Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of breast pathologies using nonlinear microscopy

Significance Development of methods for rapid intraoperative assessment of breast pathologies is important for decreasing the rate of surgical reexcisions during breast-conserving therapy. Frozen-section analysis is the most widely used method for intraoperative margin assessment but is time consuming, has limited diagnostic accuracy, and produces freezing artifacts. This manuscript demonstrates nonlinear microscopy for rapid assessment of surgical breast specimens without need for fixation, embedding, and sectioning required for conventional histology. Blinded reading of nonlinear microscopy images by three pathologists achieved 95.4% sensitivity, 93.3% specificity, and 94.1% overall accuracy compared with histology for identifying invasive cancer and ductal carcinoma in situ versus benign breast tissue. The results suggest that nonlinear microscopy is a promising method for intraoperative assessment of breast surgical excision specimens. Rapid intraoperative assessment of breast excision specimens is clinically important because up to 40% of patients undergoing breast-conserving cancer surgery require reexcision for positive or close margins. We demonstrate nonlinear microscopy (NLM) for the assessment of benign and malignant breast pathologies in fresh surgical specimens. A total of 179 specimens from 50 patients was imaged with NLM using rapid extrinsic nuclear staining with acridine orange and intrinsic second harmonic contrast generation from collagen. Imaging was performed on fresh, intact specimens without the need for fixation, embedding, and sectioning required for conventional histopathology. A visualization method to aid pathological interpretation is presented that maps NLM contrast from two-photon fluorescence and second harmonic signals to features closely resembling histopathology using hematoxylin and eosin staining. Mosaicking is used to overcome trade-offs between resolution and field of view, enabling imaging of subcellular features over square-centimeter specimens. After NLM examination, specimens were processed for standard paraffin-embedded histology using a protocol that coregistered histological sections to NLM images for paired assessment. Blinded NLM reading by three pathologists achieved 95.4% sensitivity and 93.3% specificity, compared with paraffin-embedded histology, for identifying invasive cancer and ductal carcinoma in situ versus benign breast tissue. Interobserver agreement was κ = 0.88 for NLM and κ = 0.89 for histology. These results show that NLM achieves high diagnostic accuracy, can be rapidly performed on unfixed specimens, and is a promising method for intraoperative margin assessment.
The effect of human image in B2C website design: an eye-tracking study

On B2C shopping websites, effective visual designs can bring about consumers’ positive emotional experience. From this perspective, this article developed a research model to explore the impact of human image as a visual element on consumers’ online shopping emotions and subsequent attitudes towards websites. This study conducted an eye-tracking experiment to collect both eye movement data and questionnaire data to test the research model. Questionnaire data analysis showed that product pictures combined with human image induced positive emotions among participants, thus promoting their attitudes towards online shopping websites. Specifically, product pictures with human image first produced higher levels of image appeal and perceived social presence, thus stimulating higher levels of enjoyment and subsequent positive attitudes towards the websites. Moreover, a moderating effect of product type was demonstrated on the relationship between the presence of human image and the level of image appeal. Specifically, human image significantly increased the level of image appeal when integrated in entertainment product pictures while this relationship was not significant in terms of utilitarian products. Eye-tracking data analysis further supported these results and provided plausible explanations. The presence of human image significantly increased the pupil size of participants regardless of product types. For entertainment products, participants paid more attention to product pictures integrated with human image whereas for utilitarian products more attention was paid to functional information of products than to product pictures no matter whether or not integrated with human image.
Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes: A systematic review and meta-analysis and analysis of two pregnancy cohorts

Background Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. Methods We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. Results Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. Conclusions Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608
PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database

Abstract The PharmMapper online tool is a web server for potential drug target identification by reversed pharmacophore matching the query compound against an in-house pharmacophore model database. The original version of PharmMapper includes more than 7000 target pharmacophores derived from complex crystal structures with corresponding protein target annotations. In this article, we present a new version of the PharmMapper web server, of which the backend pharmacophore database is six times larger than the earlier one, with a total of 23 236 proteins covering 16 159 druggable pharmacophore models and 51 431 ligandable pharmacophore models. The expanded target data cover 450 indications and 4800 molecular functions compared to 110 indications and 349 molecular functions in our last update. In addition, the new web server is united with the statistically meaningful ranking of the identified drug targets, which is achieved through the use of standard scores. It also features an improved user interface. The proposed web server is freely available at http://lilab.ecust. edu.cn/pharmmapper/.
End-to-end performance evaluation in high-speed wireless networks

When dealing with lossy networks, performance management through conventional Quality of Service (QoS) based methods becomes difficult and is often ineffective. We find, in fact, that in this case quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service. To better explore the value of assessing Quality of Experience (QoE) alongside QoS in high-speed, lossy networks, this paper investigates the case of video streaming services in Radio-over-Fiber (RoF) networks, a prominent example in which network performance is critically related to the application. By means of a pilot RoF test-environment, we study the sensitivity of QoE to the most critical network parameters for different test case scenarios. The outcome is a QoE-based method to assess networks performance, which allows to underpin the network criticalities and non-linear relationships between service and network planes.
RMIT at the TREC 2016 LiveQA Track

—This paper describes the four systems RMIT ﬁelded for the TREC 2016 LiveQA task and the associated experiments. Similar to last year, the results show that simple solutions tend to work best, and that our improved baseline systems achieved an above-average performance. We use a commercial search engine as a ﬁrst stage retrieval mechanism and compare it with our internal system which uses a carefully curated document collection. Somewhat surprisingly, we found that on average the small curated collection performed better within our current framework, warranting further studies on when and when not to use an external resource, such as a publicly available search engine API. Finally, we show that small improvements to performance can substantially reduce failure rates.
Cache-optimal algorithms for option pricing

Today computers have several levels of memory hierarchy. To obtain good performance on these processors it is necessary to design algorithms that minimize I/O traffic to slower memories in the hierarchy. In this article, we study the computation of option pricing using the binomial and trinomial models on processors with a multilevel memory hierarchy. We derive lower bounds on memory traffic between different levels of the hierarchy for these two models. We also develop algorithms for the binomial and trinomial models that have near-optimal memory traffic between levels. We have implemented these algorithms on an UltraSparc IIIi processor with a 4-level of memory hierarchy and demonstrated that our algorithms outperform algorithms without cache blocking by a factor of up to 5 and operate at 70% of peak performance.
Southern Ocean Intrinsic and Forced Modes of Low Frequency

A coupled Ocean-Sea ice General Circulation Model (OGCM) is used to identify a Southern Ocean southeast Pacific intrinsic mode of low frequency variability. This mode is co-located with a major region of Sub-Antarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) formation. Using CORE data a comprehensive suite of experiments were carried out to elucidate excitation and amplification mechanisms of this intrinsic mode by low frequency forcing (ENSO, SAM) and stochastic forcing due to high frequency winds. Subsurface thermocline anomalies were found to teleconnect the Pacific and Atlantic regions of the Antarctic Circumpolar Current (ACC). The Pacific region of the ACC is characterised by intrinsic baroclinic disturbances that respond to both SAM and ENSO, while the Atlantic sector of the ACC is sensitive to higher frequency winds that act to amplify thermocline anomalies propagating downstream from the Pacific resonant with eastward travelling Rossby waves. This simulation study identifies plausible mechanisms that determine the predictability of the Southern Ocean climate on multi-decadal timescales.
Distributed Energy Spectral Efficiency Optimization for Partial/Full Interference Alignment in Multi-user Multi-relay Multi-cell MIMO Systems

The energy spectral efficiency maximization (ESEM) problem of a multi-user, multi-relay, multi-cell system is considered, where all the network nodes are equipped with multi-antenna transceivers. To deal with the potentially excessive interference originating from a plethora of geographically distributed transmission sources, a pair of transmission protocols based on interference alignment (IA) are conceived. The first, termed the full-IA, avoids all intra-cell interference (ICI) and other-cell interference by finding the perfect interference-nulling receive beamforming matrices (RxBFMs). The second protocol, termed partial-IA, only attempts to null the ICI. Employing the RxBFMs computed by either of these protocols mathematically decomposes the channel into a multiplicity of non-interfering multiple-input-single-output channels, which we term as spatial multiplexing components (SMCs). The problem of finding the optimal SMCs as well as their power control variables for the ESEM problem considered is formally defined and converted into a convex optimization form with carefully selected variable relaxations and transformations. Thus, the optimal SMCs and power control variables can be distributively computed using both the classic dual decomposition and subgradient methods. Our results indicate that indeed, the ESEM algorithm performs better than the baseline equal power allocation algorithm in terms of its ESE. Furthermore, surprisingly the partial-IA outperforms the full-IA in all cases considered, which is because the partial-IA is less restrictive in terms of the number of available transmit dimensions at the transmitters. Given the typical cell sizes considered in this paper, the path-loss sufficiently attenuates the majority of the interference, and thus the full-IA over-compensates, when trying to avoid all possible sources of interference.
The ModelTalker System

The ModelTalker TTS system has recently been largely rewritten to change its design to make full use of information derived from talker-specific HMMs that are trained in optimizing phonetic transcription and alignment. Because this system is substantially different than the system last used in a Blizzard challenge in 2005, we decided to participate once again. This allows us to both compare performance with the previous version on similar tasks, and with the latest cutting edge TTS technology. The current version of ModelTalker appears to be comparable with the previous version in segmental intelligibility and substantially improved in the naturalness of its synthetic output.
Contourlet Transform for Iris Image Segmentation

The aim of this paper is improving the iris segmentation with the Contourlet transform. At first iris segmentation performed by canny edge detector and Hough Transform. By this approach some images don’t segmented properly, so we want to find a way to correct the image segmentation failures. Before applying edge detector, Contourlet transform applied for image denoising. By this approach, %100 accuracy rate in iris image segmentation is obtained. Denoised image with Contourlet transform a little blurred. After image denoised and image segmented, for keep basic quality of the image, corresponded basic image and the segmented image. So, segmentation will be right on the main image.
Engineered Biofiltration for Enhanced Hydraulic and Water Treatment Performance

Currently, biofiltration is largely operated as a passive process in the water treatment industry. Particle/turbidity removal and headloss drive the design and operation of conventional filtration as well as biofiltration. Thus, biofilter design parameters are typically limited to media configuration, backwash strategy, and loading rate. The biological removal of dissolved organic and inorganic contaminants is an anticipated benefit of biofiltration. However, common design and operational practice does not seek to enhance the biological activity responsible for those mechanisms. Indeed, in an effort to improve filter productivity and minimize headloss, many utilities employ chlorinated backwashes and other biomass control strategies. However, these are often to the detriment of biological activity and may be ineffective at removing a primary foulant of biofilters ? extracellular polymeric substances (EPS).
A cGMP-gated channel subunit in Limulus photoreceptors

The phototransduction cascade in invertebrate photoreceptors has not been fully elucidated. It has been proposed that in Limulus ventral photoreceptor cGMP is the intracellular second messenger that directly controls the gating of the light-dependent channels (Johnson et al., 1986; Bacigalupo et al., 1991). Recently, a putative cGMP-gated channel cDNA, Lcng1, has been cloned from Limulus and shown to be expressed in the brain and the ventral eye (Chen et al., 1999). In this study, we sought to more specifically localize the LCNG1 transcript and protein. In situ hybridization was used to determine whether the gene is expressed in glia or photoreceptor cells in the ventral eye. The results clearly demonstrated that Lcng1 mRNA is transcribed in the ventral photoreceptors. On Western blots probed with a polyclonal antibody raised against the C-terminus of LCNG1, a 100-kDa band and an 80-kDa band was labeled in the membrane protein preparations from brain and ventral eye, respectively. The labeling of these bands was blocked by preabsorption of the antibody with the antigen, indicating the labeling specificity. Immunocytochemistry and confocal microscopy were applied to investigate the subcellular localization of this antigen. Immunolabeling was highly localized in the transducing lobes of ventral eye photoreceptors and lateral eye photoreceptors. In both cases, the labeling was associated with membrane regions specialized for phototransduction, but the exact pattern appeared to be somewhat different in the two eyes. Preabsorption of the antiserum with antigen abolished the labeling, confirming specificity. The results lend support to the hypothesis that a cGMP-gated channel is directly involved in the phototransduction process.
Context – Aware Multi – Modal Notification for Wearable Computing

We propose to use context information obtained from body–worn sensors to mediate notifications for a wearable computer. In particular we introduce a model which uses two axes, namely personal and social interruptability of the user in order to decide both whether or not to notify the user and to decide which notification modality to use. Rather than to model and recognize the complete context of the user we argue that personal and social interruptability can be derived directly from various sensors by the combination of tendencies. First experimental results show the feasability of the approach using acceleration, audio, and location sensors. The investigation of user interface issues are the immediate next steps in our work. 1 Background of the Author Nicky Kern is a PhD student since October 2001 in the Perceptual Computing and Computer Vision Group (PCCV) at ETH Zurich. His work is supervised by Prof. Bernt Schiele. His research focuses on using non–trivial context information obtained from body–worn sensors for context– aware applications (see [2]). In his current work he tries to use context information to mediate notifications from various sources to the user of the wearable computer.
A Comparison of Machine Learning Methods for the Diagnosis of Pigmented Skin Lesions

We analyze the discriminatory power of k-nearest neighbors, logistic regression, artificial neural networks (ANNs), decision tress, and support vector machines (SVMs) on the task of classifying pigmented skin lesions as common nevi, dysplastic nevi, or melanoma. Three different classification tasks were used as benchmarks: the dichotomous problem of distinguishing common nevi from dysplastic nevi and melanoma, the dichotomous problem of distinguishing melanoma from common and dysplastic nevi, and the trichotomous problem of correctly distinguishing all three classes. Using ROC analysis to measure the discriminatory power of the methods shows that excellent results for specific classification problems in the domain of pigmented skin lesions can be achieved with machine-learning methods. On both dichotomous and trichotomous tasks, logistic regression, ANNs, and SVMs performed on about the same level, with k-nearest neighbors and decision trees performing worse.
Electrical characteristics and photocurrent spectral response of Si nanowires p-i-n junctions

P-i-n junctions were fabricated along silicon nanowires (SiNWs) via the conventional top-down approach using optical lithography. The process is fully CMOS compactable. Each device comprises 500 identical SiNWs connected in parallel, and each SiNW has a length of 1.0 μm and a triangular cross-section with dimensions of ∼6 nm (base) by ∼8 nm (height). Good rectifying electrical characteristics with a low reverse bias current of ∼0.2 fA per SiNW is observed. The photocurrent spectral response of the SiNW p-i-n photodiodes exhibits three peaks between 400 nm to 700 nm, which arise due to local optical field enhancement associated with diffraction by the periodic SiNW array and interference in an air/SiO2/Si cavity.
Spatial Temporal Analysis of Urban Heat Hazard on Education Area (University of Indonesia)

As education area, campus or university is full with various activities which have an impact on the existence of land-use or land-cover. The variation of activities dynamically change the shape of land-use or land-cover within the campus area, thus also create variations in Land Surface Temperature (LST). The LST are impacting the coziness of human activity especially when reaches more than 30 o C. This study used the term Urban Heat Signature (UHS) to explain LST in different land-use or land-cover types. The objective of this study is to examine UHS as an Urban Heat Hazard (UHH) based on Universal Temperature Climate Index (UTCI) and Effective Temperature Index (ETI) in University of Indonesia. Thermal bands of Landsat 8 images (the acquisition year 2013-2015) were used to create LST model. A ground data known as Air Surface Temperature (AST) were used to validate the model. The result showed an increased level of maximum temperature during September-October since 2013 until 2014. The maximum temperature was reduced in October 2014, however it increased again in August 2015. The UTCI showed “moderate” and “strong heat stress”, while EFI showed “uncomfortable” and “very uncomfortable” categories during that period. This research concluded that build up area in UI Campus highest temperature on UI campus based on UHS. Range UHS in Campus UI on 2013 (21.8-31.1 o C), 2014 (25.0-36.2 o C) and 2015 (24.9-38.2 o C). This maximum UHS on September (2014 and 2015) put on levelling UTCI included range temperature 32-35 o C, with an explanation of sensation temperature is warm and sensation of comfort is Uncomfortable, Psychology with Increasing Stress Case by Sweating and Blood Flow and Health category is Cardiovascular Embarrassment. This UHS occurs in September will give impact on psychology and health, that’s become the UHH of the living on education area.