Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep learning for constructing microblog behavior representation to identify social media user's personality

1 Due to the rapid development of information technology, Internet has become part of everyday life gradually. People would like to communicate with friends to share their opinions on social networks. The diverse social network behavior is an ideal users’ personality traits reflection. Existing behavior analysis methods for personality prediction mostly extract behavior attributes with heuristic. Although they work fairly well, but it is hard to extend and maintain. In this paper, for personality prediction, we utilize deep learning algorithm to build feature learning model, which could unsupervised extract Linguistic Representation Feature Vector (LRFV) from text published on Sina Micro-blog actively. Compared with other feature extraction methods, LRFV, as an abstract representation of Micro-blog content, could describe use’s semantic information more objectively and comprehensively. In the experiments, the personality prediction model is built using linear regression algorithm, and different attributes obtained through different feature extraction methods are taken as input of prediction model respectively. The results show that LRFV performs more excellently in micro-blog behavior description and improve the performance of personality prediction model. 2
Geoelectrical Investigations for Tailing Ponds' Geochemical Zonation at Paraul Cailor, Romania

Tailing ponds are seen today both as polluting factors and mineral resources. Investigating their properties, calculating their volumes, evaluating their metal stocks and their acid drainage potential are critical issues both for the industry and the environmental agencies. These objectives appear today as an important and obvious environmental problem, which, in nowadays’ concept of social, economical and ethical development, requests a careful and complex approach of which results must end up at a fast and efficient solving of the problem, respecting meanwhile the sustainable development principles. This study showed that geoelectric investigations can differentiate the oxidation and reduction zones. Volumes for these two zones were calculated.
Convolutional Neural Network-Based Polar Decoding

In this work, we extend the capability of convolutional neural network (CNN) to polar code decoding. Previous work has shown that a multi-layer perceptron (MLP), which is a basic form of deep neural network (DNN), can achieve high decoding accuracy and speed for polar code when the block length is very short. However, its performance drops drastically for longer codes, due to the bulky network structure. In this work, we design and implement a CNN for polar decoding. In order to improve the decoding accuracy, we introduce auxiliary labels into CNN output based on the encoding structure of polar code. In addition, we propose to prune the CNN to preserve the decoding accuracy of wider network while reducing the computation and the parameters. With these two innovations, the decoding accuracy of original CNN can be improved. We carry out extensive simulations to compare our designed CNN decoder with MLP decoder. Results show that when the code length is 64, our model is 60 times smaller than the MLP decoder, and the accuracy of our model increases with model size, while MLP reaches saturation. Additional results show that our proposed method outperforms original CNN with regard to the BER performance under marginal parameter increase.
Exploiting Unlabeled Text with Different Unsupervised Segmentation Criteria for Chinese Word Segmentation

This paper presents a novel approach to improve Chinese word seg- mentation (CWS) that attempts to utilize unlabeled data such as training and test data without annotation for further enhancement of the state-of-the-art perfor- mance of supervised learning. The lexical information plays the role of infor- mation transformation from unlabeled text to supervised learning model. Four types of unsupervised segmentation criteria are used for word candidate extrac- tion and the corresponding word likelihood computation. The information output by unsupervised segmentation criteria as features therefore is integrated into su- pervised learning model to strengthen the learning for the matching subsequence. The effectiveness of the proposed method is verified in data sets from the latest in- ternational CWS evaluation. Our experimental results show that character-based conditional random fields framework can effectively make use of such informa- tion from unlabeled data for performance enhancement on top of the best existing results.
The Synaptobrevin-related Domains of Bos1p and Sec22p Bind to the Syntaxin-like Region of Sed5p*

SNAREs (soluble N -ethylmaleimide-sensitive fusion proteinattachment protein receptors) are cytoplasmically oriented membrane proteins that reside on vesicular carriers (v-SNARE) and target organelles (t-SNARE). The pairing of a stage-specific v-SNARE with its cognate t-SNARE may mediate the specificity of membrane traffic. In the yeast Saccharomyces cerevisiae transport between the endoplasmic reticulum and Golgi complex employs two v-SNAREs, Bos1p and Sec22p, each containing a domain that is related to the neuronal v-SNARE synaptobrevin. Sed5p, which is homologous to syntaxin, is the t-SNARE that functions at this stage of the secretory pathway. Here we report that regions of Bos1p and Sec22p, which are homologous to synaptobrevin, bind to the syntaxin-like domain of Sed5p. Furthermore, we demonstrate that efficient v-SNARE/t-SNARE interactions require the participation of both v-SNAREs, indicating that, unlike post-Golgi membrane traffic, the active form of the endoplasmic reticulum to Golgi v-SNARE is a heteromeric complex.
Autonomic buffer pool configuration in PostgreSQL

As database management systems (DBMSs) continue to expand into new application areas, the complexity of the systems and the diversity of database workloads are increasing. Managing the performance of DBMSs via manual adjustment of resource allocations in this new environment has become impractical. Autonomic DBMSs shift the responsibility for performance management onto the systems themselves. This paper serves as a proof of concept, illustrating how autonomic principles can be applied to a DBMS to provide automatic sizing of buffer pools, a key resource in a DBMS. We describe an implementation of our autonomic system in PostgreSQL, an open source database management system, and provide a set of experiments that verify our approach.
System modelling of the interaction between surface and ground waters in problems of hydrology

ABSTRACT The objective of the paper is to give a survey of the mathematical (quantitative) modelling of the interaction between surface water and groundwater. Besides describing the existing approach to such modelling and the main difficulties in its realization, the paper presents a brief review of the principal works on the subject under consideration including Soviet ones. The construction of such coupled models requires the development of methods of conjunction between models which represent surface and subsurface flows, which describe the different processes of water transfer and transformation, constituting the hydrological cycle, and which include the different components of hydrological, hydrogeological and water management systems (water bodies, streams, aquifers, etc.). Such models are of different complexities and have different dimensionality in space variables. The characteristic time-scales of transient processes for surface water and groundwater differ greatly, and this is of profound impor.
Mean-variance optimal linear precoders for random MISO broadcast channels

We consider the problem of designing linear precoders for Gaussian multiple input, single output (MISO) broadcast (BC) channels with a random channel matrix, where the randomness models imperfect channel knowledge due to feedback delay, channel time variations, limited training, or quantized feedback. First, we introduce a design framework where the goal is to minimize outage probability (or risk) or maximize rate. It is shown that full-power precoders, i.e. those that meet the transmit power constraint with equality, satisfy the design criterion. Next, we motivate and solve a related mean-variance optimization problem by supposing the channel density is a Gaussian mixture model (GMM) and deriving efficient formulae to compute the objective and constraint functions.
Frequency of occurrence of moderate to great earthquakes in intracontinental regions: Implications for changes in stress, earthquake prediction, and hazards assessments

We investigate the departure of shallow intracontinental earthquakes from the frequency-magnitude relationship log (n(M)) = a - bM. We consider seven large continental regions but exclude subduction zones. In each, “active” and “stable” areas are differentiated. Within active areas we separately categorize earthquakes on faults with high slip rates. We use data sets from 1978–1994 and 1900–1994, which are complete for moment magnitudes Mw≥5.3 and ≥7.0, to calculate changes in b value with Mw. For all active intracontinental regions combined except Asia, b changes at 98% confidence from 0.90 to 2.1 at a corner magnitude Mc of 6.9 to 7.0. The distribution for stable regions indicates a similar change. Values of Mc are associated with downdip widths of rupture of about 23 to 27 km, which are smaller than those for subduction zones. In each case, Mc marks a transition from unbounded to bounded earthquakes. In Asia, events from 1958 to 1994 also delineate a similar change near Mc 7.0. Earthquakes in Asia of 7.0≤Mw≤8.1 from 1900 to 1957, however, define a b value of 1.0 and a moment release rate 5.6 times higher than that from 1958 to 1994. Those anomalous values indicate that a large region of Asia was close to failure, i.e., near a self-organized critical state, during the earlier period. We associate those changes with the giant Himalayan earthquake in 1950 of Mw 8.6. Regional variations in seismic strain release rates correlate with the types of processes at adjacent plate boundaries. Extrapolating rates of activity of the past 95 years to Mw≥8.0 indicates that such events should be very rare in stable areas.
Construction of block orthogonal golay sequences and application to channel estimation of mimo-ofdm systems

In this paper, we construct a family of block orthogonal Golay sequences that have low peak-to-mean envelope power ratio (PMEPR) as well as block wise orthogonal properties. We then present an application of the sequences to channel estimation of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We compare the performance of the proposed algorithm with that of a frequency division multiplexing (FDM) piloting algorithm, and investigate the effect of co-channel interference (CCI) on the channel estimation performance.
Deformations of Homotopy Algebras

Abstract Let k be a field of characteristic zero, 𝒪 be a dg operad over k and let A be an 𝒪-algebra. In this note we suggest a definition of a formal deformation functor of A from the category of artinian local dg algebras to the category of simplicial sets. This functor generalizes the classical deformation functor for an algebra over a linear operad. In the case 𝒪 and A are non-positively graded, we prove that Def A is governed by the tangent Lie algebra T A which can be calculated as the Lie algebra of derivations of a cofibrant resolution of A. An example shows that the result does not necessarily hold without the non-positivity condition.
Environmental Controls on the Surface Energy Budget over a Large Southern Inland Water in the United States: An Analysis of One-Year Eddy Covariance Flux Data

AbstractThe authors analyzed the surface energy fluxes that were measured by an eddy covariance system over the Ross Barnett Reservoir in Mississippi for a 1-yr period in 2008. On a monthly basis over the course of the year, positive vertical temperature and vapor pressure differences were observed, though negative vertical temperature differences occurred occasionally during some short periods when overwater air masses were warmer than the water surface. Consequently, the unstable atmospheric surface layer (ASL) and sufficient mechanical mixing led to positive sensible H and latent λE heat fluxes. The quantities H and λE were distinctively out of phase with the net radiation Rn. The H and λE from the water to the ASL was still substantial on nights with a negative Rn and in winter when Rn was very small. From February to August, approximately 60%–91% of the Rn was used for H and λE, with the remainder being stored in the water. Fueled by the previously stored heat in the water, H and λE exceeded Rn by al.
Chaotic watermarks for embedding in the spatial digital image domain

Binary (bi-valued) digital signals, which are suitable watermarks for digital images are presented. They are generated by using chaotic dynamical systems that provide sufficient watermark complexity and controlled lowpass characteristics. Watermark detection is performed without resorting to the original image and its reliability is studied. Efficient robustness under lossy compression, lowpass filtering and other image processing can be achieved. Possible watermark detection after geometrical transformations is discussed.
Tumor necrosis factor receptor 2-signaling in CD133-expressing cells in renal clear cell carcinoma

Compared to normal kidney, renal clear cell carcinomas (ccRCC) contain increased numbers of interstitial, non-hematopoietic CD133+cells that express stem cell markers and exhibit low rates of proliferation. These cells fail to form tumors upon transplantation but support tumor formation by differentiated malignant cells. We hypothesized that killing of ccRCC CD133+ (RCCCD133+) cells by cytotoxic agents might be enhanced by inducing them to divide. Since tumor necrosis factor-alpha (TNF), signalling through TNFR2, induces proliferation of malignant renal tubular epithelial cells, we investigated whether TNFR2 might similarly affect RCCCD133+cells. We compared treating organ cultures of ccRCC vs adjacent nontumour kidney (NK) and RCCCD133+ vs NK CD133+ (NKCD133+) cell cultures with wild-type TNF (wtTNF) or TNF muteins selective for TNFR1 (R1TNF) or TNFR2 (R2TNF). In organ cultures, R2TNF increased expression of TNFR2 and promoted cell cycle entry of both RCCCD133+ and NKCD133+ but effects were greater in RCCCD133+. In contrast, R1TNF increased TNFR1 expression and promoted cell death. Importantly, cyclophosphamide triggered much more cell death in RCCCD133+ and NKCD133+cells pre-treated with R2TNF as compared to untreated controls. We conclude that selective engagement of TNFR2 by TNF can drives RCCCD133+ proliferation and thereby increase sensitivity to cell cycle-dependent cytotoxicity.
Clostridium taeniosporum spore ribbon‐like appendage structure, composition and genes

Clostridium taeniosporum spores have about 12 large, flat, ribbon‐like appendages attached through a common trunk at one spore pole to a previously unknown surface layer outside the coat that is proposed to be called the ‘encasement’. Appendages are about 4.5 μm long, 0.5 μm wide and 30 nm thick and taper at the attachment end into a semicircle that is twisted relative to the flat ribbon. Individual fibrils, about 45 nm in length with spherical heads and long thin tails, form a hair‐like nap, visible along the appendage edge. Four appendage proteins have been detected: a paralogous pair of 29 kDa (designated P29a and P29b), a glycoprotein of about 37 kDa (designated GP85) and an orthologue of the Bacillus spore morphogenetic protein SpoVM. The P29 proteins consist of duplicated regions and each region includes a domain of unknown function 11. The GP85 glycoprotein contains a collagen‐like region. The genes for P29a and b, GP85 and possibly related proteins are closely linked on two small chromosome fragments. Putative σK‐dependent promoters upstream of the P29a and b genes indicate that they likely are expressed late in the mother cell, consistent with their deposition into the layer external to the coat.
Lunar surface rock abundance and regolith fines temperatures derived from LRO Diviner Radiometer data

[1] Surface temperatures derived from thermal infrared measurements provide a means of understanding the physical properties of the lunar surface. The contrasting thermophysical properties between rocks and regolith fines cause multiple temperatures to be present within the field of view of nighttime multispectral data returned from the Lunar Reconnaissance Orbiter (LRO) Diviner Radiometer between 60°N/S latitudes. Regolith temperatures are influenced by the presence of rocks in addition to factors such as the thermophysical properties of the regolith fines, latitude and local slopes, and radiative heating from adjacent crater walls. Preliminary comparisons of derived rock concentrations with LRO Camera images show both qualitative and quantitative agreement. Although comparisons of derived rock concentrations with circular polarization ratio radar data sets display general similarities, there are clear differences between the two data sets in the relative magnitude and areal extent of rocky signatures. Several surface units can be distinguished based on their regolith temperature and rock concentration values and distributions including maria and highlands surfaces, rocky impact craters, rilles, and wrinkle ridges, dark mantled deposits, and isolated cold surfaces. Rock concentrations are correlated with crater age and rocks are only preserved on the youngest surfaces or where steep slopes occur and mass wasting prevents mantling with fines. The presence of rocky surfaces excavated by young impacts allows for the estimation of minimum regolith thickness from the size of the impact. The derived rock concentrations confirm the presence of thicker regolith cover in the highlands and in locations of radar-dark haloes.
Relating automatic vowel space estimates to talker intelligibility

Differences in pronunciation have been shown to underlie significant talker-dependent intelligibility differences. There are several dimensions of variability that are correlated with talker intelligibility including pitch range, vowel-space expansion, and rhythmic patterns. Prior work has shown that some of the better predictors of individual intelligibility are based on the talker’s F1 by F2 vowel space, but findings are based on handcorrected measurements on carefully balanced sets of vowels, making large scale analysis impractical. This paper proposes a novel method for automatic estimation of a talker’s vowel space using sparse expanded vowel space representations, including an approximate convex hull sampling, which are projected to a low dimensional space for intelligibility scoring. Both supervised and unsupervised mappings are used to generate an intelligibility score. Automatic intelligibility rankings are assessed in terms of correlation with an intelligibility score based on human transcription accuracy. We find that including a larger sample of vowels (beyond point vowels) leads to improved performance, obtaining correlations of roughly 0.6 for this feature alone, which is a strong result given that there are other factors that may also contribute to a talker’s intelligibility in addition to a talker’s vowel space area.
Widespread Molecular Patterns Associated with Drug Sensitivity in Breast Cancer Cell Lines, with Implications for Human Tumors

Background Recent landmark studies have profiled cancer cell lines for molecular features, along with measuring the corresponding growth inhibitory effects for specific drug compounds. These data present a tool for determining which subsets of human cancer might be more responsive to particular drugs. To this end, the NCI-DREAM-sponsored DREAM7: Drug Sensitivity Prediction Challenge (sub-challenge 1) set out to predict the sensitivities of 18 breast cancer cell lines to 31 previously untested compounds, on the basis of molecular profiling data and a training subset of cell lines. Methods and Results With 47 teams submitting blinded predictions, team Creighton scored third in terms of overall accuracy. Team Creighton's method was simple and straightforward, incorporated multiple expression data types (RNA-seq, gene array, RPPA), and incorporated all profiled features (not only the “best” predictive ones). As an extension of the approach, cell line data, from public datasets of expression profiling coupled with drug sensitivities (Barretina, Garnett, Heiser) were used to “predict” the drug sensitivities in human breast tumors (using data from The Cancer Genome Atlas). Drug sensitivity correlations within human breast tumors showed differences by expression-based subtype, with many associations in line with the expected (e.g. Lapatinib sensitivity in HER2-enriched cancers) and others inviting further study (e.g. relative resistance to PI3K inhibitors in basal-like cancers). Conclusions Molecular patterns associated with drug sensitivity are widespread, with potentially hundreds of genes that could be incorporated into making predictions, as well as offering biological clues as to the mechanisms involved. Applying the cell line patterns to human tumor data may help generate hypotheses on what tumor subsets might be more responsive to therapies, where multiple cell line datasets representing various drugs may be used, in order to assess consistency of patterns.
Kinematic modeling and control for human-robot cooperation considering different interaction roles

SUMMARY This paper presents a novel approach for the description of physical human-robot interaction (pHRI) tasks that involve two-arm coordination, and where tasks are described by the relative pose between the human hand and the robot hand. We develop a unified kinematic model that takes into account the human-robot system from a holistic point of view, and we also propose a kinematic control strategy for pHRI that comprises different levels of shared autonomy. Since the kinematic model takes into account the complete human-robot interaction system and the kinematic control law is closed loop at the interaction level, the kinematic constraints of the task are enforced during its execution. Experiments are performed in order to validate the proposed approach, including a particular case where the robot controls the human arm by means of functional electrical stimulation (FES), which may potentially provide useful solutions for the interaction between assistant robots and impaired individuals (e.g., quadriplegics and hemiplegics).