Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell density in prostate histopathology images as a measure of tumor distribution

We have developed an automatic technique to measure cell density in high resolution histopathology images of the prostate, allowing for quantification of differences between tumour and benign regions of tissue. Haemotoxylin and Eosin (H&E) stained histopathology slides from five patients were scanned at 20x magnification and annotated by an expert pathologist. Colour deconvolution and a radial symmetry transform were used to detect cell nuclei in the images, which were processed as a set of small tiles and combined to produce global maps of cell density. Kolmogorov-Smirnov tests showed a significant difference in cell density distribution between tumour and benign regions of tissue for all images analyzed (p < 0.05), suggesting that cell density may be a useful feature for segmenting tumour in un-annotated histopathology images. ROC curves quantified the potential utility of cell density measurements in terms of specificity and sensitivity and threshold values were investigated for their classification accuracy. Motivation for this work derives from a larger study in which we aim to correlate ground truth histopathology with in-vivo multiparametric MRI (mpMRI) to validate tumour location and tumour characteristics. Specifically, cell density maps will be registered with T2-weighted MRI and ADC maps from diffusion-weighted MRI. The validated mpMRI data will then be used to parameterise a radiobiological model for designing focal radiotherapy treatment plans for prostate cancer patients.
Super-resolution Reconstruction for Diffusion-weighted Images using High Order SVD

The spatial resolution of diffusion-weighted imaging (DWI) is limited because of the loss of highfrequency information such as edges during data acquisition process. In this paper, method based on the patch-based super-resolution framework is proposed for single image super-resolution reconstruction of DWI dataset and the high order SVD was introduced to achieve more accurate image reconstruction and reduce the computational complexity. Experimental results demonstrate that the proposed method outperformed currently methods in both DWI reconstruction and its further applications.
BlueScan: Boosting Wi-Fi Scanning Efficiency Using Bluetooth Radio

The increasing demand for ubiquitous wireless connectivity has led to the widespread of Wi-Fi networks. However, due to the limited coverage of Wi-Fi networks, mobile stations (STAs) need to frequently search for neighboring Wi-Fi access points (APs). Inevitable inefficiency occurs during the Wi-Fi scanning since the STA typically does not have any prior knowledge of the neighboring APs, thus leading to unnecessary waste of time and energy. In this paper, we propose BlueScan, a scheme to boost Wi-Fi scanning using collocated Bluetooth radio. BlueScan enhances Wi-Fi scanning with low power Bluetooth radio by identifying the operating channels and target beacon transmission times (TBTTs) of neighboring APs, thus changing the Wi-Fi scanning from a blind search to an intelligent search. We implement a prototype of BlueScan using Ubertooth platform, and evaluate its performance through real experiments. Our results demonstrate that BlueScan reduces the scanning delay up to 77% compared to legacy Wi-Fi scanning.
Classifying Sluice Occurrences in Dialogue

Ellipsis is an important challenge for natural language processing systems, and addressing that challenge requires large collections of relevant data. The dataset described by Anand and McCloskey (2015), consisting of 4100 occurrences, is an important step towards addressing this issue. However, many NLP technologies require much larger collections of data. Furthermore, previous collections of ellipsis are primarily restricted to news data, although sluicing presents a particularly important challenge for dialogue systems. In this paper we classify sluices as Direct, Reprise, Clariﬁcation. We perform manual annotation with acceptable inter-coder agreement. We build classiﬁer models with Decision Trees and Naive Bayes, with accuracy of 67%. We deploy a classiﬁer to automatically classify sluice occurrences in OpenSubtitles, resulting in a corpus with 1.7 million occurrences. This will support empirical research into sluicing in dialogue, and it will also make it possible to build NLP systems using very large datasets. This is a noisy dataset; based on a small manually annotated sample, we found that only 80% of instances are in fact sluices, and the accuracy of sluice classiﬁcation is lower. Despite this, the corpus can be of great use in research on sluicing and development of systems, and we are making the corpus freely available on request. Furthermore, we are in the process of improving the accuracy of sluice identiﬁcation and annotation for the purpose of created a subsequent version of this corpus.
Neural Models of Selectional Preferences for Implicit Semantic Role Labeling

Implicit Semantic Role Labeling is a challenging task: it requires high-level understanding of the text while annotated data is very limited. Due to the lack of training data, most researches either resort to simplistic machine learning methods or focus on automatically acquiring training data. In this paper, we explore the possibilities of using more complex and expressive machine learning models trained on a large amount of explicit roles. In addition, we compare the impact of one-way and multi-way selectional preference with the hypothesis that the added information in multi-way models are beneficial. Although our models surpass a baseline that uses prototypical vectors for SemEval-2010, we otherwise face mostly negative results. Selectional preference models perform lower than the baseline on ON5V, a dataset of five ambiguous and frequent verbs. They are also outperformed by the Naive Bayes model of Feizabadi and Pado (2015) on both datasets. We conclude that, even though multi-way selectional preference improves results for predicting explicit semantic roles compared to one-way selectional preference, it harms performance for implicit roles. We release our source code, including the reimplementation of two previously unavailable systems to enable further experimentation.
TRESK background potassium channel is not gated at the helix bundle crossing near the cytoplasmic end of the pore

Two-pore domain K+ channels (K2P) are responsible for background K+ currents and regulate the resting membrane potential and cellular excitability. Their activity is controlled by a large variety of physicochemical factors and intracellular signaling pathways. The majority of these effects converge on the intracellular C-terminus of the channels, resulting in the modification of the gating at the selectivity filter. Another gating mechanism, the activation gate at the helix bundle crossing is also well documented in other K+ channel families, however, it remains uncertain whether this type of gating is functional in K2P channels. The regulation of TWIK-related spinal cord K+ channel (TRESK) is different from the other K2P channels. Regulatory factors acting via the C-terminus are not known, instead channel activity is modified by the phosphorylation/dephosphorylation of the unusually long intracellular loop between the 2nd and 3rd transmembrane segments. These unique structural elements of the regulation lead us to examine channel gating at the bundle crossing region. Ba2+ was applied to the intracellular side of excised membrane patches and the characteristics of the channel block were determined. We compared the kinetics of the development of Ba2+ block when the channels were phosphorylated (inhibited) or dephosphorylated (activated) and also in different mutants mimicking the two functional states. Neither the phosphorylation/dephosphorylation nor the point mutations influenced the development of Ba2+ block, suggesting that the conformational changes of the bundle crossing region do not contribute to the phosphorylation-dependent gating of TRESK.
Nonrigid registration using a rigidity constraint

Nonrigid registration is a technique commonly used in the field of medical imaging. A drawback of most current nonrigid registration algorithms is that they model all tissue as being nonrigid. When a nonrigid registration is performed, the rigid objects in the image, such as bony structures or surgical instruments, may also transform nonrigidly. Other consequences are that tumour growth between follow-up images may be concealed, or that structures containing contrast material in one image and not in the other may be compressed by the registration algorithm. In this paper we propose a novel regularisation term, which is added to the cost function in order to penalise nonrigid deformations of rigid objects. This regularisation term can be used for any representation of the deformation field capable of modelling locally rigid deformations. By using a B-spline representation of the deformation field, a fast algorithm can be devised. We show on 2D synthetic data, on clinical CT slices, and on clinical DSA images, that the proposed rigidity constraint is successful, thus improving registration results.
Preserving Workflow Reproducibility: The RePlay-DH Client as a Tool for Process Documentation

In this paper we present a software tool for elicitation and management of process metadata. It follows our previously published design idea of an assistant for researchers that aims at minimizing the additional effort required for producing a sustainable workﬂow documentation. With the ever-growing number of linguistic resources available, it also becomes increasingly important to provide proper documentation to make them comparable and to allow meaningful evaluations for speciﬁc use cases. The often prevailing practice of post hoc documentation of resource generation or research processes bears the risk of information loss. Not only does detailed documentation of a process aid in achieving reproducibility, it also increases usefulness of the documented work for others as a cornerstone of good scientiﬁc practice. Time pressure together with the lack of simple documentation methods leads to workﬂow documentation in practice being an arduous and often neglected task. Our tool ensures a clean documentation for common workﬂows in natural language processing and digital humanities. Additionally, it can easily be integrated into existing institutional infrastructures.
An Efficient Compression of Strongly Encrypted Images using Error Prediction, AES and Run Length Coding

: We implement an efficient compression of strongly encrypted images using error prediction, AES encryption and Run Length Encoding. In normal cases image encryption has to be done before the image compression. In such cases will leads to a problem of how to design a couple of algorithm for image encryption and compression while preserving the quality and security of the image. In order to provide most priority to the security of the image in the Encryption-then-Compression (ETC) system, we implement an efficient error prediction mechanism before the strong encryption schema. Block cipher mode of encryption is used to enhance the security of the image. We also demonstrate run length coding based compression scenario to improve the efficiency of image compression. While testing, we are able to compress an encrypted 640000 bit image to 278656 bits and the results shown that the proposed system is more promising and convenient.
Financial development and the share of imported capital goods in developing countries: firm-level evidence

ABSTRACT Firm-level estimations across a sample of seven developing countries suggest that a higher firm’s leverage – a proxy for credit constraints – reduces the share of imported capital goods in total capital expenditures. This result holds across different models such as a two-limit tobit and a fractional logit model. It is also confirmed after controlling for unobserved firm heterogeneity, state dependence or when using the share of property in total assets as an alternative credit constraint indicator. The results also indicate that the importance of credit constraints is significantly reduced in financially more developed countries.
Integral bHLH factor regulation of cell cycle exit and RGC differentiation

Background: In the developing mouse embryo, the bHLH transcription factor Neurog2 is transiently expressed by retinal progenitor cells and required for the initial wave of neurogenesis. Remarkably, another bHLH factor, Ascl1, normally not present in the embryonic Neurog2 retinal lineage, can rescue the temporal phenotypes of Neurog2 mutants. Results: Here we show that Neurog2 simultaneously promotes terminal cell cycle exit and retinal ganglion cell differentiation, using mitotic window labeling and integrating these results with retinal marker quantifications. We also analyzed the transcriptomes of E12.5 GFP‐expressing cells from Neurog2GFP/+, Neurog2GFP/GFP, and Neurog2Ascl1KI/GFP eyes, and validated the most significantly affected genes using qPCR assays. Conclusions: Our data support the hypothesis that Neurog2 acts at the top of a retinal bHLH transcription factor hierarchy. The combined expression levels of these downstream factors are sufficiently induced by ectopic Ascl1 to restore RGC genesis, highlighting the robustness of this gene network during retinal ganglion cell neurogenesis. Developmental Dynamics 247:965‐975, 2018. © 2018 Wiley Periodicals, Inc.
Imaging of cosmetic plastic procedures and implants in the body and their potential complications.

OBJECTIVE Cosmetic plastic surgery procedures, as well as implants, are increasingly being performed. These implants are often encountered on routine imaging examinations, and radiologists are often asked to evaluate for complications or evidence of failure. Pectoral augmentation, gluteal augmentation, body lift and abdominoplasty, and penile and testicular prostheses are reviewed in this article. CONCLUSION The typical appearance of common cosmetic implants and cosmetic techniques used in the human body is presented, along with the imaging spectrum of their potential complications.
An Adaptive Environmental Effects Monitoring Framework for Assessing the Influences of Liquid Effluents on Benthos, Water, and Sediments in Aquatic Receiving Environments

Environmental effects monitoring (EEM) has been traditionally used to evaluate the effects of existing facilities discharging liquid effluents into natural receiving waters in Canada. EEM also has the potential to provide feedback to an ongoing project in an adaptive management context and can inform the design of future projects. EEM, consequently, can and should also be used to test the predictions of effects related to new projects. Despite EEM's potential for widespread applicability, challenges related to the effective implementation of EEM include the use of appropriate study designs and the adoption of tiers for increasing or decreasing monitoring intensity. Herein we describe a template for designing and implementing a 6‐tiered EEM program that utilizes information from the project‐planning and predevelopment baseline data collection stages to build on forecasts from the initial environmental impact assessment project‐design stage and that feeds into an adaptive management process. Movement between the 6 EEM tiers is based on the exceedance of baseline monitoring triggers, forecast triggers, and management triggers at various stages in the EEM process. To distinguish these types of triggers, we review the historical development of numeric and narrative triggers as applied to chemical (water and sediment) and biological (plankton, benthos, fish) endpoints. We also provide an overview of historical study design issues and discuss how the 6 EEM tiers and associated triggers influence the temporal‐spatial experimental design options and how the information gained through EEM could be used in an adaptive management context. Integr Environ Assess Manag 2018;14:552–566. © 2018 SETAC
What Drives Local Wine Expenditure in Kentucky, Ohio, Tennessee and Pennsylvania? A Consumer Behavior and Wine Market Segmentation Analysis

This study explores wine expenditure driven factors for consumers in the United States by employing a four-state consumer behaviors study. A market segmentation method is applied to investigate spending patterns of wine consumers in Pennsylvania, Ohio, Kentucky, and Tennessee. Determinants including market segmentation measurements, lifestyle factors and demographic variables are investigated and compared for their significance in driving local wine expenditure, local wine purchase probability, and local wine to total wine expenditure ratio. This study also recommends market strategic insights for wine business stakeholders.
Mindfulness-Based Hypnotherapy

This special issue was a project initiated by Dr. Assen Alladin, whose unexpected death on November 14, 2017, occurred prior to its completion. His death, however, was not to impede his desire, as its production was continued. I have been honored to assist with Assen’s legacy and to guest edit under the tutelage of Stephen Lankton. In what follows we see an example of Dr. Alladin’s interest in promoting hypnosis as an assimilative practice (Alladin & Amundson, 2011). By this we mean a metaphorical “big tent” under which many empirical, theoretical, and traditional wisdom sources can be aggregated. With this in mind, mindfulness has been invited to the coterie. Mindfulness initially entered into its relationship with hypnosis as a form of mental reserve—that is, detachment or functional dissociation (Cramer, 2000). The distinction, however, between detachment in hypnosis versus mindfulness is an important one. This distinction is addressed in this issue in “The Association Between Mindfulness and Hypnotizability: Clinical and Theoretical Implications” by Grover, Jensen, Patterson, Getz, and Day. In their article, the authors remind us that while increased, moment-tomoment awareness may constitute one form of detachment (i.e., positive dissociation), hypnosis is another and distinct form of detachment. In this distinction, they raise the discussion from Buddhism regarding “single mind,” associated with the Mahayana tradition, and “wandering mind” of the Theravada practices; the former is more akin to hypnosis, while the latter is more akin to mindfulness. Digging deeper into the esoteric aspects of mindfulness, Amundson, Ross, and Campbell present “HeyWait! I Just Thought of Something Else! Advaita and Clinical Hypnosis. ”This article focuses upon how the practices of Vipassana, Satipatthana, Zen, Ch’an, and related mindfulness traditions find their roots in early Hindu philosophy. While underlying
A High Conversion Gain Wideband Mixer Design for UWB Applications

A CMOS mixer with wideband input impedance matching and high conversion gain is presented in this paper. Dual RLC circuits are utilized with Gilbert mixer for wideband input matching. Capacitive feedback, and inductive series and shunt peaking techniques, are used to implement the RF port matching network. Inductive peaking is also adopted to widen the 3-dB conversion gain bandwidth. Active load with AC resistive blocking is employed to boost the mixer conversion gain. The proposed circuit is designed, simulated and implemented in XFAB XH018 process with VDD of 1.8V. It achieves a very good RF matching over a band of 5.6–14.6GHz, with a conversion gain of 25.0–28.2dB over the desired band of frequency.
Improved Transcription and Indexing of Oral History Interviews for Digital Humanities Research

This paper describes different approaches to improve the transcription and indexing quality of the Fraunhofer IAIS Audio Mining system on Oral History interviews for the Digital Humanities Research. As an essential component of the Audio Mining system, automatic speech recognition faces a lot of difﬁcult challenges when processing Oral History interviews. We aim to overcome these challenges using state-of-the-art automatic speech recognition technology. Different acoustic modeling techniques, like multi-condition training and sophisticated neural networks, are applied to train robust acoustic models. To evaluate the performance of these models on Oral History interviews a German Oral History test-set is presented. This test-set represents the large audio-visual archives “Deutsches Ged¨achtnis” of the Institute for History and Biography. The combination of the different applied techniques results in a word error rate reduced by 28 . 3% relative on this test-set compared to the current baseline system while only one eighth of the previous amount of training data is used. In context of these experiments new opportunities are set out for Oral History research offered by Audio Mining. Also the workﬂow is described used by Audio Mining to process long audio-ﬁles to automatically create time-aligned transcriptions.
Parameter Estimation in Gamma Mixture Model using Normal-based Approximation

Gamma mixture models have wide applications in hydrology, finance and reliability. Parameter estimation in this class of models is a challenging task owing to the complexity associated with the model structure. In this paper, a novel approach is proposed to estimate the parameters of Gamma mixture models using Wilson-Hilferty normalbased approximation method. The proposed methodology uses a popular clustering algorithm for Gaussian mixtures namely, MCLUST and a confidence interval based search approach to obtain the estimates. The methodology is implemented on simulated as well as real-life datasets and its performance is compared with gammamixEM() function available in R.
VARIATIONS IN INFRARED SPECTRA, MOLECULAR SYMMETRY AND SITE SYMMETRY OF SULFATE MINERALS

The interaction of the functional molecular group, soaF, in sulfate minerals r,vith its tion of the symmetry of the sulfate ion from la to various lower symmetries. The spectral data for alunite and jarosite show more vibrational components for v1 than permitted by the site symmetry of the sulfate ion, thus indicating the presence of non-equivalent ions. hgtnooucrror.r rn recent years there has been increasing interest in infrared application to mineral analysis. As a result the need for more informatlon on factors afiecting variation of characteristic molecular group frequencies has become evident, for without this knowledge there is l i tt le poisibil i ty of deriving unambiguous information of structural significance from complex mineral spectra. certain general principles that govern the correlation of the vibrational spectra of molecular ions with their structural features are implicit in every application of absorption spectroscopy. First, each vibrational frequencv is associated with a different motion of the vibrating nuclei; second, each specific configuration of the nuclei forming the molecule will produce a characteristic vibrational spectrum; third, the vibrational spectrum is dependent both on the masses of the nuclei and the internal forces that maintain the equilibrium configuration of the molecule; and, fourth, the functional molecules mav exist in crystals in differing environments which more or less alter the equilibrium parameters of the molecule. From what has already been done, it is apparent that the interaction of functional molecular groups with their surrounding ions is an important aspect of molecular absorption spectroscopl, of minerals. Recent spectral investigations (Adler and Kerr, 1963a,b) emphasizing the dependence of functional molecular groups on intermolecular environment have shown that the spectroscopic distinction between minerals in both the calcite and aragonite groups has as its basis the modification of