types in hydrological science. Consequently, color should be used with more care to highlight most important aspects of a visualization and the identification of correct data types such as categorical or sequential data is essential to pick appropriate color maps. We give guidance how to avoid, improve and trust and color in a proper and scientific way. Finally, we sketch a way to improve the communication of rainbow flaws between different status groups in science, publishers, and the media.

The value of color-map virtual touch tissue imaging (CMV) in the differential diagnosis of benign and malignant breast lesions

BACKGROUND: Researchers have evaluated the VTI value in the diagnosis of breast lesions, mostly based on gray-scale. PURPOSE: This study aimed to evaluate the value of color-map virtual touch tissue imaging (CMV) in the diagnosis of breast lesions. METHODS: We retrospectively analyzed the virtual touch tissue imaging (VTI) images of 55 breast lesions in 49 female patients who underwent an examination of breast lesions in our hospital from January 2019 to December 2019. The pathological results were taken as the gold standard. The receiver operating characteristic (ROC) curve of CMV was analyzed, and its diagnostic performance was evaluated. Weighted Kappa (k) statistics were used to assess the inter-observer agreement for CMV. RESULTS: A total of 55 breast lesions were included, including 19 malignant lesions and 36 benign lesions. Multivariate analysis showed that patients with higher CMV scores (P = 0.014, odds ratio [OR] = 13.667, 95% CI = 1.702–109.773) were independent predictors of breast cancer. The sensitivity, specificity, and the area under curve (AUC) of CMV were 94.47%, 72.22%, and 0.912. The CMV’s inter-observer agreement was almost perfect among radiologists with different work experience (k = 0.854, standard error = 0.049, 95% confidence interval = 0.758–0.950). CONCLUSIOS: CMV has high accuracy and repeatability in the diagnosis of malignant breast lesions.