Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapist–Client Interactions in Motivational Interviewing: The Effect of Therapists’ Utterances on Client Change Talk

Aims Motivational Interviewing is an effective treatment for a range of problematic behaviours, however, previous studies have revealed substantial variability in the effectiveness of therapists. Curiously, the specific behaviours which contribute to positive outcomes have rarely been studied. The aim of this study was to investigate hypothesised relationships between therapists' utterances and clients' change talk by analysing interactions sampled from the United Kingdom Alcohol Treatment Trial (UKATT). Methods This study comprised secondary analysis of process data and recordings selectively sampled from the UKATT database using sequential analyses of utterance categories, defined using the Motivational Interviewing Sequential Code for Observing Process Exchanges (MI-SCOPE). MI-SCOPE categories were modified on the basis of the existing literature. Observed and expected frequencies of change talk, transitional probabilities and their significance levels both immediately following therapists' statements (Lag 1), and after a delay (Lag 2) were calculated using the Generalised Sequential Querier (GSEQ) programme. Regression analyses were conducted using SPSS 21.0. Results In successful alcohol treatment sessions, therapists' open questions and complex reflections were significantly positively associated with client preparatory talk at Lag 1. Therapists' complex reflections were significantly positively associated with and predictive of strong client commitment talk at Lag 2. Conclusions The findings extend those of previous studies, suggesting that open questions and complex reflections play a central role in preparing clients for, and facilitating strong commitment to, behaviour change.
Manifold Optimization Approach for Data Detection in Massive Multiuser MIMO Systems

When the number of base station (BS) antennas is considerably larger than the number of user terminals (UTs), a simple linear minimum mean-square-error (LMMSE) data detection algorithm is near-optimal for uplink massive multiuser multiple-input and multiple-output (MIMO) systems. However, the LMMSE detector suffers significant performance loss when the number of UTs is comparable to the number of BS antennas. To alleviate the performance loss caused by the decrease in the BS-antenna-to-UT ratio, known data detection algorithm, namely “TASER,” can yield bit error rate (BER) performance close to that of the optimal detector in symmetric massive multiuser MIMO systems, where the BS-antenna-to-UT ratio is one. However, this TASER algorithm can only handle binary and quadratic phase-shift keying (PSK) modulations. Moreover, the computational complexity of the TASER algorithm is still remarkably high. Thus, a novel data detection algorithm is proposed in this study to reduce the computational complexity of the detection algorithm while achieving acceptable BER performance. The proposed algorithm is developed from the retraction-based Riemannian manifold optimization (RMO) framework for symmetric massive multiuser MIMO systems. Unlike the TASER-based detector, the proposed RMO-based detector can be applied for general $M$-ary PSK modulations. Simulation results show that the proposed detector significantly outperforms the LMMSE detector in terms of BER performance. In addition, the required complexity of RMO is substantially lower than that of TASER. These findings indicate that the proposed RMO-based detector exhibits a highly desirable tradeoff between BER performance and complexity.
Quantitative Analysis of Lipid Droplet Fusion: Inefficient Steady State Fusion but Rapid Stimulation by Chemical Fusogens

Lipid droplets (LDs) are dynamic cytoplasmic organelles containing neutral lipids and bounded by a phospholipid monolayer. Previous studies have suggested that LDs can undergo constitutive homotypic fusion, a process linked to the inhibitory effects of fatty acids on glucose transporter trafficking. Using strict quantitative criteria for LD fusion together with refined light microscopic methods and real-time analysis, we now show that LDs in diverse cell types show low constitutive fusogenic activity under normal growth conditions. To investigate the possible modulation of LD fusion, we screened for agents that can trigger fusion. A number of pharmacological agents caused homotypic fusion of lipid droplets in a variety of cell types. This provided a novel cell system to study rapid regulated fusion between homotypic phospholipid monolayers. LD fusion involved an initial step in which the two adjacent membranes became continuous (<10 s), followed by the slower merging (100 s) of the neutral lipid cores to produce a single spherical LD. These fusion events were accompanied by changes to the LD surface organization. Measurements of LDs undergoing homotypic fusion showed that fused LDs maintained their initial volume, with a corresponding decrease in surface area suggesting rapid removal of membrane from the fused LD. This study provides estimates for the level of constitutive LD fusion in cells and questions the role of LD fusion in vivo. In addition, it highlights the extent of LD restructuring which occurs when homotypic LD fusion is triggered in a variety of cell types.
Why do placentas evolve? Evidence for a morphological advantage during pregnancy in live-bearing fish

A live-bearing reproductive strategy can induce large morphological changes in the mother during pregnancy. The evolution of the placenta in swimming animals involves a shift in the timing of maternal provisioning from pre-fertilization (females supply their eggs with sufficient yolk reserves prior to fertilization) to post-fertilization (females provide all nutrients via a placenta during the pregnancy). It has been hypothesised that this shift, associated with the evolution of the placenta, should confer a morphological advantage to the females leading to a more slender body shape during the early stages of pregnancy. We tested this hypothesis by quantifying three-dimensional shape and volume changes during pregnancy and in full-grown virgin controls of two species within the live-bearing fish family Poeciliidae: Poeciliopsis gracilis (non-placental) and Poeciliopsis turneri (placental). We show that P. turneri is more slender than P. gracilis at the beginning of the interbrood interval and in virgins, and that these differences diminish towards the end of pregnancy. This study provides the first evidence for an adaptive morphological advantage of the placenta in live-bearing fish. A similar morphological benefit could drive the evolution of placentas in other live-bearing (swimming) animal lineages.
Origin of Low Carrier Mobilities in Halide Perovskites

Halide perovskites constitute a new class of semiconductors that hold promise for low-cost solar cells and optoelectronics. One key property of these materials is the electron mobility, which determines the average electron speed due to a driving electric field. Here we elucidate the atomic-scale mechanisms and theoretical limits of carrier mobilities in halide perovskites by performing a comparative analysis of the archetypal compound CH3NH3PbI3, its inorganic counterpart CsPbI3, and a classic semiconductor for light-emitting diodes, wurtzite GaN, using cutting-edge many-body ab initio calculations. We demonstrate that low-energy longitudinal-optical phonons associated with fluctuations of the Pb–I bonds ultimately limit the mobility to 80 cm2/(V s) at room temperature. By extending our analysis to a broad class of compounds, we identify a universal scaling law for the carrier mobility in halide perovskites, and we establish the design principles to realize high-mobility materials.
Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes. Design Type(s) data integration objective Measurement Type(s) Biomarker Technology Type(s) digital curation Factor Type(s) tissue • diagnosis • microarray Sample Characteristic(s) Homo sapiens • breast • colon • uterine endometrium • kidney • lung • ovary • prostate gland • uterus • glia • peripheral blood • peripheral blood lymphocyte • colorectum • ependymal epithelium • squamous epithelium • peripheral blood mononuclear cell • alimentary canal • blast cell • leukocyte • connective tissue Design Type(s) data integration objective Measurement Type(s) Biomarker Technology Type(s) digital curation Factor Type(s) tissue • diagnosis • microarray Sample Characteristic(s) Homo sapiens • breast • colon • uterine endometrium • kidney • lung • ovary • prostate gland • uterus • glia • peripheral blood • peripheral blood lymphocyte • colorectum • ependymal epithelium • squamous epithelium • peripheral blood mononuclear cell • alimentary canal • blast cell • leukocyte • connective tissue Machine-accessible metadata file describing the reported data (ISA-Tab format)
Self-regulation strategies used by students with brain injury while transitioning to college.

PURPOSE Students with TBI enter college with strategies that they have used prior to being injured yet often without knowing which ones will be effective in helping them to be successful. The purpose here is to describe how semi-structured interviews were used to identify self-regulated learning strategies, to demonstrate the utility and reliability of coding self-regulated learning strategies, and to provide examples of student-centered goals derived from survey and interview responses. METHODS College students completed the College Survey for Students with Brain Injury (CSS-BI) and were interviewed before and after coaching support that focused on teaching self-regulated learning. Responses to interview questions about strategies were coded using a modified version of Zimmerman and Martinez-Pons's (1986) schema. Coders also rated strategies for specificity. RESULTS Strategies were reliably coded into 16 categories of self-regulation. Inter and intra-reliability were strong. Four of the five students reported using a larger variety of self-regulation strategies and strategies that were more specific after coaching support. DISCUSSION AND CONCLUSIONS It is possible to reliably code self-regulation learning strategies reported by college students with TBI. These measures have potential as functional 'outcomes' for students who are transitioning to college. Interview responses can be used to collaboratively create student-centered goals.
Document-Level Information as Side Constraints for Improved Neural Patent Translation

We investigate the usefulness of document information as side constraints for machine translation. We adapt two approaches to encoding this information as features for neural patent translation: As special tokens which are attached to the source sentence, and as tags which are attached to the source words. We found that sentence-attached features produced the same or better results as word-attached features. Both approaches produced signiﬁcant gains of over 1% BLEU over the baseline on a German-English translation task, while sentence-attached features also produced signiﬁcant gains of 0.7% BLEU on a Japanese-English task. We also describe a method to encode document information as additional phrase features for phrase-based translation, but did not ﬁnd any improvements.
Performance of protein induced by vitamin K absence or antagonist-II assessed by chemiluminescence enzyme immunoassay for hepatocellular carcinoma detection: a meta-analysis

Abstract Objectives: In the setting of surveillance for hepatocellular carcinoma (HCC) detection, the use of serum biomarkers in addition to ultrasonography (US) is still a matter of debate. Hence, we performed a meta-analysis to evaluate the diagnostic accuracy of protein induced by vitamin K absence or antagonist-II (PIVKA-II) and alpha-fetoprotein (AFP) alone or in combination for HCC detection in patients at risk of tumor development. Materials and methods: We performed a systematic search in PubMed and Scopus database for original articles published in English from 2011 to 2017, investigating the accuracy of PIVKA-II alone or in combination with AFP (reported as area under the curve [AUC]) for HCC detection among patients at risk of tumor development. Furthermore, we focused on studies in which serum PIVKA-II was assessed by highly sensitive chemiluminescence immunoassay (CLEIA). Results: A total of 11 studies (873 patients with HCC and 1244 patients with advanced liver disease/cirrhosis) were included in the meta-analysis. The weighted summary AUC (sAUC) of PIVKA-II and AFP for the discrimination between patients with HCC and those without was 0.791 (0.746–0.837) and 0.767 (0.732–0.803), respectively. The combination of PIVKA-II + AFP results in a sAUC of 0.859 (0.837–0.882). The performance for HCC detection of PIVKA-II + AFP was significantly superior to each biomarker used alone (ΔsAUC = 0.068, p = .032 and ΔsAUC = 0.092, p < .001, respectively). Conclusion: In clinical practice, the use of PIVKA-II + AFP in addition to US examination may improve the effectiveness of surveillance among patients at risk for HCC development.
Automated mitosis detection in histopathology using morphological and multi-channel statistics features

Context: According to Nottingham grading system, mitosis count plays a critical role in cancer diagnosis and grading. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to improve the accuracy of mitosis detection by selecting the color channels that better capture the statistical and morphological features, which classify mitosis from other objects. Materials and Methods: We propose a framework that includes comprehensive analysis of statistics and morphological features in selected channels of various color spaces that assist pathologists in mitosis detection. In candidate detection phase, we perform Laplacian of Gaussian, thresholding, morphology and active contour model on blue-ratio image to detect and segment candidates. In candidate classification phase, we extract a total of 143 features including morphological, first order and second order (texture) statistics features for each candidate in selected channels and finally classify using decision tree classifier. Results and Discussion: The proposed method has been evaluated on Mitosis Detection in Breast Cancer Histological Images (MITOS) dataset provided for an International Conference on Pattern Recognition 2012 contest and achieved 74% and 71% detection rate, 70% and 56% precision and 72% and 63% F-Measure on Aperio and Hamamatsu images, respectively. Conclusions and Future Work: The proposed multi-channel features computation scheme uses fixed image scale and extracts nuclei features in selected channels of various color spaces. This simple but robust model has proven to be highly efficient in capturing multi-channels statistical features for mitosis detection, during the MITOS international benchmark. Indeed, the mitosis detection of critical importance in cancer diagnosis is a very challenging visual task. In future work, we plan to use color deconvolution as preprocessing and Hough transform or local extrema based candidate detection in order to reduce the number of candidates in mitosis and non-mitosis classes.
Body Mass Index of 92,027 patients acutely admitted to general hospitals in Denmark: Associated clinical characteristics and 30-day mortality

Background Data are sparse on the range of BMI among patients acutely admitted to general hospitals. We investigated BMI values and associated patient characteristics, reasons for hospital admission, and mortality in Denmark. Methods We identified all persons with an acute inpatient admission 2011–2014 in Central Denmark Region and assessed BMI measurements recorded in the Clinical Information System. We used cross-sectional and cohort analyses to examine the BMI distribution and its association with demographic characteristics, comorbidities, medication use, tobacco smoking, reasons for admission, and 30-day mortality. Results Among 92,027 acutely admitted patients (median age 62 years, 49% female) with a BMI measurement, 4% had a BMI (kg/m2) <18.5, 42% a BMI between 18.5 and 25, 34% a BMI between 25 and 30, and 20% a BMI ≥30. Compared with normal-weight patients, 30-day mortality was high among patients with BMI <18.5 (7.5% vs. 2.8%, age- and smoking-adjusted odds ratio (aOR) 2.4; 95% confidence interval (CI): 2.0–2.9, whereas patients with overweight (aOR 0.7; 95% CI: 0.6–0.8) and obesity class I (aOR 0.8; 95% CI: 0.6–0.9)). Compared with the total population, patients with BMI <18.5 were older (68 years median); more were female (73%); more had comorbidities (Charlson Comorbidity Index score >0 in 42% vs. 33% overall), more were current smokers (45% vs. 27% overall), and acute admissions due to respiratory diseases or femoral fractures were frequent. In contrast, patients with BMI ≥30 were relatively young (59 years median), fewer smoked (24%): type 2 diabetes, sleep disorders, cholelithiasis, and heart failure were frequent diagnoses. Prevalence of therapies for metabolic syndrome, pain, and psychiatric disorders increased with higher BMI, while patients with BMI <18.5 frequently used asthma medications, glucocorticoids, and antibiotics. Conclusion In patients acutely admitted to general hospitals, reasons for hospital admission and associated clinical characteristics differ substantially according to BMI range. BMI <18.5 is a clinical predictor of high short-term mortality.
Frame-Based Representation for Event Detection on Twitter

Large scale first-hand tweets motivate automatic event detection on Twitter. Previous approaches model events by clustering tweets, words or segments. On the other hand, event clusters represented by tweets are easier to understand than those represented by words/segments. However, compared to words/segments, tweets are sparser and therefore makes clustering less effective. This article proposes to represent events with triple structures called frames, which are as efficient as, yet can be easier to understand than words/segments. Frames are extracted based on shallow syntactic information of tweets with an unsupervised open information extraction method, which is introduced for domain-independent relation extraction in a single pass over web scale data. This is then followed by bursty frame element extraction functions as feature selection by filtering frame elements with bursty frequency pattern via a probabilistic model. After being clustered and ranked, high-quality events are yielded and then reported by linking frame elements back to frames. Experimental results show that frame-based event detection leads to improved precision over a state-of-the-art baseline segment-based event detection method. Superior readability of frame-based events as compared with segment-based events is demonstrated in some example outputs. key words: frame, event representation, tweet, event detection, bursty, zscore
Improved Cross-Entropy-Based Tone Injection Scheme With Structured Constellation Extension Design for PAPR Reduction of OFDM Signals

The application of the cross entropy (CE) method to tone injection (TI) can make the peak-to-average power ratio (PAPR) of the orthogonal frequency division multiplexing (OFDM) signals reduced efficiently with great complexity savings. However, as a population-based search method, the CE method requires large samples to find a high-quality solution, which means higher complexity and more time consuming concerning convergence. To reduce the complexity while achieving promising PAPR performance, an improved CE based TI scheme is proposed in this paper. First, a structured extended constellation for rectangular quadrature amplitude modulation is designed to provide more freedom degrees. With proper parameter selection, the proposed extended constellation can offer more design flexibilities and achieve a better tradeoff between freedom degree and power increase. Then, by analyzing the impact of the subcarrier candidate population on the conventional CE based TI scheme, we derive an explicit expression for the determination of the size of the subcarrier candidate population. And, based on the prior information carried by the clipping signal, proper candidate subcarriers are selected. Finally, an improved CE based TI scheme is proposed, which can efficiently enhance the solution quality and greatly accelerate the convergence speed. Simulation results demonstrate that the improved CE based TI scheme achieves great improvements on the performance of PAPR, bit error rate, power increase and complexity compared with the conventional CE based TI scheme.
Phonological Complexity in the Japanese Short Poetry: Coexistence Between Nearest-Neighbor Correlations and Far-Reaching Anticorrelations

Sound correlations among six sites on the Japanese short poetry are analyzed in detail. For haiku composed of 5-7-5 syllables, the six sites are occupied by the head vowels on the three phrases as well as by the end sounds (in addition to five vowels, a syllabic nasal being included) on them. For tanka, first, one should divide the entire poem (5-7-5-7-7 syllables) into two parts, namely, the first (5-7-5) and the latter (5-7-7) part. For the six-dimensional array of sounds, there are 203 rhyme patterns possible. Specifically, for corpora of the haiku poetry, the complete works of three haiku poets, all of whom are distinguished in Japan, are selected. For those of the tanka, Collection of Ten Thousand Leaves and The Twenty-One Collections of Waka are chosen. Analyzed results through comparison between the surveyed and the expected frequencies show statistically the strong preference for the arrangements with a far-reaching antirhyming between sounds on the three ends, along with the correlation between those on the heads. In addition to the avoided rhyming, one finds a preference for specific arrangements exhibiting the nearest-neighbor correlations. Subsequently, to manifest the distinctive feature of each corpus, correlation analysis is carried out between frequency distributions of the arrangements. Moreover, in order to explore a statistical rule for the rank-ordered data, fitting is attempted to a long-tail distribution, followed by the Durbin-Watson testing. Quantitative analyses by using Gini’s coefficient as well as Shannon’s information entropy are also made. Finally, it is shown that the results of the complicated rhyming can be explained in part in comparison with the sound correlation between the first and the latter parts in the full names of Japanese.