Miracle-dz/UniFAR-FTUs huggingface dataset:
Systems of natural-language-facilitated human-robot cooperation: A review

Natural-language-facilitated human-robot cooperation (NLC), in which natural language (NL) is used to share knowledge between a human and a robot for conducting intuitive human-robot cooperation (HRC), is continuously developing in the recent decade. Currently, NLC is used in several robotic domains such as manufacturing, daily assistance and health caregiving. It is necessary to summarize current NLC-based robotic systems and discuss the future developing trends, providing helpful information for future NLC research. In this review, we first analyzed the driving forces behind the NLC research. Regarding to a robot s cognition level during the cooperation, the NLC implementations then were categorized into four types {NL-based control, NL-based robot training, NL-based task execution, NL-based social companion} for comparison and discussion. Last based on our perspective and comprehensive paper review, the future research trends were discussed.
The effect of whole‐blood storage time on the number of white cells and platelets in whole blood and in white cell–reduced red cells

BACKGROUND: Whole blood (WB) can be stored for some time before it is processed into components. After introduction of universal white cell (WBC) reduction, it was observed that longer WB storage was associated with more residual WBCs in the WBC‐reduced red cells (RBCs). Also, weak propidium iodide (PI)‐positive events were observed in the flow cytometric WBC counting method, presumably WBC fragments. The effect of storage time on the composition of WB and subsequently prepared WBC‐reduced RBCs was studied.
Timing-Dependent Effects of Restraint Stress on Eosinophilic Airway Inflammation in Mice

Background: Chronicstress has been proposed to aggravate allergic inflammation, whereas acute stress may have functional beneficial effects. The aim of this study was to investigate the influence of timing of single short restraint stress (RST) in a model of eosinophilic airway inflammation. Methods: The airways of ovalbumin (OVA)-sensitized mice were exposed to an intranasal OVA challenge. RST was applied in two different ways; either 2 h before (pre-stress) or after (post-stress) the OVA challenge, respectively, or as a combination of stress before and after (double-stress) the OVA challenge. One group of mice was also treated with metyrapone (ME) prior to a pre-stress challenge. The inflammatory cell response was evaluated in bronchoalveolar lavage fluid (BALF), lung and nasal tissue, as well as bone marrow. Result: RST applied prior to the OVA challenge (pre-stress) inhibited OVA-induced airway inflammation in BALF and lung tissue, and reduced nasal histopathology compared to unstressed mice. Given as post-stress or double-stress, RST did not affect the inflammation in BALF, lungs or nasal tissue. Pre-treatment with ME prevented the pre-challenge stress evoked decrease in inflammation in BALF and lungs. Conclusion: Effects of RST on eosinophilic airway inflammation appear to be strongly dependent on timing and, as could be judged from the ME inhibition pattern, also corticosterone dependent. Hypothalamic-pituitary-adrenal axis activation probably influences eosinophilic inflammation through specific sequences of compartmental activation and thereby timing effects are evident on cellular recruitment pattern during the allergic reaction.
CSC 2541 Project Paper : Mood-based Image to Music Synthesis

This paper explores the generation of music that expresses a similar mood as a given image. Combining techniques from areas of computer vision and sequence modelling, we show how a CNN with an RNN can generate music conditioned on an image. After training seven different models, we conducted 360 surveys to evaluate our results, and find them promising. In addition, we also explore the ability of variational recurrent autoencoders in capturing global features of music that can potentially help with our objective. Due to time and resource constraints, this exploration has not yet produced a conclusive answer, although we present several directions to take in the future to further enquire into this topic.
Polyphasic characterization of benthic cyanobacterial diversity from biofilms of the Guadarrama river (Spain): morphological, molecular, and ecological approaches1

The occurrence and environmental factors responsible for the distribution of benthic cyanobacteria in running waters remain largely unexplored in comparison with those of other aquatic ecosystems. In this study, combined data of ecological characteristics, molecular analysis (based on 16S rRNA gene), and direct microscopic inspection of environmental samples were analyzed in parallel with the morphological characterization of the isolated strains to investigate benthic cyanobacterial diversity in the Guadarrama river (Spain). A total of 17 species were identified that belonged to the genera Aphanocapsa, Pleurocapsa, Chroococcus, Chamaesiphon, Cyanobium, Pseudan‐abaena, Leptolyngbya, Phormidium, Nostoc, and Tolypothrix. Phenotypic features were associated with the results of 16S rRNA gene sequencing, complementing existing morphological and genetic databases. A decrease in the cyanobacterial diversity was observed along a pollution gradient in the river. Water quality differed among the sampling sites, and variation in nutrient content was the principal difference among locations. These characteristics were closely associated with an upstream‐downstream eutrophic gradient. Canonical correspondence analysis distinguished three groups of species with respect to the eutrophication gradient. The first group (Tolypothrix cf. tenuis, Nostoc punctiforme, Nostoc piscinale, Chamaesiphon investiens, Chroococcus minor, Leptolyngbya nostocorum, and Leptolyngbya tenuis) was characteristic of waters with low levels of nutrients. The second group (Cyanobium sp., Chamaesiphon polymorphus, Leptolyngbya boryana, Phormidium autumnale, Phormidium sp., and Aphanocapsa cf. rivularis) was characteristic of polluted waters, its members appearing mainly in great abundance under eutrophic‐hypertrophic conditions. The third group of species (Pseudanabaena catenata, Aphanocapsa muscicola, and Nostoc carneum) was present at upstream and downstream sites.
A Pitfall of Unsupervised Pre-Training

The point of this paper is to question typical assumptions in deep learning and suggest alternatives. A particular contribution is to prove that even if a Stacked Convolutional Auto-Encoder is good at reconstructing pictures, it is not necessarily good at discriminating their classes. When using Auto-Encoders, intuitively one assumes that features which are good for reconstruction will also lead to high classification accuracy. Indeed, it became research practice and is a suggested strategy by introductory books. However, we prove that this is not always the case. We thoroughly investigate the quality of features produced by Stacked Convolutional Auto-Encoders when trained to reconstruct their input. In particular, we analyze the relation between the reconstruction and classification capabilities of the network, if we were to use the same features for both tasks. Experimental results suggest that in fact, there is no correlation between the reconstruction score and the quality of features for a classification task. This means, more formally, that the sub-dimension representation space learned from the Stacked Convolutional Auto-Encoder (while being trained for input reconstruction) is not necessarily better separable than the initial input space. Furthermore, we show that the reconstruction error is not a good metric to assess the quality of features, because it is biased by the decoder quality. We do not question the usefulness of pre-training, but we conclude that aiming for the lowest reconstruction error is not necessarily a good idea if afterwards one performs a classification task.
ESTIMATING CORN YIELD IN THE UNITED STATES WITH MODIS EVI AND MACHINE LEARNING METHODS

Abstract. Satellite remote sensing is commonly used to monitor crop yield in wide areas. Because many parameters are necessary for crop yield estimation, modelling the relationships between parameters and crop yield is generally complicated. Several methodologies using machine learning have been proposed to solve this issue, but the accuracy of county-level estimation remains to be improved. In addition, estimating county-level crop yield across an entire country has not yet been achieved. In this study, we applied a deep neural network (DNN) to estimate corn yield. We evaluated the estimation accuracy of the DNN model by comparing it with other models trained by different machine learning algorithms. We also prepared two time-series datasets differing in duration and confirmed the feature extraction performance of models by inputting each dataset. As a result, the DNN estimated county-level corn yield for the entire area of the United States with a determination coefficient (R2) of 0.780 and a root mean square error (RMSE) of 18.2 bushels/acre. In addition, our results showed that estimation models that were trained by a neural network extracted features from the input data better than an existing machine learning algorithm.
Antibodies to Cryptococcus neoformans glucuronoxylomannan enhance antifungal activity of murine macrophages

Monoclonal antibodies (MAbs) to the capsular polysaccharide of the pathogenic fungus Cryptococcus neoformans can prolong survival and decrease organ fungal burden in experimental murine cryptococcosis. To investigate the mechanism of antibody-mediated protection, the interaction of C. neoformans and murine macrophage-like J774.16 cells was studied in the presence and absence of MAbs differing in isotype. Immunoglobulin G2a (IgG2a) and IgG2b isotype switch variants were isolated from an IgM hybridoma to complete the IgG subclass set. IgM, IgG1, IgG2a, IgG2b, IgG3, and IgA MAbs were studied for their ability to promote phagocytosis and reduce the number of CFU in C. neoformans and J774.16 cell cocultures. The MAbs in this set had similar if not identical fine specificities and were derived from a single B cell. All isotypes promoted phagocytosis; however, the IgG subclasses were more effective opsonins than IgM or IgA. All isotypes enhanced J774.16 anti-C. neoformans activity in vitro, as measured by a reduction in the number of CFU. The IgG1 MAbs were consistently more active in promoting opsonization and reducing the number of CFU. Addition of IgG1 MAb to C. neoformans and J774.16 cocultures resulted in rapid reduction in the number of CFU, which is consistent with fungal killing. Electron microscopy revealed that MAb-opsonized C. neoformans cells were internalized and appeared damaged. Administration of IgM, IgG1, IgG2a, and IgG2b isotype switch variant MAbs revealed that the IgG2a and IgG2b subclasses were the most and least effective isotypes, respectively, in prolonging survival in an intraperitoneal murine infection model. The results indicate that murine antibody subclasses differ in their ability to enhance macrophage anti-C. neoformans activity and suggest that antibody enhancement of macrophage function is a mechanism by which antibodies modify infection in vivo.
Alexithymia and Suicide Ideation in a Sample of Patients with Binge Eating Disorder

Objective. The goal of this cross-sectional study was to evaluate the relationships between alexithymia and suicide ideation in 80 adult outpatients with a DSM-IV diagnosis of binge eating disorder (BED). Methods. Alexithymia was measured with the 20-item Toronto Alexithymia Scale (TAS-20); suicide ideation was assessed with the Scale of Suicide Ideation (SSI); severity of BED was assessed with the Binge Eating Scale (BES); and depressive and anxiety symptoms were evaluated, respectively, with the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Anxiety Rating Scale (Ham-A). Results. Prevalence of current suicide ideation was 27.5% (n=22) in this sample and 10 subjects (12.5%) had attempted suicide at some time in their lives. Subjects with alexithymia had more significant suicide ideation, a higher prevalence of current suicide ideation, and more previous suicide attempts than those without alexithymia. In a linear regression model, higher MADRS scores and higher scores on the Difficulty in Identifying Feelings/Difficulty in Describing Feelings dimensions of the TAS-20 were associated with increased suicide ideation. Discussion. Suicidal behavior is no less common in BED than in other eating disorders. Individuals with BED may show increased suicide ideation, especially in the presence of alexithymia and depressive symptoms, even if these symptoms are subclinical. The authors also discuss limitations of this study and future research needs. (Journal of Psychiatric Practice 2012;18:5–11)
Can big data improve public policy analysis?

We conduct a systematic review targeting the idea of whether big data can improve public policy analysis. The ideas about the benefits and risks of applying big data technologies on public policy analysis are summarized. Big data can provide accurate, proactive, and participatory policy analysis but at the same time it raises risks in data privacy, data misuse and bias, and inequality. We then examine the detailed implementation of big data in each public policy stage. The experiments or practical applications from the relevant literature demonstrate how exactly big data is used to improve policy analysis. This study will guide governments on adopting big data for public policy analysis.
Multistep brownian dynamics: Application to short wormlike chains

Brownian dynamics simulations of short wormlike chains are carried out using the method of Ermak and McCammon [(1978) J. Chem. Phys. 69, 1352–1360]. Following Hagerman and Zimm [(1981) Biopolymers 20, 1481–1502], the wormlike chain is modeled as a string of beads. In each simulation, the dynamic evolution of an ensemble of 100 randomly generated chains is calculated for a period of from 3 to 200 ns. Two different “experiments,” fluorescence depolarization and dynamic light scattering, were performed in these simulations. Since we are primarily interested in the bending motions and not the torsional motions in this work, we have placed the transition moments along the local symmetry axis of the wormlike chain in the fluorescence depolarization “experiment. ” As predicted by the Barkley and Zimm theory [(1979) J. Chem. Phys. 70, 2991–3008], a considerable amount of rapid bending motion was detected by fluorescence depolarization, though not as much as predicted by theory. We conclude that these differences are primarily due to differences between the model used in the theory and the simulations. The light‐scattering experiment was found to be insensitive to internal motion in the low scattering angle limit.
Comparative proteomic analyses of two Taxus species (Taxus [REPLACEMENT CHARACTER] media and Taxus mairei) reveals variations in the metabolisms associated with paclitaxel and other metabolites

Taxus species are well-known for paclitaxel, which exhibits antitumor activities and is used for treating various cancers. Although most Taxus species are widespread in many areas, few studies have characterized the variation in metabolism among different Taxus species. Using an integrated approach involving 'tandem mass tag' labeling and liquid chromatography-tandem mass spectrometry (HPLC-MS), proteomes of T. media and T. mairei were investigated and 4078 proteins were quantified. Screening and classification of differentially expressed proteins revealed many metabolism-associated proteins. In detail, four enzymes involved in the flavonoid biosynthesis pathway were predominantly expressed in T. mairei. Four enzymes associated with supplying precursors for paclitaxel biosynthesis and three cytochrome P450 taxoid oxygenases were preferentially expressed in T. media compared with T. mairei. Furthermore, variations in taxoid contents between T. media and T. mairei were determined using HPLC-MS analysis. Variations in flavonoid contents between T. media and T. mairei were determined by HPLC analysis. A number of differentially expressed proteins may provide an explanation for the variation in metabolisms of different Taxus species.
Planar Cell Polarity Pathway Regulates Nephrin Endocytosis in Developing Podocytes

Background: The PCP pathway controls many cell processes during development. Results: The PCP pathway induces nephrin endocytosis when cultured podocytes are treated with Wnt5a. Loss of PCP protein Vangl2 decreases nephrin endocytosis. Conclusion: During glomerular development, endocytosis of nephrin is regulated by the PCP pathway. Significance: Implicating the PCP pathway in nephrin endocytosis is important for understanding the complexity of PCP signaling during mammalian development. The noncanonical Wnt/planar cell polarity (PCP) pathway controls a variety of cell behaviors such as polarized protrusive cell activity, directional cell movement, and oriented cell division and is crucial for the normal development of many tissues. Mutations in the PCP genes cause malformation in multiple organs. Recently, the PCP pathway was shown to control endocytosis of PCP and non-PCP proteins necessary for cell shape remodeling and formation of specific junctional protein complexes. During formation of the renal glomerulus, the glomerular capillary becomes enveloped by highly specialized epithelial cells, podocytes, that display unique architecture and are connected via specialized cell-cell junctions (slit diaphragms) that restrict passage of protein into the urine; podocyte differentiation requires active remodeling of cytoskeleton and junctional protein complexes. We report here that in cultured human podocytes, activation of the PCP pathway significantly stimulates endocytosis of the core slit diaphragm protein, nephrin, via a clathrin/β-arrestin-dependent endocytic route. In contrast, depletion of the PCP protein Vangl2 leads to an increase of nephrin at the cell surface; loss of Vangl2 functions in Looptail mice results in disturbed glomerular maturation. We propose that the PCP pathway contributes to podocyte development by regulating nephrin turnover during junctional remodeling as the cells differentiate.
The effect of Knowledge Characteristics in student's performances: An Empirical case study

Knowledge characteristics are the essential step in leveraging knowledge value in the university. Share Document, and contributes knowledge may not be useful without the context provided by experience. This paper focuses on the characteristics of knowledge in applied science private university and its effect on student's performance, which aim to focus in the nature knowledge and the quality of material. Questioner was designed and sent to MIS students in the applied sciences university in order to improve the context of the knowledge and facilitated the knowledge usage in order to improve the student knowledge level. The result lead recommends that the university should understand the knowledge characteristics and the potential techniques that support sharing knowledge. In addition the university should now which type of knowledge can by articulated or which knowledge can be taught to individuals, through training, practices or apprenticeship, in order to improve the student performance. Keywords-codify ability, Explicitness, Availability, Teach ability, student performance.
Estrogen Exhibits a Biphasic Effect on Prostate Tumor Growth through the Estrogen Receptor β-KLF5 Pathway

ABSTRACT Estrogens are effective in the treatment of prostate cancer; however, the effects of estrogens on prostate cancer are enigmatic. In this study, we demonstrated that estrogen (17β-estradiol [E2]) has biphasic effects on prostate tumor growth. A lower dose of E2 increased tumor growth in mouse xenograft models using DU145 and PC-3 human prostate cancer cells, whereas a higher dose significantly decreased tumor growth. We found that anchorage-independent apoptosis in these cells was inhibited by E2 treatment. Similarly, in vivo angiogenesis was suppressed by E2. Interestingly, these effects of E2 were abolished by knockdown of either estrogen receptor β (ERβ) or Krüppel-like zinc finger transcription factor 5 (KLF5). Ιn addition, E2 suppressed KLF5-mediated transcription through ERβ, which inhibits proapoptotic FOXO1 and proangiogenic PDGFA expression. Furthermore, we revealed that a nonagonistic ER ligand GS-1405 inhibited FOXO1 and PDGFA expression through the ERβ-KLF5 pathway and regulated prostate tumor growth without ERβ transactivation. Therefore, these results suggest that E2 biphasically modulates prostate tumor formation by regulating KLF5-dependent transcription through ERβ and provide a new strategy for designing ER modulators, which will be able to regulate prostate cancer progression with minimal adverse effects due to ER transactivation.
O6‐methylguanine‐DNA methyltransferase activity in breast and brain tumors

The DNA repair protein O6‐methylguanine‐DNA methyltransferase (MGMT) is a main determinant of resistance of tumor cells to the cytostatic activity of chemotherapeutic alkylating agents (methylating and chloroethylating nitrosoureas) and is effective in protecting normal cells against genotoxic and carcinogenic effects resulting from DNA alkylation. Therefore, the level of expression of MGMT is significant for the response of both the tumor and the non‐target tissue following application of nitrosoureas in tumor therapy. To determine the expression of MGMT in tumor tissue, we have assayed MGMT activity in 68 breast carcinomas and 38 brain tumors. There was a wide variation of MGMT expression in breast carcinomas ranging from below the level of detection up to 863 fmol/mg protein. About 4% of breast tumors did not display detectable MGMT, 15% had activity lower than 100 fmol/mg protein, and 26% expressed more than 500 fmol/mg. The mean level of expression was 321 fmol/mg. In brain tumors (astrocytoma WHO grade I, II, and III, and glioblastoma WHO grade IV) the MGMT activity was generally lower than in breast tumors, ranging from below the level of detection up to 238 fmol/mg. The mean level of expression was 55 fmol/mg. Five percent of the brain tumors had no detectable MGMT activity. The MGMT repair activity correlated well with the amount of MGMT protein present in tumor samples, as shown by Western‐blot analysis, indicating that loss of MGMT repair activity is due to inability of these tumor cells to synthesize the protein. © 1995 Wiley‐Liss, Inc.
RA and ω-3 PUFA co-treatment activates autophagy in cancer cells

Retinoic acid (RA), is a promising therapeutic agent for the treatment of breast cancer. However, metabolic disorders and drug resistance reduce the efficacy of RA. In this study, we found that RA and ω-3 polyunsaturated fatty acids (ω-3 PUFAs) synergistically induced cell death in vitro and in vivo and autophagy activation. Moreover, RA-induced hypercholesterolemia was completely corrected by ω-3 PUFA supplementation. In addition, we demonstrated that the effects of this combination on the autophagic flux were independent of the two major canonic regulatory complexes controlling autophagic vesicle formation. The treatment activated Gαq-p38 MAPK signaling pathways, which resulted in autophagy of breast cancer cells. Knockdown of Gαq or P38 expression prevented RA and ω-3 PUFAs from inducing autophagy. Data indicated that Gαq-p38activation was mediated by the co-activation of GPR40 and RARα in lipid rafts, rather than by the activation of GPR120, RARβ, or RARγ. The results of this study suggest that hyperlipidemic drug side effects may be ameliorated by the administration of ω-3 PUFAs. Thus, the therapeutic indexes of the corresponding drugs may be increased.