Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon partitioning in N2 fixing Medicago sativa plants exposed to different CO2 and temperature conditions.

Many of the studies analysing the CO2 effect on plant development have been conducted in optimal growth conditions. Furthermore, although some of those studies suggest that legumes might show a steady productivity increase with rising CO2, the role of nodule activity on the plant responsiveness to predicted atmospheric CO2 enhancement is not well understood. In this study, C (metabolism and allocation) and N (nodule activity) interaction between the plant and the bacterial symbiont during the photosynthetic acclimation of N2-fixing alfalfa (Medicago sativa L. cv. Aragón) plants exposed to elevated CO2 and temperature conditions was analysed. The plants were grown in temperature gradient greenhouses (TGG) where, in the case of elevated CO2 treatments, the isotopic 13C/12C composition (δ13C) inside the TGG was modified. Compared with the corresponding temperature treatment, exposure to 700 μmol mol-1 CO2 enhanced dry mass (DM) of plants in elevated temperature treatments (26%), whereas no significant effect was detected in ambient temperature treatments. The δ13C data revealed that although all the carbon corresponding to leaf total organic matter (TOM) came from newly assimilated C, plants exposed to elevated CO2 did not develop strong sink activity (especially in ambient temperature conditions). Leaf carbohydrate build-up induced reduction in the Rubisco (E.C. 4.1.1.39) carboxylation capacity of plants. Despite this reduction in Rubisco content, plants exposed to elevated CO2 conditions maintained (at ambient temperature) or increased (at elevated temperature) photosynthetic rates (measured at growth conditions) by increasing N use efficiency. The larger C sink strength of nodules in plants grown at elevated CO2 and temperature conditions did not contribute towards overcoming photosynthetic acclimation. Further, the inhibitory effect of CO2 on nodule total activity was caused by a large depletion in total soluble protein (TSP) of nodules. Depletion of leaf N demand, together with the reduction in nodule carbohydrate availability (as reflected by the nodule starch concentration), negatively affected the nodule TSP content and enzymatic activity.
Discovery News: A Generic Framework for Financial News Recommendation

In the financial services industry, it is crucial for analysts to constantly monitor and stay informed on the latest developments of their portfolio of companies. This ensures that analysts are up-to-date in their analysis and provide highly credible and timely insights. Currently, analysts receive news alerts through manually created news alert subscriptions that are often noisy and difficult to manage. The manual review process is time-consuming and error-prone. We demonstrate Discovery News, a framework for an automated news recommender system for financial analysis at S&P's Global Ratings. This system includes the automated ingestion, relevancy, clustering, and ranking of news. The proposed framework is adaptable to any form of input news data and can seamlessly integrate with other data used for analysis like financial data.
Embedding Convolution Neural Network-Based Defect Finder for Deployed Vision Inspector in Manufacturing Company Frontec

In collaboration with Frontec, which produces parts such as bolts and nuts for the automobile industry, Kyung Hee University and Benple Inc. develop and deploy AI system for automatic quality inspection of weld nuts. Various constraints to consider exist in adopting AI for the factory, such as response time and limited computing resources available. Our convolutional neural network (CNN) system using large-scale images must classify weld nuts within 0.2 seconds with accuracy over 95%. We designed Circular Hough Transform based preprocessing and an adjusted VGG (Visual Geometry Group) model. The system showed accuracy over 99% and response time of about 0.14 sec. We use TCP / IP protocol to communicate the embedded classification system with an existing vision inspector using LabVIEW. We suggest ways to develop and embed a deep learning framework in an existing manufacturing environment without a hardware change.
Structuring Two-Medium Dialog for Learning Language and Other Things

OVERVIEW: Naturalistic two-medium communication with a computational system, using both language and interactive graphics (Cohen, 1991; Maier, 1993; McKeown, 1993), is an important practical complement to studies that involve only language, only graphics and/or only people. Integrative two-medium work should build on insights and findings in the one-medium disciplines of graphical manipulative interfaces (e.g., Hutchins et al., 1986; Sullivan and Tyler, 1991) and natural language discourse (e.g., Grosz and Sidner, 1986; Litman and Allen, 1987; Hovy, 1988; Lambert and Carberry, 1991; Paris, 1991).
Homeostatic plasticity triggered by rod photoreceptor degenerative disease is associated with maintenance of sensitive night vision

Neuronal plasticity of the inner retina has been observed in response to photoreceptor degeneration. Typically, this phenomenon has been considered maladaptive and may preclude vision restoration in the blind. However, several recent studies utilizing triggered photoreceptor ablation have shown adaptive responses in bipolar cell dendrites expected to support normal vision. Whether such homeostatic plasticity occurs during progressive photoreceptor degenerative disease to help maintain normal visual behavior is unknown. We addressed these issues in an established mouse model of Retinitis Pigmentosa caused by the P23H mutation in rhodopsin. We show robust modulation of the retinal transcriptomic network reminiscent of the neurodevelopmental state as well as potentiation of rod – rod bipolar cell signaling following rod photoreceptor degeneration. Additionally, we found highly sensitive night vision in P23H mice even when more than half of the rod photoreceptors were lost. The results implicate retinal adaptation leading to persistent visual function during photoreceptor degenerative disease.
TSPAN1 promotes human pancreatic cancer cells proliferation by modulating CDK1 via Akt

Background To explore the potential therapeutic target to treat pancreatic cancers, Tspan1 was detected in human pancreatic cancer tissue and human pancreatic ductal adenocarcinoma cells and functional role of Tspan1 on proliferation was explored and the mechanism was investigated. Materials and Methods Tspan1 in PCC tissue and PDAC cell lines was measured by qRT-PCR and Western blot. Tspan1 was knock-downed and over-expressed in cells via transfection with Tspan1-siRNA and pLNCX-TSPAN1-cDNA, cell survival, proliferation and cell cycle were measured with MTT, Alamar blue and Flow Cytometry assay. The mRNA and protein expression were assessed by qRT-PCR and Western blotting. The expression of PI3K, Akt and p-Akt were detected, and CDK1 siRNA and specific inhibitor of Akt were used to explore the mechanism of TSPAN1 promoting PDAC cells proliferation. Results Tspan1 expression in PCC tissue and PDAC cells was increased. Transfection of siRNA targeting Tspan1 in BxPC3 and PNAC-1 cells obviously decreased cell proliferation and down-regulated CDK1 expression. Consistently, both cell proliferation and CDK1 expression in BxPC3 and PNAC-1 cells were up-regulated with pLNCX-TSPAN1-cDNA transfection. Cell cycle analysis showed that after knockdown of Tspan1 the G2/M phase ratio was increased to cause mitosis arrest, and TSPAN1 overexpression caused cell cycle transition from G2 to M phase to promote cell proliferation. And these were dependent on the modulation of CDK1 expression via Akt. Conclusion Tspan1 up-regulates CDK1 expression via activating Akt to promote human PCC cell proliferation and silencing of Tspan1 may be a potential therapeutic target to treat pancreatic cancers.
Method in Ecology: Strategies for Conservation

1. Introduction: what ecology can't do 2. Ecological concepts are problematic 3. Ecological theory is problematic 4. Ecological science is value laden 5. What ecology can do 6. Ecology and a new account of rationality 7. Objections: rationality in ecology 8. A case study: the Florida panther 9. Policy aspects of the Florida panther case 10. Conclusions References Index.
TermEval 2020: TALN-LS2N System for Automatic Term Extraction

Automatic terminology extraction is a notoriously difficult task aiming to ease effort demanded to manually identify terms in domain-specific corpora by automatically providing a ranked list of candidate terms. The main ways that addressed this task can be ranged in four main categories: (i) rule-based approaches, (ii) feature-based approaches, (iii) context-based approaches, and (iv) hybrid approaches. For this first TermEval shared task, we explore a feature-based approach, and a deep neural network multitask approach -BERT- that we fine-tune for term extraction. We show that BERT models (RoBERTa for English and CamemBERT for French) outperform other systems for French and English languages.
An extracellular protein regulates patched-related/DAF-6-mediated sensory compartment formation in C. elegans

Coordination of neurite extension with surrounding glia development is critical for neuronal function, but the underlying molecular mechanisms remain poorly understood. Through a genome-wide mutagenesis screen in C. elegans, we identified dyf-4 and daf-6 as two mutants sharing similar defects in dendrite extension. DAF-6 encodes a glia-specific patched-related membrane protein that plays vital roles in glial morphogenesis. We cloned dyf-4 and found that DYF-4 encodes a glia-secreted extracellular protein. Intriguingly, DYF-4 colocalizes with DAF-6 along the glial channel. Further investigations revealed that DYF-4 directly interacts with DAF-6 and regulates its proper membrane localization. Notably, reported glial suppressors of daf-6 could also restore dendrite elongation and ciliogenesis in both dyf-4 and daf-6 mutants. Collectively, our data suggest that secreted DYF-4 likely acts as a novel ligand/regulator for the patched-related receptor DAF-6 which promotes the proper formation of the glial channel and indirectly affects neurite extension and ciliogenesis.
Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank

The human leukocyte antigen (HLA) region is one of the most disease-associated regions of the human genome, yet even well-studied alleles in the HLA region have unknown impact on disease. Here, we study the effect of 156 HLA alleles on 677 binary phenotypes for 337,138 individuals in the UK Biobank. We assess HLA allele associations and subsequently use Bayesian Model Averaging for conditional analysis, a) replicating 88 known associations between HLA alleles and binary disease phenotypes such as cancer, and b) discovering 90 novel associations to phenotypes such as skin and reproductive tract cancers and to other phenotypes not previously associated with the HLA region (e.g. anemias and acne). We find several non-additive effects, suggesting a more complex landscape of disease-modifying effects throughout the region. Finally, we discover associations between homozygous HLA allele burden and several cancer and other phenotypes, suggesting that peptide presentation spectra as coded for by the HLA region are important in determining disease risk. Our results demonstrate the HLA region’s complexity and richness while underscoring its clinical relevance.
A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders

The importance of cell type-specific gene expression in disease-relevant tissues is increasingly recognized in genetic studies of complex diseases. However, the vast majority of gene expression studies are conducted on bulk tissues, necessitating computational approaches to infer biological insights on cell type-specific contribution to diseases. Several computational methods are available for cell type deconvolution (that is, inference of cellular composition) from bulk RNA-Seq data, but cannot impute cell type-specific expression profiles. We hypothesize that with external prior information such as single cell RNA-seq (scRNA-seq) and population-wide expression profiles, it can be a computationally tractable and identifiable to estimate both cellular composition and cell type-specific expression from bulk RNA-Seq data. Here we introduce CellR, which addresses cross-individual gene expression variations by employing genome-wide tissue-wise expression signatures from GTEx to adjust the weights of cell-specific gene markers. It then transforms the deconvolution problem into a linear programming model while taking into account inter/intra cellular correlations, and uses a multi-variate stochastic search algorithm to estimate the expression level of each gene in each cell type. Extensive analyses on several complex diseases such as schizophrenia, Alzheimer’s disease, Huntington’s disease, and type 2 diabetes validated efficiency of CellR, while revealing how specific cell types contribute to different diseases. We conducted numerical simulations on human cerebellum to generate pseudo-bulk RNA-seq data and demonstrated its efficiency in inferring cell-specific expression profiles. Moreover, we inferred cell-specific expression levels from bulk RNA-seq data on schizophrenia and computed differentially expressed genes within certain cell types. Using predicted gene expression profile on excitatory neurons, we were able to reproduce our recently published findings on TCF4 being a master regulator in schizophrenia and showed how this gene and its targets are enriched in excitatory neurons. In summary, CellR compares favorably (both accuracy and stability of inference) against competing approaches on inferring cellular composition from bulk RNA-seq data, but also allows direct imputation of cell type-specific gene expression, opening new doors to re-analyze gene expression data on bulk tissues in complex diseases.
Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering

This paper proposes a new idea that uses Wikipedia categories as answer types and defines candidate sets inside Wikipedia. The focus of a given question is searched in the hierarchy of Wikipedia main pages. Our searching strategy combines head-noun matching and synonym matching provided in semantic resources. The set of answer candidates is determined by the entry hierarchy in Wikipedia and the hyponymy hierarchy in WordNet. The experimental results show that the approach can find candidate sets in a smaller size but achieve better performance especially for ARTIFACT and ORGANIZATION types, where the performance is better than state-of-the-art Chinese factoid QA systems.
Human Genetic Disorders Associated with Genome Instability, Premature Aging and Cancer Predisposition

Our genetic material is constantly damaged by internal sources such as reactive oxygen species and external sources such as ionizing radiation and sunlight. However, we seldom notice these injuries because our cells possess elegant DNA surveillance networks that serve to maintain cellular homeostasis. These networks are complex signal transduction pathways that coordinate cell cycle checkpoints and DNA repair processes to eliminate DNA damage, as well as invoking pathways such as sustained growth arrest (i.e., accelerated senescence) and apoptotic cell death to eliminate injured cells from the proliferating population. The p53 tumor suppressor protein and its downstream effector p21 are key regulators of these various responses. Failure of cells to properly activate p53/p21-mediated events following genotoxic stress may lead to the development of genomic instability and the emergence of malignant cells which exhibit stem cell-like properties. It is therefore not surprising that defects in major players of the DNA surveillance networks are the underlying cause for numerous debilitating human genetic disorders that are characterized by genomic instability, premature aging, and cancer proneness. In this article, we first provide an update on the role of the p53 signaling pathway in determining the fate of human cells following exposure to DNA-damaging agents. We next review the clinical and laboratory features of the most extensively studied human genome instability disorders including xeroderma pigmentosum, Cockayne syndrome, ataxia telangiectasia, and Li-Fraumeni syndrome, and discuss the current knowledge on the biological consequences of deregulated p53 signaling in cells derived from patients with such disorders.
Question Analysis and Answer Passage Retrieval for Opinion Question Answering Systems

Question answering systems provide an elegant way for people to access an underlying knowledge base. However, people are interested in not only factual questions, but also opinions. This paper deals with question analysis and answer passage retrieval in opinion QA systems. For question analysis, six opinion question types are defined. A two-layered framework utilizing two question type classifiers is proposed. Algorithms for these two classifiers are described. The performance achieves 87.8% in general question classification and 92.5% in opinion question classification. The question focus is detected to form a query for the information retrieval system and the question polarity is detected to retain relevant sentences which have the same polarity as the question. For answer passage retrieval, three components are introduced. Relevant sentences retrieved are further identified as to whether the focus (Focus Detection) is in a scope of opinion (Opinion Scope Identification) or not, and, if yes, whether the polarity of the scope and the polarity of the question (Polarity Detection) match with each other. The best model achieves an F-measure of 40.59% by adopting partial match for relevance detection at the level of meaningful unit. With relevance issues removed, the F-measure of the best model boosts up to 84.96%.
The Chemistry of Antigenic Components Isolated From Glomerular Basement Membrane

Fractions of varying molecular size and chemical composition were isolated from glomerular basement membrane (GBM) and characterized inimunochemically. Reduction and alkylation in 8 M urea results in a fraction (GRAU) with an amino acid and carbohydrate composition similar to the whole membrane. Antiserum to this fraction (anti-GRAU) gives two precipitin lines upon immunodiffusion. Reduction and alkylation in the absence of 8 M urea results in a fraction with significantly less hydroxyproline and hydroxylysine which gives two precipitin lines of identity with GRAU when reacted against anti-GRAU. One of these precipitin lines is given by a fraction which can be obtained either after extraction with 8 M urea or as the undigested residue after treatment of GBM with collagenase. This fraction has a molecular weight of over 200,000, has low amounts of hydroxyproline and hydroxylysine and a glucose to galactose ratio of 0.25. The second precipitin line is given by a smallmolecular weight glycoprotein which is r.
57 Phytotoxic Effect of Waterhyacinth Water Extract and Decayed Residues

Two experiments were conducted to study the effect of waterhacinth water extract and decayed residue on radish germination and seedlign growth. Waterhyacinth plant parts were either extracted at three ratios with distilled water or allowed to decay in a water and 2, 4-D dimethylamine salt solution. Extracts of high ratios of leaf and rhizome contained water soluble substances that inhibited radish germination and seedling growth. With increasing plant material ratio, germination inhibition and seedling length reduction increased in leaf, rhizome and whole plant extracts. Decayed residue of the untreated plant caused a slight adverse effect on germination. The decayed rhizome residue showed relatively higher phytotoxicity on seedling growth. Treatment with 2, 4-D caused severe stunting to the seedlings during the period of decay, except in the root and whole plant treatments in which the herbicidal effect disappeared completely and partially by 8 weeks after incubation, respectively. Seedling dry weight was generally reduced by the decayed residue especially in the herbicide treatment, but that effect declined with time.
Management of freshwater systems: The interactive roles of science, politics and management, and the public

Although the global water crisis has been well recognized by both international and national agencies, little progress is being made in the management of this most precious of global resources. All fresh waters are connected with interflow from one water compartment to another. The rates of retention, or overturn, of water in each compartment, namely the atmosphere, rivers, lakes and groundwater, are the major determinants of both freshwater system classification and management strategies. Management implies manipulation to achieve some defined beneficial condition relevant to societal requirements. Three social groups interact directly in the management function, including the scientific, public and political communities. It is only when these three entities function in harmony that comprehensive management of natural systems can truly occur. Political concern over water management and, indeed, all environmental management, is driven by policies largely derived from the influence exerted by many groups and organizations with vested interests in advancing their own purposes or agendas. Once policies are established and implemented by legislation and the bureaucracy, management possibilities and public funding then become focused, and the flexibility to deal with other issues might be largely lost. The pursuit of knowledge through scientific research is a major victim of policy changes and short-term changes in the priorities of funding allocation. It is now clear that the scientific community and the public need a greater awareness of the manner in which the system functions as a whole, and how they can ensure that their collective opinions are used to greater effect in the determination of public policy and consequent management of freshwater systems.
Performance Limit and Coding Schemes for Resistive Random-Access Memory Channels

Resistive random-access memory (ReRAM) is a promising candidate for the next generation non-volatile memory technology due to its simple read/write operations and high storage density. However, its crossbar array structure causes a severe interference effect known as the “sneak path. ” In this paper, we propose channel coding techniques that can mitigate both the sneak-path interference and the channel noise. The main challenge is that the sneak-path interference is data-dependent, and also correlated within a memory array, and hence the conventional error correction coding scheme will be inadequate. In this work, we propose an across-array coding strategy that assigns a codeword to multiple independent memory arrays, and exploit a real-time channel estimation scheme to estimate the instantaneous status of the ReRAM channel. Since the coded bits from different arrays experience independent channels, a “diversity” gain can be obtained during decoding, and when the codeword is adequately distributed over different memory arrays, the code actually performs as that over an uncorrelated channel. By performing decoding based on the scheme of treating-interference-as-noise (TIN), the ReRAM channel over different memory arrays is equivalent to a block varying channel we defined, for which we propose both the capacity bounds and a coding scheme. The proposed coding scheme consists of a serial concatenation of an optimized error correction code with a data shaper, which enables the ReRAM system to achieve a near capacity limit storage efficiency.