Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Lesion-to-Fat Elasticity Ratio Measured by Shear-Wave Elastography for Breast Mass: Which Area Should Be Selected as the Fat Reference?

Objectives To investigate whether the diagnostic performance of lesion-to-fat elasticity ratio (Eratio) was affected by the location of the reference fat. Methods For 257 breast masses in 250 women who underwent shear-wave elastography before biopsy or surgery, multiple Eratios were measured with a fixed region-of-interest (ROI) in the mass along with multiple ROIs over the surrounding fat in different locations. Logistic regression analysis was used to determine that Eratio was independently associated with malignancy adjusted for the location of fat ROI (depth, laterality, and distance from lesion or skin). Mean (Emean) and maximum (Emax) elasticity values of fat were divided into four groups according to their interquartile ranges. Diagnostic performance of each group was evaluated using the area under the ROC curve (AUC). False diagnoses of Eratio were reviewed for ROIs on areas showing artifactual high or low stiffness and analyzed by logistic regression analysis to determine variables (associated palpable abnormality, lesion size, the vertical distance from fat ROI to skin, and elasticity values of lesion or fat) independently associated with false results. Results Eratio was independently associated with malignancy adjusted for the location of fat ROI (P<0.0001). Among four groups of fat elasticity values, the AUC showed no significant difference (<25th percentile, 25th percentile~median, median~75th percentile, and ≥75th percentile; 0.973, 0.982, 0.967, and 0.954 for Emean; 0.977, 0.967, 0.966, and 0.957 for Emax). Fat elasticity values were independently associated with false results of Eratio with the cut-off of 3.18 from ROC curve (P<0.0001). ROIs were set on fat showing artifactual high stiffness in 90% of 10 false negatives and on lesion showing vertical striped artifact or fat showing artifactual low stiffness in 77.5% of 71 false positives. Conclusion Eratio shows good diagnostic performance regardless of the location of reference fat, except when it is placed in areas of artifacts.
Dimension and liner dependent thermomechanical strain characterization of through-silicon vias using synchrotron x-ray diffraction

Strain measurements are demonstrated for through-silicon vias (TSVs) using synchrotron x-ray diffraction to characterize the effect of copper via dimensions and liner materials. Reduction in strains in the silicon around TSVs is observed for the TSVs with smaller via diameters and the TSVs with a thicker polymer liner. To interpret the measured two-dimensional (2D) TSV strain distribution maps of the three-dimensional (3D) TSV strains, a data averaging method based on the energy dependent x-ray absorption is implemented along with additional considerations from the sample preparation by means of an indirect comparison methodology.
HD 172481: A super lithium-rich metal-deficient post-AGB binary with a red AGB companion

We present in this paper a study on the peculiar supergiant HD 172481. Its spectral type (F2Ia), high galactic latitude ( b = -10 fraction of degree37), circumstellar dust, high radial velocity and moderate metal deficiency ([Fe/H] = -0.55) confirm the post-AGB character of this object. A detailed chemical analysis shows slight but real s -process overabundances, however no CNO-enhancement was detected. Furthermore, the spectral energy distribution and the TiO bands in the red part of the spectrum reveal a red luminous companion. The luminosity ratio of the hot F type component and this cool M type companion $L_{\rm F}/L_{\rm M}$ is derived for a reddening of $E(B-V)=0.44$ ($L_{\rm F}/L_{\rm M} \sim 1.8$) and indicates that the companion must also be strongly evolved and probably evolving along the AGB. Neither our photometric data-set, nor our radial velocity monitoring show evidence for orbital variability which may indicate that the period is too large for direct binary interaction. Most interestingly, a strong lithium resonance line is detected, which yields an abundance of $\log\epsilon({\rm Li})$ = 3.6. Several explanations for this large lithium content are explored.
An Improved MPPT Method for PV System With Fast-Converging Speed and Zero Oscillation

Maximum power point tracking (MPPT) is essential for photovoltaic (PV) systems to ensure the highest power output of PV arrays under any environmental condition. Comparing to other techniques, the Beta method shows advantages in terms of tracking speed, steady-state performance, and simple implementation. However, the conventional Beta can further be improved by minimizing oscillations around the maximum power point under a steady state and an increasing tracking speed in response to rapid changing of irradiance or temperature. An improved Beta-parameter-based MPPT method is proposed in this paper to achieve the above-mentioned objectives. An adaptive scaling factor is introduced and utilized in the MPPT mechanism, which enhances the tracking speed and is easily applied for any PV power system. Furthermore, the proposed method can identify and maintain the middle point of the three-level perturbations, which eliminate the oscillations at a steady state. The control mechanism is not limited by specific operating conditions and illustrates superior performance over traditional methods with regards to transient response and steady-state performance, which contributes to effective solar power harvesting. Followed by theoretical analysis, the simulation and experimental evaluation validate the claimed advantages of the proposed MPPT solution.
A context-based privacy preserving framework for wearable visual lifeloggers

The ability of wearable cameras to continuously capture the first person viewpoint with minimal user interaction, has made them very attractive in many application domains. Wearable technology today is available and useful but not widely used and accepted due to various challenges mainly privacy concerns. In this paper, we introduce a novel efficient privacy-aware framework for wearable cameras that can protect all sensitive subjects such as people, objects (e.g, display screens, license plates and credit cards) and locations (e.g, bathrooms and bedrooms). It uses the contextual information obtained from the wearable's sensors and recorded images to identify the potential sensitive subjects in each image. Using image processing techniques, first the sensitive subjects are recognized and then blurred or eliminated. Finally the edited image is ready to publish. Using a practical case study, we experimentally evaluate the proposed framework. Our experimental results show that the proposed system can detect and blur the sensitive subjects among around 300 images with around 70% accuracy.
"The Sum of Its Parts": Joint Learning of Word and Phrase Representations with Autoencoders

Recently, there has been a lot of effort to represent words in continuous vector spaces. Those representations have been shown to capture both semantic and syntactic information about words. However, distributed representations of phrases remain a challenge. We introduce a novel model that jointly learns word vector representations and their summation. Word representations are learnt using the word co-occurrence statistical information. To embed sequences of words (i.e. phrases) with different sizes into a common semantic space, we propose to average word vector representations. In contrast with previous methods which reported a posteriori some compositionality aspects by simple summation, we simultaneously train words to sum, while keeping the maximum information from the original vectors. We evaluate the quality of the word representations on several classical word evaluation tasks, and we introduce a novel task to evaluate the quality of the phrase representations. While our distributed representations compete with other methods of learning word representations on word evaluations, we show that they give better performance on the phrase evaluation. Such representations of phrases could be interesting for many tasks in natural language processing.
Lip color classification based on support vector machine and histogram

According to observe diagnostics theory of Traditional Chinese Medicine (TCM), the lip color of one person is considered as symptoms and signs to diagnose whether his spleen or stomach is healthy or not. In traditional diagnostics method, the lip color is recognized by TCM master or veteran practitioner. The diagnostic result is affected not only by the doctor's knowledge and experience, but also by the light, temperature and other environmental condition. Developing the new objective method to diagnose the lip color becomes urgent and important. This paper describes an automatic, low-cost method based on support vector machine and histogram for classifying lip color, independent of lighting and imaging device characteristics, using consumer digital cameras in a close chamber with stable light source. In HSI color space, the Hue, Saturation, Intensity channel were divided into different number of bins according to probability distribution of all pixels. Histogram of three channels are computed and combined together as feature vector for classifying lip color. A set of lip images with assigned color labels including five classes by TCM master practitioner was used to train multi-classes SVM classifier. The accuracy rate of classification on testing set is close to 85%. Experimental results show that the proposed method is effective and available for the lip color classification.
Fast Transient (FT) Technique With Adaptive Phase Margin (APM) for Current Mode DC-DC Buck Converters

This paper proposes a fast transient (FT) control with the adaptive phase margin (APM) to achieve good transient response in current-mode DC-DC buck converters at different load conditions. The overshoot/undershoot voltage and the transient recovery time are effectively reduced. The APM control can always maintain the system phase margin at an adequate value under different load conditions. That is, the compensation pole-zero pair is adapted to load current to extend the system bandwidth and get an adequate phase margin. Experimental results show the overshoot/undershoot voltage is smaller than 60 mV (3%) and transient period is smaller than 12 μs as load current suddenly changes from 100 to 500 mA, or vice versa. Compared with conventional designs without any fast transient technique, the undershoot voltage and recovery time are enhanced by 45% and 85%, respectively.
Neuroscience and Biobehavioral Reviews a Systems Level Analysis of the Mirror Neuron Hypothesis and Imitation Impairments in Autism Spectrum Disorders

Although several studies suggest an imitation deficit as a key feature of autism, questions have been raised about the consistency of this finding and about the component skills involved in imitation. The primary aim of this review is to examine the uneven profile of imitation deficits found in autism in the context of the mirror neuron system (MNS) dysfunction hypothesis. We use the cortical undercon-nectivity framework (Just et al., 2004) to examine the coordination of brain areas that orchestrate the communication between the component skills underlying imitation. A comprehensive account of imitation deficit in autism should take into account the regions that are at the core of the MNS (e.g., IFG and IPL) and related regions that feed into the MNS (e.g., STS, Cerebellum) in their functioning and in their coordination. Our findings suggest that the MNS may be associated with mediating familiarity, attention, self-other matching, and social relevance, which may be vital in characterizing the imitation deficits in autism. Such an analysis may have greater clinical and therapeutic value.
Privacy Preserving Reputation Systems

Reputation systems provide mechanisms for multiple parties, in a community, to quantify the trust between one another and to encourage adherence to contract in e-commerce. In this thesis we provide two protocols to calculate the reputation value of participant agents in peer to peer community, using a private, additive and fully decentralized manner. The first protocol considers the churn rate in the network, where peers enter and leave the network very often and the second protocol solves the problem of the leak of trustworthiness among peers. We also provide an analyzing framework to compare our algorithms to former ones in the domain of reputation systems. We refer that our proposals are resilient against the semi-trusted and curious peers attacks and they both have linear complexity.
Monolithically-Integrated Mulitlevel Inverter on Lateral GaN-on-Si Technology for High-Voltage Applications

This work reports on the development of a fully integrated monolithic single-phase diode-clamped multilevel (DCM) converter in a high-voltage AlGaN/GaN-on-Si technology for high-power conversion applications. The power chip operates as an inverter (DC/AC) to produce a three level output voltage from a DC link as well as a rectifier (AC/DC) to feed a DC link with a desired voltage. The application range, the topology, and the design of the inverter are presented in detail. The integrated inverter circuit is dimensioned for Umax = +/- 400 V and Imax = 5 A. Furthermore measurements of the performance of the single devices on the integrated chip are demonstrated.
Assessment and visualization of geographically distributed event-related sentiments by mining social networks and news

In this paper we present a method/tool for integrating heterogeneous data, assessing and visualizing sentiments related to big impact events in geographically confined populations. The data employed are official statistical information provided by governments, news web sites and user submitted georeferenced comments retrieved from various social networks. Sentiment analysis is applied to the retrieved comments and results are visualized on interactive maps, thus providing an effective tool for decision makers and analysts to evaluate how socioeconomic factors can influence the mood and the opinion of a specific area. The method is designed to assist city planners, business managers or social scientists for strategic planning and decision making. Furthermore, the experimental evaluation showed that the proposed method is robust, achieves state-of-the-art performance and allows an easy-exploration of big, distributed and heterogeneous information.
Number of unowned free-roaming cats in a college community in the southern United States and characteristics of community residents who feed them.

OBJECTIVE To estimate the number of unowned free-roaming cats in a college community in the southern United States and identify the characteristics of community residents who feed these cats. DESIGN Cross-sectional, random-digit telephone survey. SAMPLE POPULATION 587 households in Alachua County, Florida, surveyed between March 1 and May 10, 1999. PROCEDURE Telephone surveys were conducted, and respondents were asked questions about feeding of unowned free-roaming cats. RESULTS 70 (12%) households fed free-roaming cats; mean +/- SD number of free-roaming cats fed per household was 3.6 +/- 1.9. Households that fed free-roaming cats were more likely to own pet cats than were households that did not feed free-roaming cats; however, 30 of 70 (43%) households feeding free-roaming cats did not own cats or dogs. Although the percentage of pet cats that were neutered was high (90%), only 8 (11%) households that fed free-roaming cats attempted to have such cats neutered. The free-roaming cat population was estimated to represent approximately 44% of the population of cats in the county. CONCLUSIONS AND CLINICAL RELEVANCE Results suggest that unowned free-roaming cats may represent a substantial portion of the total cat population in a region. Public policies and education programs aimed at reducing cat overpopulation should include provisions for neutering unowned free-roaming cats, and efforts should target the general public, not only pet owners, because not all households that feed unowned free-roaming cats own pets.
Specificity of M and L Cone Inputs to Receptive Fields in the Parvocellular Pathway: Random Wiring with Functional Bias

Many of the parvocellular pathway (PC) cells in primates show red–green spectral selectivity (cone opponency), but PC ganglion cells in the retina show no anatomical signs of cone selectivity. Here we asked whether responses of PC cells are compatible with “random wiring” of cone inputs. We measured long-wavelength-sensitive (L) and medium-wavelength-sensitive (M) cone inputs to PC receptive fields in the dorsal lateral geniculate of marmosets, using discrete stimuli (apertures and annuli) to achieve functional segregation of center and surround. Receptive fields between the fovea and 30° eccentricity were measured. We show that, in opponent PC cells, the center is dominated by one (L or M) cone type, with normally <20% contribution from the other cone type (high “cone purity”), whereas non-opponent cells have mixed L and M cone inputs to the receptive field center. Furthermore, opponent response strength depends on the overall segregation of L and M cone inputs to center and surround rather than exclusive input from one cone type to either region. These data are consistent with random wiring. The majority of PC cells in both foveal (<8°) and peripheral retina nevertheless show opponent responses. This arises because cone purity in the receptive field surround is at least as high as in the center, and the surround in nearly all opponent PC cells is dominated by the opposite cone type to that which dominates the center. These functional biases increase the proportion of opponent PC cells, but their anatomical basis is unclear.
iTad: I/O Thermal Aware Data Center Model

With the ever-growing cooling costs of large-scale data centers, thermal management must be adequately addressed. Thermal models can play a critical role in thermal management that helps in reducing cooling costs in data centers. However, existing thermal models for data centers can overload I/O activities. To address this issue, we developed an I/O-aware thermal model called iTad for data centers. The iTad model captures the thermal characteristics of servers in a data center, offering a much finer granularity than the existing models. In addition to CPU workloads, iTad incorporates the I/O load in order to accurately estimate the thermal footprint of the servers with I/O-intensive activities. We validate the accuracy of the iTad model using real-world temperature measurements acquired by an infrared thermometer. Our empirical results show that I/O utilizations have a significant impact on internal temperatures of data servers. We show that thermal management mechanisms can quickly retrieve the thermal information of servers from iTad before making important workload placement decisions in a real-time manner.
On the dynamic technician routing and scheduling problem

The Technician Routing and Scheduling Problem (TRSP) deals with a limited crew of technicians that serves a set of requests. In the TRSP, each technician has a set of skills, tools, and spare parts, while requests require a subset of each. The problem is then to design a set of tours of minimal total duration such that each request is visited exactly once, within its time window, by a technician with the required skills, tools, and spare parts. The TRSP naturally arises in a wide range of applications, including telecoms, public utilities, and maintenance operations. To the best of our knowledge, no work considers neither tools, nor spare parts, nor the arrival of new requests, three important components of real-world applications. The present work addresses this aspect and proposes an optimization approach for the dynamic version of the problem, noted D-TRSP, where new requests arrive during the execution of the routes.
Meta-Analysis of Attitudes toward Damage-Causing Mammalian Wildlife

Many populations of threatened mammals persist outside formally protected areas, and their survival depends on the willingness of communities to coexist with them. An understanding of the attitudes, and specifically the tolerance, of individuals and communities and the factors that determine these is therefore fundamental to designing strategies to alleviate human‐wildlife conflict. We conducted a meta‐analysis to identify factors that affected attitudes toward 4 groups of terrestrial mammals. Elephants (65%) elicited the most positive attitudes, followed by primates (55%), ungulates (53%), and carnivores (44%). Urban residents presented the most positive attitudes (80%), followed by commercial farmers (51%) and communal farmers (26%). A tolerance to damage index showed that human tolerance of ungulates and primates was proportional to the probability of experiencing damage while elephants elicited tolerance levels higher than anticipated and carnivores elicited tolerance levels lower than anticipated. Contrary to conventional wisdom, experiencing damage was not always the dominant factor determining attitudes. Communal farmers had a lower probability of being positive toward carnivores irrespective of probability of experiencing damage, while commercial farmers and urban residents were more likely to be positive toward carnivores irrespective of damage. Urban residents were more likely to be positive toward ungulates, elephants, and primates when probability of damage was low, but not when it was high. Commercial and communal farmers had a higher probability of being positive toward ungulates, primates, and elephants irrespective of probability of experiencing damage. Taxonomic bias may therefore be important. Identifying the distinct factors explaining these attitudes and the specific contexts in which they operate, inclusive of the species causing damage, will be essential for prioritizing conservation investments.
Previento-A Wind Power Prediction System with an Innovative Upscaling Algorithm

Previento is an operational forecast system which provides a prediction of the expected power output for a time horizon up to 48 hours. It is based on an physical approach with input from a large scale weather prediction model like Lokalmodell of the German Weather Service. In this paper we focus on the forecast of power output of regional distributed wind farms. Due to spatial smoothing effects the fluctuations of the combined power output of distributed wind farms are damped, which results in decrease of fluctuations of the regional power output compared to the forecast for single sites. These effects are already covered with the forecast of a small numbers of turbines. Therefore a detailed forecast for each turbine is not necessary and a linear upscaling from a small number of turbines is possible. As an example we make a forecast for whole Germany and show how this method works practicaly and which data is needed.
Effects of Steel Mill Dust on the Strength Characteristics of Black Cotton Clay Soils

the results of laboratory investigations on the influence of steel mill dust on the strength characteristics of tropical black cotton clay soils are presented. Tropical Black Cotton clay soils were mixed with steel mill dust at 5%, 10%, 15%, 20%and 30% steel mill dust content (by dry weight of soil) in order to establish the soil stabilizing potentials. The Unconfined compressive strength and CBR tests on the soil-steel mill dust mixtures yielded peak values at 30% mill scale content. The soil-steel mill dust mixture can be used as subgrade and sub-base courses of rural roads when compacted at the energy of the West Africa Standard.