Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of a Computer-Aided Diagnosis System in the Classification of Lesions in Breast Strain Elastography Imaging

Purpose: Evaluation of the performance of a computer-aided diagnosis (CAD) system based on the quantified color distribution in strain elastography imaging to evaluate the malignancy of breast tumors. Methods: The database consisted of 31 malignant and 52 benign lesions. A radiologist who was blinded to the diagnosis performed the visual analysis of the lesions. After six months with no eye contact on the breast images, the same radiologist and other two radiologists manually drew the contour of the lesions in B-mode ultrasound, which was masked in the elastography image. In order to measure the amount of hard tissue in a lesion, we developed a CAD system able to identify the amount of hard tissue, represented by red color, and quantify its predominance in a lesion, allowing classification as soft, intermediate, or hard. The data obtained with the CAD system were compared with the visual analysis. We calculated the sensitivity, specificity, and area under the curve (AUC) for the classification using the CAD system from the manual delineation of the contour by each radiologist. Results: The performance of the CAD system for the most experienced radiologist achieved sensitivity of 70.97%, specificity of 88.46%, and AUC of 0.853. The system presented better performance compared with his visual diagnosis, whose sensitivity, specificity, and AUC were 61.29%, 88.46%, and 0.829, respectively. The system obtained sensitivity, specificity, and AUC of 67.70%, 84.60%, and 0.783, respectively, for images segmented by Radiologist 2, and 51.60%, 92.30%, and 0.771, respectively, for those segmented by the Resident. The intra-class correlation coefficient was 0.748. The inter-observer agreement of the CAD system with the different contours was good in all comparisons. Conclusions: The proposed CAD system can improve the radiologist performance for classifying breast masses, with excellent inter-observer agreement. It could be a promising tool for clinical use.
Inland Water Atmospheric Correction Based on Turbidity Classification Using OLCI and SLSTR Synergistic Observations

Atmospheric correction is an essential prerequisite for obtaining accurate inland water color information. An inland water atmospheric correction algorithm, ACbTC (Atmospheric Correction based on Turbidity Classification), was proposed in this study by using OLCI (Ocean and Land Color Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer) synergistic observations for the first time. This method includes two main steps: (1) water turbidity classification by the GRA index (GRAdient of the spectrum index); and (2) atmospheric correction by synergistic use of OLCI and SLSTR images. The algorithm was validated with 72 in situ sampling sites in Lake Erhai, Lake Hongze, and Lake Taihu, and compared with other atmospheric correction methods, i.e., C2RCC (Case 2 Regional Coast Colour processor), MUMM (Management Unit of the North Seas Mathematical Models), FLAASH (Fast Line-of-sight Atmospheric Analysis of Hypercubes), POLYMER (POLYnomial based algorithm applied to MERIS), and BPAC (Bright Pixel Atmospheric Correction). The results show that (1) the GRA index performed better than the proposed turbidity classification indices, i.e., the Diff (spectral difference index) and the Tind (turbid index), in inland lakes by using the reflectance peak at 1020 nm in clean water; (2) the synergistic use of OLCI and SLSTR performed feasibly for atmospheric correction, and the ACbTC algorithm achieved full-band average values of the mean absolute percentage error (MAPE) = 29.55%, mean relative percentage error (MRPE) = 13.98%, and the root mean square of error (RMSE) = 0.0039 sr−1, which were more reliable than C2RCC, MUMM, FLAASH, POLYMER, and BPAC; and (3) the synergistic use of the 17th band (865 nm) on OLCI and the 5th band (1613 nm) on SLSTR are suitable for clean inland lakes, while both the 5th band (1613 nm) and 6th band (2250 nm) on SLSTR are advisable for the turbidity.
Integrating Guided Clustering in Visual Analytics to Support Domain Expert Reasoning Processes

Recent research shows promise in combining Information Visualization (IV) and Machine Learning (ML) to assist data analysis performed by domain experts. However, this approach presents non-trivial challenges, in particular when the goal is to incorporate knowledge provided by the domain expert in underlying ML algorithms. To address these challenges, we present an analytical process and a visual analytics tool that uses visual queries to capture examples from the domain experts’ existing reasoning process which will guide the subsequent clustering. Our work is motivated by a collaboration with personnel at the Danish Business Authority, who are interested in two types of insights: (1) On which data dimensions is a selected subset of companies different from the remaining companies? (2) Which other companies lie within the same multi-dimensional sub-space? The poster will illustrate a real analysis scenario, where the presented analytic process allows auditors to use their knowledge of identiﬁed "suspicious" companies to kick-start the analysis for others.
Experimental Evidence of a Variant Neutron Spectrum from the T(t,2n)α Reaction at Center-of-Mass Energies in the Range of 16-50 keV.

Full calculations of six-nucleon reactions with a three-body final state have been elusive and a long-standing issue. We present neutron spectra from the T(t,2n)α (TT) reaction measured in inertial confinement fusion experiments at the OMEGA laser facility at ion temperatures from 4 to 18 keV, corresponding to center-of-mass energies (E_{c.m.}) from 16 to 50 keV. A clear difference in the shape of the TT-neutron spectrum is observed between the two E_{c.m. }, with the ^{5}He ground state resonant peak at 8.6 MeV being significantly stronger at the higher than at the lower energy. The data provide the first conclusive evidence of a variant TT-neutron spectrum in this E_{c.m. } range. In contrast to earlier available data, this indicates a reaction mechanism that must involve resonances and/or higher angular momenta than L=0. This finding provides an important experimental constraint on theoretical efforts that explore this and complementary six-nucleon systems, such as the solar ^{3}He(^{3}He,2p)α reaction.
Equilibrative Nucleoside Transporter 1 (ENT1, SLC29A1) Facilitates Transfer of the Antiretroviral Drug Abacavir across the Placenta

Abacavir is a preferred antiretroviral drug for preventing mother-to-child human immunodeficiency virus transmission; however, mechanisms of its placental transfer have not been satisfactorily described to date. Because abacavir is a nucleoside-derived drug, we hypothesized that the nucleoside transporters, equilibrative nucleoside transporters (ENTs, SLC29A) and/or Na+-dependent concentrative nucleoside transporters (CNTs, SLC28A), may play a role in its passage across the placenta. To test this hypothesis, we performed uptake experiments using the choriocarcinoma-derived BeWo cell line, human fresh villous fragments, and microvillous plasma membrane (MVM) vesicles. Using endogenous substrates of nucleoside transporters, [3H]-adenosine (ENTs, CNT2, and CNT3) and [3H]-thymidine (ENTs, CNT1, and CNT3), we showed significant activity of ENT1 and CNT2 in BeWo cells, whereas experiments in the villous fragments and MVM vesicles, representing a model of the apical membrane of a syncytiotrophoblast, revealed only ENT1 activity. When testing [3H]-abacavir uptakes, we showed that of the nucleoside transporters, ENT1 plays the dominant role in abacavir uptake into placental tissues, whereas contribution of Na+-dependent transport, most likely mediated by CNTs, was observed only in BeWo cells. Subsequent experiments with dually perfused rat term placentas showed that Ent1 contributes significantly to overall [3H]-abacavir placental transport. Finally, we quantified the expression of SLC29A in first- and third-trimester placentas, revealing that SLC29A1 is the dominant isoform. Neither SLC29A1 nor SLC29A2 expression changed over the course of placental development, but there was considerable interindividual variability in their expression. Therefore, drug-drug interactions and the effect of interindividual variability in placental ENT1 expression on abacavir disposition into fetal circulation should be further investigated to guarantee safe and effective abacavir-based combination therapies in pregnancy.
Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments

The implementation of antiretroviral treatment combined with the monitoring of drug resistance mutations improves the quality of life of HIV-1 positive patients. The drug resistance mutation patterns and viral genotypes are currently analyzed by DNA sequencing of the virus in the plasma of patients. However, the virus compartmentalizes, and different T cell subsets may harbor distinct viral subsets. In this study, we compared the patterns of HIV distribution in cell-free (blood plasma) and cell-associated viruses (peripheral blood mononuclear cells, PBMCs) derived from ART-treated patients by using Sanger sequencing- and Next-Generation sequencing-based HIV assay. CD4+CD45RA−RO+ memory T-cells were isolated from PBMCs using a BD FACSAria instrument. HIV pol (protease and reverse transcriptase) was RT-PCR or PCR amplified from the plasma and the T-cell subset, respectively. Sequences were obtained using Sanger sequencing and Next-Generation Sequencing (NGS). Sanger sequences were aligned and edited using RECall software (beta v3.03). The Stanford HIV database was used to evaluate drug resistance mutations. Illumina MiSeq platform and HyDRA Web were used to generate and analyze NGS data, respectively. Our results show a high correlation between Sanger sequencing and NGS results. However, some major and minor drug resistance mutations were only observed by NGS, albeit at different frequencies. Analysis of low-frequency drugs resistance mutations and virus distribution in the blood compartments may provide information to allow a more sustainable response to therapy and better disease management.
The Social Picture: Advanced Image Analysis Applications

In The Social Picture (TSP) an huge amount of crowdsourced social images can be collected and explored. We distinguish three main kind of events: public, private and cultural heritage related ones. The framework embeds a number of advanced Computer Vision algorithms, able to capture the visual content of images and organize them in a semantic way. In this paper we employ VisualSFM (VSFM) to add new features in TSP through the computation of a 3D sparse reconstruction of a collection within TSP. VisualSFM creates a N-View Match (NVM) ﬁle as output. Starting from this NVM ﬁle, which characterizes the 3D sparse reconstruction, we are able to build two important relationships: the one between cameras and points and the one between cameras themselves. Using these relationships, we implemented two advanced Image Analysis applications. In the ﬁrst one, we consider the cameras as nodes in a fully connected graph in which the edges weights are equal to the number of matches between cameras. The spanning tree of this graph is used to explore images in a meaningful way, obtaining a scene summarization. In the second application, we deﬁne three kinds of density maps with relation to image features: density map, weighted-density map and social-weighted-density map. Results of a test conducted on a collection from TSP is shown. Categories and Subject Descriptors (according to ACM CCS) : I.3. 3 [Computer Graphics]: Display Algorithms—Viewing Algorithms. I.3. 8 [Computer Graphics]: Applications—
Spectral Interpretation and Applications of Decision Diagrams

Different Decision Diagrams (DDs) for representation of discrete functions are discussed. DDs can be derived by applying some reduction rules to Decision Trees (DTs) which in turn are graphical representations of some function expressions for discrete functions. Various DTs and their generalizations based on lesser known AND-EXOR rather than AND-OR expressions are surveyed. Finally, the concept of spectral interpretation of DDs and some of their applications and ways of calculation are also presented.
Detecting dietary preference of social media users in China via sentiment analysis

Dietary preferences are linked to all aspects of the human culture. Currently, researches on dietary preferences are mainly based on questionnaires, etc., which are mature and feasible. However, high cost, small scale and long timeframes are difficult to avoid. With the rapid development of social media, massive dietary reviews are shared in social media. Therefore, researches on users' dietary preferences by mining data from social media may overcome the disadvantages of traditional methods. In this paper, we use microblogs from weibo.com (one of the most popular social media platforms in China) to detect dietary preferences of social media users in China via sentiment analysis. Specifically, we compared four different aspect extraction methods and chose an optimal one to obtain aspects about dietary preferences. Secondly, sentiment polarities of the aspects and dishes are identified by sentiment classification. Empirical analysis on 3,975,800 microblogs presents that social media users in China are not satisfied with the overall status quo of dietary. In addition, experimental results show that semantic information is useful in extracting dietary aspects.
Airborne LiDAR Remote Sensing for Individual Tree Forest Inventory Using Trunk Detection-Aided Mean Shift Clustering Techniques

: Airborne LiDAR (Light Detection And Ranging) remote sensing for individual tree-level forest inventory necessitates proper extraction of individual trees and accurate measurement of tree structural parameters. Due to the inadequate tree ﬁnding capability offered by LiDAR technology and the complex patterns of forest canopies, signiﬁcant omission and commission errors occur frequently in the segmentation results. Aimed at error reduction and accuracy reﬁnement, this paper presents a novel adaptive mean shift-based clustering scheme aided by a tree trunk detection technique to segment individual trees and estimate tree structural parameters based solely on the airborne LiDAR data. Tree trunks are detected by analyzing points’ vertical histogram to detach all potential crown points and then clustering the separated trunk points according to their horizontal mutual distances. The detected trunk information is used to adaptively calibrate the kernel bandwidth of the mean shift procedure in the ﬁne segmentation stage by applying an original 2D (two-dimensional) estimation of individual crown diameters. Trunk detection results and LiDAR point clusters generated by the adaptive mean shift procedures serve as mutual references for ﬁnal detection of individual trees. Experimental results show that a combination of adaptive mean shift clustering and detected tree trunk can provide a signiﬁcant performance improvement in individual tree-level forest measurement. Compared with conventional clustering techniques, the trunk detection-aided mean shift clustering approach can detect 91.1% of the trees (“recall”) with a higher tree positioning accuracy (the mean positioning error is reduced by 33%) in a multi-layered coniferous and broad-leaved mixed forest in South China, and 93.5% of the identiﬁed trees are correct (“precision”). The tree detection brings the estimation of structural parameters for individual trees up to an accuracy level: − 2.2% mean relative error and 5.8% relative RMSE (Root Mean Square Error) for tree height and 0.6% mean relative error and 21.9% relative RMSE for crown diameter, respectively.
Interleukin-1 Receptor Antagonist Is Associated With Pediatric Acute Respiratory Distress Syndrome and Worse Outcomes in Children With Acute Respiratory Failure*

Objectives: To test whether plasma interleukin-1 receptor antagonist or variants within the gene encoding for interleukin-1ra (IL1RN), or proteins involved in regulating interleukin-1&bgr; levels or interleukin-1&bgr; response, are associated with pediatric acute respiratory distress syndrome or outcomes in mechanically ventilated children with parenchymal lung disease. Design: Prospective cohort study. Setting: Twenty-two PICUs participating in the multisite clinical trial, Randomized Evaluation of Sedation Titration for Respiratory Failure (U01 HL086622). Subjects: Children 2 weeks to 17 years old treated with invasive mechanical ventilation for acute airways and/or parenchymal lung disease. Measurements and Main Results: Three-hundred seventy-eight of 549 patients had pediatric acute respiratory distress syndrome; DNA and plasma were obtained from 523 of 549 and 480 of 549 patients, respectively. Plasma interleukin-1ra was highest on the day of intubation (day 0) and decreased over the subsequent 3 days (p < 0.0001). Interleukin-1ra level was higher in patients with pediatric acute respiratory distress syndrome than those without pediatric acute respiratory distress syndrome (p < 0.0001). Multivariable regression analysis of data across all days demonstrated a significant association of interleukin-1ra (odds ratio, 1.30; 95% CI, 1.10–1.52; p = 0.002) and day (p < 0.05) with pediatric acute respiratory distress syndrome, independent of age and Pediatric Risk of Mortality-III score. Analysis on individual days indicated that plasma interleukin-1ra levels were associated with pediatric acute respiratory distress syndrome on days 0 and 2, independent of age and Pediatric Risk of Mortality-III score (p = 0.04 and 0.003, respectively), however did not quite reach significance on days 1 and 3 (p = 0.06 and 0.07, respectively). Interleukin-1ra was independently associated with mortality on day 1 (p = 0.02). Interleukin-1ra also correlated with length of mechanical ventilation, measures of oxygenation, and PICU length of stay. No genetic variants were associated with pediatric acute respiratory distress syndrome. Conclusions: Plasma interleukin-1ra is associated with pediatric acute respiratory distress syndrome, PICU length of stay, length of mechanical ventilation, and mortality in children with acute respiratory failure requiring mechanical ventilation.
Deformation Response of Seismogenic Faults to the Wenchuan MS 8.0 Earthquake: A Case Study for the Southern Segment of the Longmenshan Fault Zone

The spatiotemporal deformation response of a seismogenic fault to a large earthquake is of great significance to understanding the nucleation and occurrence of the next strong earthquake. The Longmeshan fault, where the 2008 Wenchuan MS 8.0 earthquake and 2013 Lushan MS 7.0 earthquake occurred, provides an opportunity for us to study this important issue. Based on the GPS observations, we exploit the deformation response of the Southern Segment of the Longmenshan Fault (SSLMF) to the Wenchuan earthquake. The results are as follows: (1) during the co-seismic and post-seismic processes of the Wenchuan earthquake, the deformation is dominated by a continuous pattern in the SSLMF, which is different from the rupture pattern in the middle-northern segment of the Longmenshan Fault (LMF). Quantitatively, the compressive strain present between 2008 and 2013 was equal to the strain accumulation of 69 years during the interseismic period in the SSLMF. If the statistics scope is restricted to the eastern region of the Anxian-Guanxian Fault (AGF), which covers the Lushan source area (Abbr.: Eastern Region), the value is about 25 years; (2) After the Wenchuan earthquake, the strain accumulation pattern changes significantly. First, the deformation adjustment (especially the shear deformation) in the region that crosses the Maoxian-Wenchuan Fault (MWF) and Beichuan-Yingxiu Fault (BYF) (Abbr.: Western Region) is significantly greater than that in the Eastern Region. Furthermore, the crustal shortening is significant in the Eastern Region with minor adjustments in shear deformation. Second, the azimuth angles of the principal compressive strain rate in both regions show significant adjustments, which change fast in the first year of the observation period and then turn into the stable state. In general, the deformation responses of the SSLMF reveal that the Wenchuan earthquake promotes the occurrence of the Lushan earthquake. Their differences in the spatiotemporal domain can be attributed to the influence of afterslip, viscous relaxation of the lithosphere, mechanical parameters and block movement.
Deep Learning-Based Enhanced Presentation Attack Detection for Iris Recognition by Combining Features from Local and Global Regions Based on NIR Camera Sensor

Iris recognition systems have been used in high-security-level applications because of their high recognition rate and the distinctiveness of iris patterns. However, as reported by recent studies, an iris recognition system can be fooled by the use of artificial iris patterns and lead to a reduction in its security level. The accuracies of previous presentation attack detection research are limited because they used only features extracted from global iris region image. To overcome this problem, we propose a new presentation attack detection method for iris recognition by combining features extracted from both local and global iris regions, using convolutional neural networks and support vector machines based on a near-infrared (NIR) light camera sensor. The detection results using each kind of image features are fused, based on two fusion methods of feature level and score level to enhance the detection ability of each kind of image features. Through extensive experiments using two popular public datasets (LivDet-Iris-2017 Warsaw and Notre Dame Contact Lens Detection 2015) and their fusion, we validate the efficiency of our proposed method by providing smaller detection errors than those produced by previous studies.
Anti‐carcinogenic effect of hesperidin against renal cell carcinoma by targeting COX‐2/PGE2 pathway in Wistar rats

The present study was designed to evaluate the protective effects of hesperidin, a flavonoid on DEN initiated and Fe‐NTA promoted renal carcinogenesis in Wistar rats. Renal cancer was initiated by a single i.p. injection of DEN (200 mg/kg b.wt.) and promoted with Fe‐NTA (9 mg Fe/kg b.wt. i.p.) twice a week for 16 weeks. Rats were simultaneously administered with hesperidin (100 and 200 mg/kg b.wt.) for 16 consecutive weeks. The chemopreventive effect of hesperidin was assessed in terms of antioxidant activities, renal function, PGE2 level, and the expressions of COX‐2 and VEGF. Hesperidin decreased the DEN and Fe‐NTA induced lipid peroxidation, improved the renal function (by decreasing the levels of BUN, creatinine, and KIM‐1) and restored the renal antioxidant armory (GSH, GPx, GR, SOD, and catalase). Hesperidin was also found to decrease the level of PGE2 and downregulate the expressions of COX‐2 and VEGF. Histological findings further revealed the protective effects of hesperidin against DEN and Fe‐NTA induced kidney damage. The result of our present findings suggest that hesperidin may be a promising modulator in preventing renal cancer possibly by virtue of its ability to alleviate oxidative stress and inhibit COX‐2/PGE2 pathway.