Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasound demonstration of mammographically detected microcalcifications.

PURPOSE To evaluate the capabilities of breast ultrasound (US) for identifying microcalcifications in benign breast changes, in situ carcinomas, and small nonpalpable invasive carcinomas. MATERIAL AND METHODS Forty-six consecutive patients with 49 clustered microcalcifications detected by mammography were included in this prospective study. Patients with palpable breast lesions were excluded. Breast US was performed with knowledge of mammographic findings for presence and visibility of microcalcifications, and for parenchymal structure abnormalities. Mammographic and US findings were compared with histology. RESULTS Nine ductal in situ carcinomas, 2 lobular in situ carcinomas, 11 invasive carcinomas and 27 benign lesions were confirmed by histology. For all lesions, US achieved a sensitivity of 75% in the detection of microcalcifications. The detection rate for microcalcification in invasive and in situ carcinomas was 100%. In 11 cases, no microcalcifications were visible on US; they all proved to be benign on histology. CONCLUSION Microcalcifications in malignant lesions are reliably recognized by US. They are, however, difficult to detect in fibrocystic breast changes.
Bidirectional Learning for Time-series Models with Hidden Units

Hidden units can play essential roles in modeling time-series having long-term dependency or nonlinearity but make it difficult to learn associated parameters. Here we propose a way to learn such a time-series model by training a backward model for the time-reversed time-series, where the backward model has a common set of parameters as the original (forward) model. Our key observation is that only a subset of the parameters is hard to learn, and that subset is complementary between the forward model and the backward model. By training both of the two models, we can effectively learn the values of the parameters that are hard to learn if only either of the two models is trained. We apply bidirectional learning to a dynamic Boltzmann machine extended with hidden units. Numerical experiments with synthetic and real datasets clearly demonstrate advantages of bidirectional learning.
DeshadowNet: A Multi-context Embedding Deep Network for Shadow Removal

Shadow removal is a challenging task as it requires the detection/annotation of shadows as well as semantic understanding of the scene. In this paper, we propose an automatic and end-to-end deep neural network (DeshadowNet) to tackle these problems in a unified manner. DeshadowNet is designed with a multi-context architecture, where the output shadow matte is predicted by embedding information from three different perspectives. The first global network extracts shadow features from a global view. Two levels of features are derived from the global network and transferred to two parallel networks. While one extracts the appearance of the input image, the other one involves semantic understanding for final prediction. These two complementary networks generate multi-context features to obtain the shadow matte with fine local details. To evaluate the performance of the proposed method, we construct the first large scale benchmark with 3088 image pairs. Extensive experiments on two publicly available benchmarks and our large-scale benchmark show that the proposed method performs favorably against several state-of-the-art methods.
Complex Urban Infrastructure Deformation Monitoring Using High Resolution PSI

The rising concern on the urban vulnerability to the intensive infrastructure development requires enabling technologies offering a prompt and accurate monitoring of urban infrastructures deformation. Urban infrastructures vary dramatically both spatially and temporally and their deformation characteristics are complex. We evaluated the potential of high resolution Persistent Scatterer Interferometry (PSI) technology using coherent stacks of Spotlight mode TerraSAR-X images in monitoring the deformations of different types of infrastructures in a new economics center in China. The high density of Persistent Scatterers (PSs) was identified and therefore facilitates analyzing the deformation character of individual structures. All PSs weer categorized by identifying their corresponding ground object so as to enable to characterize deformation pattern of certain type of urban infrastructure. The spatial and temporal varying patterns of the deformations of typical building infrastructures and transportation infrastructures are revealed. They are strongly related to the interactive effects between the types, engineering structures, geometries, engineering geological settings and various loading scenarios. Besides subsidence of the ground surface, thermal dilation of the infrastructure itself might be another factor accounting for the observed deformation of infrastructure. Although the interpretation for the observed deformation patterns could be quite site-specific, high resolution PSI is shown to have the potential to reveal detailed deformation characteristics of complex urban infrastructures at a relatively large scale.
Hypoxia-Inducible Factor Prolyl 4-Hydroxylase-2 Inhibition Protects Against Development of Atherosclerosis

Objective— Small-molecule hypoxia-inducible factor prolyl 4-hydroxylase (HIF-P4H) inhibitors are being explored in clinical studies for the treatment of anemia. HIF-P4H-2 (also known as PHD2 or EglN1) inhibition improves glucose and lipid metabolism and protects against obesity and metabolic dysfunction. We studied here whether HIF-P4H-2 inhibition could also protect against atherosclerosis. Approach and Results— Atherosclerosis development was studied in low-density lipoprotein (LDL) receptor–deficient mice treated with an oral HIF-P4H inhibitor, FG-4497, and in HIF-P4H-2-hypomorphic/C699Y-LDL receptor–mutant mice, all mice being fed a high-fat diet. FG-4497 administration to LDL receptor–deficient mice reduced the area of atherosclerotic plaques by ≈50% when compared with vehicle-treated controls and also reduced their weight gain, insulin resistance, liver and white adipose tissue (WAT) weights, adipocyte size, number of inflammation-associated WAT macrophage aggregates and the high-fat diet–induced increases in serum cholesterol levels. The levels of atherosclerosis-protecting circulating autoantibodies against copper-oxidized LDL were increased. The decrease in atherosclerotic plaque areas correlated with the reductions in weight, serum cholesterol levels, and WAT macrophage aggregates and the autoantibody increase. FG-4497 treatment stabilized HIF-1&agr; and HIF-2&agr; and altered the expression of glucose and lipid metabolism and inflammation-associated genes in liver and WAT. The HIF-P4H-2-hypomorphic/C699Y-LDL receptor–mutant mice likewise had a ≈50% reduction in atherosclerotic plaque areas, reduced WAT macrophage aggregate numbers, and increased autoantibodies against oxidized LDL, but did not have reduced serum cholesterol levels. Conclusions— HIF-P4H-2 inhibition may be a novel strategy for protecting against the development of atherosclerosis. The mechanisms involve beneficial modulation of the serum lipid profile and innate immune system and reduced inflammation.
Putting the community into Total Flood Warning Systems

The lead guiding document for the development of the Total Flood Warning System (TFWS) in Australia is ‘Manual 21 – Flood Warning’ (Attorney-General’s Department, 2009). According to Manual 21, the TFWS consists of six components: Prediction; Interpretation; Message Construction; Communication; Response; and, Review. In a review of these TFWS components in relation to the findings of previous social research and government inquiries into flood warning in Australia, Molino et al. (2011) identified a further six components of a TFWS: Understanding the Flood Risk; Emergency Management Planning; Community Flood Education; Data Collection; Community Participation in the TFWS; and, Integration of the TFWS Components. The twelve components have since been tested in the assessment of existing warning systems and the development of TFWSs for several communities across Australia. This paper provides a summary of the findings from these projects with a particular emphasis on the successes and challenges involving the more community-related TFWS components such as Understanding the Flood Risk, Community Flood Education and Community Participation. For example, the TFWS assessments found that: • Up to 20% of people living in floodplains were unaware of their flood risk • Community flood education tended to rely on the provision of information • There was little community participation in flood warning systems. The findings demonstrated the need to engage with communities about all twelve TFWS components and this paper concludes by explaining how this could be best done using tailored techniques.
Medical informatics and pediatrics. Decision-support systems.

Decision support is an important area of medical informatics research. Computer-based decision-support tools facilitate diagnosis and the management of patients after a diagnosis has been established. Diagnostic decision-support tools, such as Meditel, Quick Medical Reference, DXplain, Iliad, and PEM-DXP are potentially useful "expert systems. " Other management-support tools, such as systems that use clinical practice guidelines to create reminders and alerts, also have been developed and evaluated. We do the following: (1) to provide an overview of diagnostic and management decision-support systems; (2) explore the background of and motivation behind these systems; (3) survey the uses of decision-support technology in office-based and inpatient pediatric practices; and (4) discuss the virtues and problems associated with some of these tools, and current controversies and future goals for computer-based decision support.
Connexin Isoform Expression in Smooth Muscle Cells and Endothelial Cells of Hamster Cheek Pouch Arterioles and Retractor Feed Arteries

Objective: Gap junction channels formed by connexin (Cx) protein subunits enable cell‐to‐cell conduction of vasoactive signals. Given the lack of quantitative measurements of Cx expression in microvascular endothelial cells (EC) and smooth muscle cells (SMC), the objective was to determine whether Cx expression differed between EC and SMC of resistance microvessels for which conduction is well‐characterized.
Numerical investigations of soil plugging effect inside large-diameter, open-ended wind turbine monopiles driven by vibratory hammers

Abstract This study established a Couple Eulerian–Lagrange model to simulate monopile vibratory penetration for the investigation of soil plugging effect during high-frequency penetration of monopiles for wind turbine. Simulation analysis is focused particularly on soil plugging effect of a large diameter monopile during vibratory penetration into sand, clay, or layered soil. The results of the numerical simulation show that soil plugging effect is unlikely to occur during monopile penetration into the clay soil, while partial soil plugging may occur during the sand penetration. Penetration resistance at the pile toe is transferred to the radial stress around the pile wall. At a critical point penetration process, internal shaft friction becomes larger than external shaft friction. Moreover, radial pressure factors increase during partial soil plugging effect. For layered soil, the topsoil not only has great influence on the soil plugging effect, but also affects shaft friction in the subsoil during monopile penetration.
New Constructions of MDS Codes With Complementary Duals

Linear complementary-dual (LCD for short) codes are linear codes that intersect with their duals trivially. LCD codes have been used in certain communication systems. It is recently found that LCD codes can be applied in cryptography. This application of LCD codes renewed the interest in the construction of LCD codes having a large minimum distance. Maximum distance separable (MDS) codes are optimal in the sense that the minimum distance cannot be improved for given length and code size. Constructing LCD MDS codes is thus of significance in theory and practice. Recently, Jin constructed several classes of LCD MDS codes through generalized Reed-Solomon codes. In this paper, a different approach is proposed to obtain new LCD MDS codes from generalized Reed-Solomon codes. Consequently, new code constructions are provided and certain previously known results by Jin are extended.
LEEN: Locality/Fairness-Aware Key Partitioning for MapReduce in the Cloud

This paper investigates the problem of Partitioning Skew in MapReduce-based system. Our studies with Hadoop, a widely used MapReduce implementation, demonstrate that the presence of partitioning skew causes a huge amount of data transfer during the shuffle phase and leads to significant unfairness on the reduce input among different data nodes. As a result, the applications experience performance degradation due to the long data transfer during the shuffle phase along with the computation skew, particularly in reduce phase. We develop a novel algorithm named LEEN for locality-aware and fairness-aware key partitioning in MapReduce. LEEN embraces an asynchronous map and reduce scheme. All buffered intermediate keys are partitioned according to their frequencies and the fairness of the expected data distribution after the shuffle phase. We have integrated LEEN into Hadoop-0.18. 0. Our experiments demonstrate that LEEN can efficiently achieve higher locality and reduce the amount of shuffled data. More importantly, LEEN guarantees fair distribution of the reduce inputs. As a result, LEEN achieves a performance improvement of up to 40% on different workloads.
Paraoxonase-1 activities in children and adolescents with type 1 diabetes mellitus.

BACKGROUND Paraoxonase-1 is an HDL-associated esterase that acts as an anti-atherogenic agent by protecting LDL from oxidation. This study investigates paraoxonase-1 activities in children and adolescents with type 1 diabetes mellitus and possible associations with other biochemical markers. PATIENTS AND METHODS The study enrolled 82 children and adolescents with type 1 diabetes mellitus and 41 controls with similar age and gender distribution. Serum paraoxonase-1 arylesterase and salt-stimulated paraoxonase activities were assessed by measuring the rates of phenyl acetate and paraoxon hydrolysis, respectively; paraoxonase-1 lactonase activity and oxidized LDL were assessed by a pH-sensitive colorimetric assay and ELISA, respectively. Glycated haemoglobin HbA1c and lipid profile were assayed with an immunoturbidimetric method and commercially available kits, respectively. RESULTS We found lower paraoxonase-1 activities in diabetics when compared to controls. The decrease was statistically significant only for the lactonase activity, the difference being higher when referring to the subgroup with poor glycaemic control. The lactonase activity/HDL ratio was also lower in diabetics vs. controls, but without statistical significance. Both lactonase and arylesterase activities were negatively correlated with HbA1c in diabetics, but only the latter was statistically significant (ρ = -0.21, P = 0.055; ρ = -0.24, P = 0.03, respectively). A correlation coefficient of ρ = 0.196 (P = 0.078) was found between oxidized LDL and HbA1c. CONCLUSION All paraoxonase-1 activities were lower in diabetic children and adolescents, but only the decrease in the lactonase activity was statistically significant. Although lipid profile and glycaemic control were altered in diabetics, no differences were observed between groups regarding oxidized LDL level.
Characterization of Electrical Transitions Using Transmission Line Measurements

An analytical methodology for characterizing electrical transitions associated with transmission line-based microwave channels is presented in this paper. The methodology is formulated using ABCD matrixes obtained from S-parameters measured to two lines with different length and terminated with the transition under investigation. This allows to determine the two-port network parameters of the transition in a simple and direct way. Excellent results are obtained when characterizing coplanar waveguide-to-microstrip and coaxial-to-microstrip transitions. Moreover, the methodology was also successfully applied to obtain the network parameters of packages fabricated on printed circuit board technology.
Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer

A key barrier to the realization of personalized medicine for cancer is the identification of biomarkers. Here we describe a two-stage strategy for the discovery of serum biomarker signatures corresponding to specific cancer-causing mutations and its application to prostate cancer (PCa) in the context of the commonly occurring phosphatase and tensin homolog (PTEN) tumor-suppressor gene inactivation. In the first stage of our approach, we identified 775 N-linked glycoproteins from sera and prostate tissue of wild-type and Pten-null mice. Using label-free quantitative proteomics, we showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome. Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of PCa patients and control individuals. The resulting proteomic profiles were analyzed by machine learning to build predictive regression models for tissue PTEN status and diagnosis and grading of PCa. Our approach suggests a general path to rational cancer biomarker discovery and initial validation guided by cancer genetics and based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling.
The validity and value of inclusive fitness theory

Social evolution is a central topic in evolutionary biology, with the evolution of eusociality (societies with altruistic, non-reproductive helpers) representing a long-standing evolutionary conundrum. Recent critiques have questioned the validity of the leading theory for explaining social evolution and eusociality, namely inclusive fitness (kin selection) theory. I review recent and past literature to argue that these critiques do not succeed. Inclusive fitness theory has added fundamental insights to natural selection theory. These are the realization that selection on a gene for social behaviour depends on its effects on co-bearers, the explanation of social behaviours as unalike as altruism and selfishness using the same underlying parameters, and the explanation of within-group conflict in terms of non-coinciding inclusive fitness optima. A proposed alternative theory for eusocial evolution assumes mistakenly that workers' interests are subordinate to the queen's, contains no new elements and fails to make novel predictions. The haplodiploidy hypothesis has yet to be rigorously tested and positive relatedness within diploid eusocial societies supports inclusive fitness theory. The theory has made unique, falsifiable predictions that have been confirmed, and its evidence base is extensive and robust. Hence, inclusive fitness theory deserves to keep its position as the leading theory for social evolution.
Antioxidant Activity and Total Phenolic Content of Nerium oleander L. Grown in North of Iran

In this study, we have examined the antioxidant activity and total phenolic content of different extracts (including water, methanol, water : methanol and acetone) of Nerium oleander L. grown in the north of Iran by employing various in-vitro assay, i.e. DPPH free radical scavenging, reducing power and total antioxidant capacity through the Mo (VI) reduction. The extracts showed different levels of efficacy in each assay in a dose-dependent manner. Methanolic and aqueous methanolic extracts with the highest amount of total phenolic (by using the Folin-Ciocalteu phenol reagent method), were the most potent antioxidant in all of the assays that were used. According to the results of present study, Nerium oleander L. flowers were found to serve as a potential source of natural antioxidants.
Linkage of the Actin Cytoskeleton to the Postsynaptic Density via Direct Interactions of Abp1 with the ProSAP/Shank Family

Synaptic contacts contain elaborate cytomatrices on both sides of the synaptic cleft, which are believed to organize and link the different synaptic functions in time and space and can respond to different inner and outer cues with massive structural reorganizations. At the PSD (postsynaptic density), activity-dependent reorganizations of the cortical actin cytoskeleton are hypothesized to play a role in synaptic plasticity. Here, we report on interactions of the F-actin binding protein Abp1 with members of the ProSAP/Shank family: multidomain scaffolding PSD proteins interconnecting glutamate receptors with other synaptic components. Affinity-purification experiments demonstrate that the interactions are mediated by the Abp1 (actin-binding protein 1) SH3 (Src homology 3) domain, which associates with a proline-rich motif that is conserved within the C-terminal parts of ProSAP1(proline-rich synapse-associated protein 1)/Shank2 and ProSAP2/Shank3. The distribution of Abp1, ProSAP1, and ProSAP2 overlaps within the brain, and all three proteins are part of the PSD and are particularly enriched in cortex and hippocampus. Coimmunoprecipitation of endogenous Abp1 and ProSAP2 and colocalization studies of Abp1 and ProSAPs in hippocampal neurons indicate the in vivo relevance of the interactions. Intriguingly, in vivo recruitment assays demonstrate that Abp1 can bind to dynamic F-actin structures and ProSAPs simultaneously, suggesting that Abp1 might link different organizing elements in the PSD. Importantly, different paradigms of neuronal stimulation induce a redistribution of Abp1 to ProSAP-containing synapses. Our data suggest that ProSAPs may serve to localize Abp1 to dendritic spines, thus serving as attachment points for the dynamic postsynaptic cortical actin cytoskeleton. This creates a functional connection between synaptic stimulation and cytoskeletal rearrangements.
Mining Connection Pathways for Marked Nodes in Large Graphs

Suppose we are given a large graph in which, by some external process, a handful of nodes are marked. What can we say about these nodes? Are they close together in the graph? or, if segregated, how many groups do they form? We approach this problem by trying to find sets of simple connection pathways between sets of marked nodes. We formalize the problem in terms of the Minimum Description Length principle: a pathway is simple when we need only few bits to tell which edges to follow, such that we visit all nodes in a group. Then, the best partitioning is the one that requires the least number of bits to describe the paths that visit all the marked nodes. We prove that solving this problem is NP-hard, and introduce DOT2DOT, an efficient algorithm for partitioning marked nodes by finding simple pathways between nodes. Experimentation shows that DOT2DOT correctly groups nodes for which good connection paths can be constructed, while separating distant nodes.