Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content Measurement

Distributional word representations are widely used in NLP tasks. These representations are based on an assumption that words with a similar context tend to have a similar meaning. To improve the quality of the context-based embeddings, many researches have explored how to make full use of existing lexical resources. In this paper, we argue that while we incorporate the prior knowledge with context-based embeddings, words with different occurrences should be treated differently. Therefore, we propose to rely on the measurement of information content to control the degree of applying prior knowledge into context-based embeddings - different words would have different learning rates when adjusting their embeddings. In the result, we demonstrate that our embeddings get significant improvements on two different tasks: Word Similarity and Analogical Reasoning.
Investigation into the Effect of Extended Laundering on the KES-F Mechanical Properties of an Easy Care Treated Cotton Fabric

The effect of extended laundering on cotton fabric treated with Dimethylol dihydroxyethyleneurea (DMDHEU) easy care finish was investigated and the fabric characterised by crease recovery performance and the Kawabata Evaluation System for Fabrics (KES-F). The KES-F results indicated that the mechanical handle properties of the DMDHEU treated cotton fabrics were affected by both the levels of application of the DMDHEU easy care finishes and the stress relaxation of the fabrics in aqueous conditions.
Current understanding of disseminated intravascular coagulation

Disseminated intravascular coagulation (DIC) is a syndrome characterized by systemic intravascular activation of coagulation, leading to widespread fibrin deposition in the circulation. There is compelling evidence from clinical and experimental studies that DIC is involved in the pathogenesis of microvascular dysfunction and contributes to organ failure. In addition, the massive, ongoing activation of coagulation may result in depletion of platelets and coagulation factors, which may cause bleeding. Recent insights in important pathogenetic mechanisms that may lead to DIC have resulted in novel preventive and therapeutic approaches for patients with sepsis and deranged coagulation. Thrombin generation proceeds via the (extrinsic) tissue factor/factor VIIa route and simultaneously occurring depression of inhibitory mechanisms, such as antithrombin III and the protein C system. Also, impaired fibrin degradation, because of high circulating levels of plasminogen activator inhibitor, type 1 (PAI-1), contributes to an enhanced intravascular fibrin deposition. Supportive strategies aimed at the inhibition of coagulation activation may theoretically be justified and were beneficial in experimental and initial clinical studies. These strategies comprise inhibition of tissue factormediated activation of coagulation or restoration of physiological anticoagulant pathways, for example by means of the administration of recombinant human activated protein C.
A generic graph-based multidimensional recommendation framework and its implementations

As the volume of information on the Web is explosively growing, recommender systems have become essential tools for helping users to find what they need or prefer. Most existing systems are two-dimensional in that they only exploit User and Item dimensions and perform a typical form of recommendation 'Recommending Item to User'. Yet, in many applications, the capabilities of dealing with multidimensional information and of adapting to various forms of recommendation requests are very important. In this paper, we take a graph-based approach to accomplishing such requirements in recommender systems and present a generic graph-based multidimensional recommendation framework. Based on the framework, we propose two homogeneous graph-based and one heterogeneous graph-based multidimensional recommendation methods. We expect our approach will be useful for increasing recommendation performance and enabling flexibility of recommender systems so that they can incorporate various user intentions into their recommendation process. We present our research result that we have reached and discuss remaining challenges and future work.
Water–Ice Analogues of Polycyclic Aromatic Hydrocarbons: Water Nanoclusters on Cu(111)

Water has an incredible ability to form a rich variety of structures, with 16 bulk ice phases identified, for example, as well as numerous distinct structures for water at interfaces or under confinement. Many of these structures are built from hexagonal motifs of water molecules, and indeed, for water on metal surfaces, individual hexamers of just six water molecules have been observed. Here, we report the results of low-temperature scanning tunneling microscopy experiments and density functional theory calculations which reveal a host of new structures for water–ice nanoclusters when adsorbed on an atomically flat Cu surface. The H-bonding networks within the nanoclusters resemble the resonance structures of polycyclic aromatic hydrocarbons, and water–ice analogues of inene, naphthalene, phenalene, anthracene, phenanthrene, and triphenylene have been observed. The specific structures identified and the H-bonding patterns within them reveal new insight about water on metals that allows us to refine the so-called “2D ice rules”, which have so far proved useful in understanding water–ice structures at solid surfaces.
On-Road Multiple Obstacles Detection in Dynamical Background

Road In this paper, we focus on both the road vehicle and pedestrians detection, namely obstacle detection. At the same time, a new obstacle detection and classification technique in dynamical background is proposed. Obstacle detection is based on inverse perspective mapping and homography. Obstacle classification is based on fuzzy neural network. The estimation of the vanishing point relies on feature extraction strategy, which segments the lane markings of the images by combining a histogram-based segmentation with temporal filtering. Then, the vanishing point of each image is stabilized by means of a temporal filtering along the estimates of previous images. The IPM image is computed based on the stabilized vanishing point. The method exploits the geometrical relations between the elements in the scene so that obstacle can be detected. The estimated homography of the road plane between successive images is used for image alignment. A new fuzzy decision fusion method with fuzzy attribution for obstacle detection and classification application is described. The fuzzy decision function modifies parameters with auto-adapted algorithm to get better classification probability. It is shown that the method can achieve better classification result.
Point Placement by Phylogenetic Trees and its Application to Visual Analysis of Document Collections

The task of building effective representations to visualize and explore collections with moderate to large number of documents is hard. It depends on the evaluation of some distance measure among texts and also on the representation of such relationships in bi- dimensional spaces. In this paper we introduce an alternative approach for building visual maps of documents based on their content similarity, through reconstruction of phylogenetic trees. The tree is capable of representing relationships that allows the user to quickly recover information detected by the similarity metric. For a variety of text collections of different natures we show that we can achieve improved exploration capability and more clear visualization of relationships amongst documents.
Toward an estimation of binding constants in aqueous solution: studies of associations of vancomycin group antibiotics.

An approach toward the estimation of binding constants for organic molecules in aqueous solution is presented, based upon a partitioning of the free energy of binding. Consideration is given to polar and hydrophobic contributions and to the entropic cost of rotor restrictions and bimolecular associations. Several parameters (derived from an analysis of entropy changes upon the melting of crystals and from the binding of cell wall peptide analogues to the antibiotic ristocetin A) which may be useful guides to a crude understanding of binding phenomena are presented: (i) amide-amide hydrogen bond strengths of -(1 to 7) +/- 2 kJ.mol-1, (ii) a hydrophobic effect of -0.2 +/- 0.05 kJ.mol-1.A-2 of hydrocarbon removed from exposure to water in the binding process, and (iii) free energy costs for rotor restrictions of 3.5-5.0 kJ.mol-1. The validity of the parameters for hydrogen bond strengths is dependent on the validity of the other two parameters. The phenomenon of entropy/enthalpy compensation is considered, with the conclusion that enthalpic barriers to dissociations will result in larger losses in translational and rotational entropy in the association step. The dimerization of some vancomycin group antibiotics is strongly exothermic (-36 to -51 kJ.mol-1) and is promoted by a factor of 50-100 by a disaccharide attached to ring 4 (in vancomycin and eremomycin) and by a factor of ca. 1000 by an amino-sugar attached to the benzylic position of ring 6 in eremomycin. The dimerization process (which, as required for an exothermic association, appears to be costly in entropy) may be relevant to the mode of action of the antibiotics.
The Labor Market E ff ects of a Refugee Wave : Synthetic Control Method meets the Mariel Boatlift

We apply the synthetic control method to re-examine the wage and employment effect of the Mariel Boatlift, a large inflow of Cuban refugees to Miami in 1980. This method improves on previous studies by choosing a control group for Miami so as to best match its labor market features in the eight years before the Boatlift. Given the presence of significant measurement error for average city wages we emphasize the importance of using the May-ORG CPS sample rather than the March-CPS. The first includes a more reliable measure of weekly wages, has larger sample size and ∗We thank David Card, Colin Cameron, Thomas Lemieux, David Green, Michael Clemens, Pat Kline, Doug Miller, Joan Monras, Enrico Moretti, David Roodman, Shu Shen and participants in seminars at NBER winter meetings, University of British Columbia and Georgetown University for useful comments. We are grateful for the criticism contained in Borjas (2015b) to the first draft of this paper, as it has helped our current revision. We have not received any financial support for this paper. †Giovanni Peri: Department of Economics, UC Davis, One Shields Avenue, Davis CA, 95616; email: gperi@ucdavis.edu. ‡Vasil Yasenov: Department of Economics, UC Davis, One Shields Avenue, Davis CA, 95616; email: viyasenov@ucdavis.edu.
A selective rendering method for data visualization

Author(s): Wang, Wencheng; Wu, En-Hua; Max, Nelson | Abstract: Selective visualization is a solution for visualizing data of large size and dimensionality. In this paper a new method is proposed for effectively rendering certain chosen parts among the full set of data in terms of a colour buffer, referred to as the virtual plane, for storing intermediate results. By this method, scientists may concentrate their attention on the contents of data in which they are interested. Besides, the method could be easily integrated with all the current direct volume rendering techniques, especially progressive refinement methods and selective methods.
Rectification method for lookup-table type FPGA's

A method to rectify lookup-table-type field-programmable gate array (FPGA) designs is presented. Instead of changing the netlist, only the functionality realized by lookup tables in a chip is modified and the netlist is retained so that there is no change in the delay of the chip. The problem is formalized using characteristic functions, and a redesign technique based on Boolean relations is presented. <<ETX>>
Decentralized search in expert networks: Generic models and performance bounds

We investigate the problem of query answering in expert networks, which are composed of inter-connected experts with various specialties. Upon receiving a query, the expert network is tasked to route this query to experts with sufficient expertise in a timely and reliable manner. However, the efficiency of query answering depends on the underlying query routing protocol being used. Among all possible query routing protocols, decentralized search, operating purely on each expert's local information without any network global knowledge, represents the most basic and scalable routing protocol. However, there is still a lack of fundamental understanding on the efficiency of decentralized search in different expert networks. In this regard, we establish a generic model that can abstract diversified social and structural attributes in various expert networks into a common framework, thus applicable to a wide range of network scenarios. On top of such generic network model, we then study decentralized search by quantifying its performance under a variety of network parameters. Our key findings reveal the existence of network conditions, under which decentralized search can achieve significantly short query routing paths (i.e., between O(log n) and O(log2 n) hops, n: total number of experts in the network). To the best of our knowledge, this is the first work studying fundamental behaviors of decentralized search without relying on strict underlying network structures in expert networks. Experiments in both synthetic and real expert networks confirm the efficacy of the developed performance bounds in understanding and reasoning the network performance.
A Laboratory to Facilitate Computer-Controlled Behavioral Experiments

The Management Science Laboratory was conceived by faculty in the Center for Research in Management Science at the University of California at Berkeley as a facility for behavioral research.1 A facilities grant from the National Science Foundation was awarded to the Center, and an interest group was formed to design and construct a laboratory for experiments with human subjects in situations based on models from the behavioral disciplines. Our thinking was guided by results from a prototype laboratory2 and by the emerging literature in experimental gaming. Two princi-
Grand unified theory based on the SU(6) symmetry

We present a complete set of generators for the rank 5 special unitary group, SU(6), to unify strong, weak and electromagnetic interactions. The unification is realized through the breaking pattern of SU(6){yields}SU(3){sub C}xSU(3){sub H}xU(1){sub C} followed by SU(3){sub H}{yields}SU(2){sub L}xU(1){sub B}. All known elementary particles and its quantum numbers are well accommodated in its {l_brace}6{r_brace} and {l_brace}15{r_brace} multiplets. These multiplets require a new neutral fermion which should be assigned as the heavy Majorana neutrino to realize the seesaw mechanism naturally.
A denotational semantics of inheritance

This thesis develops a semantic model of inheritance and investigates its applications for the analysis and design of programming languages. Inheritance is a mechanism for incremental programming in the presence of self-reference. This interpretation of inheritance is formalized using traditional techniques of fixed-point theory, resulting in a compositional model of inheritance that is directly applicable to object-oriented languages. Novel applications of inheritance revealed by the model are illustrated to show that inheritance has wider significance beyond object-oriented class inheritance. Constraints induced by self-reference and inheritance are investigated using type theory and yield a formal characterization of abstract classes and a demonstration that the subtype relation is a direct consequence of the basic mechanism of inheritance. The model is proven equivalent to the operational semantics of inheritance embodied by the interpreters of object-oriented languages like Smalltalk. Concise descriptions of inheritance behavior in several object-oriented languages, including Smalltalk, Beta, Simula, and Flavors, are presented in a common framework that facilitates direct comparison of their features.
White blood cell concentrations during lower body negative pressure and blood loss in humans

What is the central question of this study? Is lower body negative pressure a useful surrogate to study white blood cell responses to haemorrhage in humans? What is the main finding and its importance? We found that lower body negative pressure appears to be a useful surrogate to study the early white blood cell mobilization response during blood loss.
Use of high doses of folic acid supplements in pregnant women in Spain: an INMA cohort study

Objectives We examined the use of low (<400 μg/day, including no use) and high folic acid supplement (FAS) dosages (≥1000 μg/day) among pregnant women in Spain, and explored factors associated with the use of these non-recommended dosages. Design Population-based cohort study. Setting Spain. Participants We analysed data from 2332 pregnant women of the INMA study, a prospective mother-child cohort study in Spain. Main outcome measures We assessed usual dietary folate and the use of FAS from preconception to the 3rd month (first period) and from the 4th to the 7th month (second period), using a validated food frequency questionnaire. We used multinomial logistic regression to estimate relative risk ratios (RRRs). Results Over a half of the women used low dosages of FAS in the first and second period while 29% and 17% took high dosages of FAS, respectively. In the first period, tobacco smoking (RRR=1.63), alcohol intake (RRR=1.40), multiparous (RRR=1.44), unplanned pregnancy (RRR=4.20) and previous spontaneous abortion (RRR=0.58, lower use of high FAS dosages among those with previous abortions) were significantly associated with low FAS dosages. Alcohol consumption (RRR=1.42), unplanned pregnancy (RRR=2.66) and previous spontaneous abortion (RRR=0.68) were associated with high dosage use. In the second period, only tobacco smoking was significantly associated with high FAS dosage use (RRR=0.67). Conclusions A high proportion of pregnant women did not reach the recommended dosages of FAS in periconception and a considerable proportion also used FAS dosages ≥1000 μg/day. Action should be planned by the Health Care System and health professionals to improve the appropriate periconceptional use of FAS, taking into consideration the associated factors.
Sonographic-detected joint effusion compared with physical examination in the assessment of sacroiliac joints in spondyloarthritis

Objective: An observational case–control study was designed to analyse the discriminative value of ultrasound (US)-detected joint effusion compared with physical examination in the assessment of sacroiliac joints (SIJ) in patients with spondyloarthropathy (SpA) with or without inflammatory back pain (IBP). Methods: 45 patients with SpA, classified according to European Spondylarthropathy Study Group criteria, and 30 healthy volunteers were studied. All patients had clinical evaluation of the SIJ, Bath ankylosing spondylitis (AS) metrology index, Bath AS disease activity index, Bath AS functional index, health assessment questionnaire, patient’s and physician’s visual analogue scale on global disease activity. Results: Ultrasound showed joint effusion in 38.9% of SIJ of patients with SpA and in 1.7% of SIJ of controls (p<0.001). The presence of IBP was significantly associated with SIJ effusion assessed by US alone or plus at least one SIJ test. SIJ effusion assessed by US alone or plus at least one SIJ test had a positive likelihood ratio (LR) (2.67 and 4.04, respectively) for the presence of IBP higher than LR of single clinical tests. Positive sacral sulcus test, iliac gapping and midline sacral thrust test were associated with SIJ effusion assessed by US, but all clinical tests, singly and in various combinations, had a low LR for the presence of SIJ effusion assessed by US. Conclusions: The study suggests that high resolution sonography is useful in the assessment of SIJ involvement in SpA, resulting in images that are fast and inexpensive and may locate, complementing the physical examination, the origin of IBP.
Purified Dendritic Cell-Tumor Fusion Hybrids Supplemented with Non-Adherent Dendritic Cells Fraction Are Superior Activators of Antitumor Immunity

Background Strong evidence supports the DC-tumor fusion hybrid vaccination strategy, but the best fusion product components to use remains controversial. Fusion products contain DC-tumor fusion hybrids, unfused DCs and unfused tumor cells. Various fractions have been used in previous studies, including purified hybrids, the adherent cell fraction or the whole fusion mixture. The extent to which the hybrids themselves or other components are responsible for antitumor immunity or which components should be used to maximize the antitumor immunity remains unknown. Methods Patient-derived breast tumor cells and DCs were electro-fused and purified. The antitumor immune responses induced by the purified hybrids and the other components were compared. Results Except for DC-tumor hybrids, the non-adherent cell fraction containing mainly unfused DCs also contributed a lot in antitumor immunity. Purified hybrids supplemented with the non-adherent cell population elicited the most powerful antitumor immune response. After irradiation and electro-fusion, tumor cells underwent necrosis, and the unfused DCs phagocytosed the necrotic tumor cells or tumor debris, which resulted in significant DC maturation. This may be the immunogenicity mechanism of the non-adherent unfused DCs fraction. Conclusions The non-adherent cell fraction (containing mainly unfused DCs) from total DC/tumor fusion products had enhanced immunogenicity that resulted from apoptotic/necrotic tumor cell phagocytosis and increased DC maturation. Purified fusion hybrids supplemented with the non-adherent cell population enhanced the antitumor immune responses, avoiding unnecessary use of the tumor cell fraction, which has many drawbacks. Purified hybrids supplemented with the non-adherent cell fraction may represent a better approach to the DC-tumor fusion hybrid vaccination strategy.
Melanocortin receptor agonists MCR 1‐5 protect photoreceptors from high‐glucose damage and restore antioxidant enzymes in primary retinal cell culture

Retinal photoreceptors are particularly vulnerable to local high‐glucose concentrations. Oxidative stress is a risk factor for diabetic retinopathy development. Melanocortin receptors represent a family of G‐protein‐coupled receptors classified in five subtypes and are expressed in retina. Our previous data indicate that subtypes 1 and 5 receptor agonists exert a protective role on experimental diabetic retinopathy. This study focuses on their role in primary retinal cell cultures in high‐glucose concentrations. After eye enucleation from wild‐type male C57BL/6 mice, retinal cells were isolated, plated in high‐glucose concentration and treated with melanocortin receptors 1 and 5 agonists and antagonists. Immunocytochemical and biochemical analysis showed that treatment with melanocortin receptors 1 and 5 agonists reduced anti‐inflammatory cytokines and chemokines and enhanced manganese superoxide dismutase and glutathione peroxidase levels, preserving photoreceptor integrity. According with these evidences, we propose a major role of melanocortin receptors 1 and 5 on primary retinal cell response against high glucose or oxidative insults.