Miracle-dz/UniFAR-FTUs huggingface dataset:
Building Chinese field association knowledge base from Wikipedia

Field association FA terms are a limited set of discriminating terms that offer humans the knowledge to identify fields exiting in the document text. Field association knowledge base is composed of FA terms and their potential hierarchical relationship of the fields they belong to. The main purpose of this research is building Chinese FA knowledge base. After this, the new knowledge base is tested through a system which can imitate the process whereby humans recognise the fields by looking at a few special terms. In doing so, a novel approach makes use of the structured knowledge in Chinese Wikipedia. A totally new Chinese FA knowledge base is built including 115,696 FA terms. The resulting FA knowledge from this knowledge base is applied to text categorisation. The average accuracies, 97.7% and 89%, are both higher than values obtained by SVM.
Automatic generation of analysis class diagrams from use case specifications

In object oriented software development, the analysis modeling is concerned with the task of identifying problem level objects along with the relationships between them from software requirements. The software requirements are usually written in some natural language, and the analysis modeling is normally performed by experienced human analysts. The huge gap between the software requirements which are unstructured texts and analysis models which are usually structured UML diagrams, along with human slip-ups inevitably makes the transformation process error prone. The automation of this process can help in reducing the errors in the transformation. In this paper we propose a tool supported approach for automated transformation of use case specifications documented in English language into analysis class diagrams. The approach works in four steps. It first takes the textual specification of a use case as input, and then using a natural language parser generates type dependencies and parts of speech tags for each sentence in the specification. Then, it identifies the sentence structure of each sentence using a set of comprehensive sentence structure rules. Next, it applies a set of transformation rules on the type dependencies and parts of speech tags of the sentences to discover the problem level objects and the relationships between them. Finally, it generates and visualizes the analysis class diagram. We conducted a controlled experiment to compare the correctness, completeness and redundancy of the analysis class diagrams generated by our approach with those generated by the existing automated approaches. The results showed that the analysis class diagrams generated by our approach were more correct, more complete, and less redundant than those generated by the other approaches.
From process modeling to domain modeling

The hype on software process and software reuse as the capitalization on software as a valuable asset is encountering more and more appreciation. This paper presents an experience in modeling and extracting valuable process assets to build a framework in a small Italian firms specialized in telecommunications personalized solutions.The company has been modeled at first by means of interviews and then analyzing the components in terms of fours main entities.Then, domain analysis was performed. The results of the two phases gave birth to a set of organizational patterns of reuse in the firm that lead to a general organizational framework. The framework can then be refined in a more specific meta-pattern definition or a design framework.
ANATOXIN-A(S): NATURAL ORGANOPHOSPHORUS ANTICHOLINESTERASE AGENT

Anatoxin-a(s) is a guanidinemethyl phosphate ester isolated from the freshwater cyanobacterium (bluegreen algae) Anabaena flos-aquae strain NRC 525–17. Previous work has shown anatoxin-a(s) to be a potent irreversible inhibitor of electric eel acetylcholinesterase (AChE, EC 3.1.1.7). Anatoxin-a(s) has been shown to be an active site-directed inhibitor of AChE, which is resistant to reactivation by oximes because of the enzyme-oxime adduct formation. In vivo pretreatment with physostigmine and high concentrations of pyridine 2-aldoxime methochloride (2-PAM) were the only effective antagonists against a lethal dose of anatoxin-a(s). Anatoxin-a(s) is very toxic and it is produced by cyanobacteria during its blooms. Purified toxin has an LD50 (i.p) of approximately 20-50 μg/kg body weight in mice. Toxicoses associated with cholinesterase-inhibiting anatoxin-a(s) have been observed in humans, animals, birds and fish. Anatoxina(s) induces clinical signs of hypercholinergic preponderance, such as salivation, lacrimation, urinary incontinence, defecation, convulsion, fasciculation, and respiratory arrest.
Query-driven module discovery in microarray data

MOTIVATION Existing (bi)clustering methods for microarray data analysis often do not answer the specific questions of interest to a biologist. Such specific questions could be derived from other information sources, including expert prior knowledge. More specifically, given a set of seed genes which are believed to have a common function, we would like to recruit genes with similar expression profiles as the seed genes in a significant subset of experimental conditions. RESULTS We introduce QDB, a novel Bayesian query-driven biclustering framework in which the prior distributions allow introducing knowledge from a set of seed genes (query) to guide the pattern search. In two well-known yeast compendia, we grow highly functionally enriched biclusters from small sets of seed genes using a resolution sweep approach. In addition, relevant conditions are identified and modularity of the biclusters is demonstrated, including the discovery of overlapping modules. Finally, our method deals with missing values naturally, performs well on artificial data from a recent biclustering benchmark study and has a number of conceptual advantages when compared to existing approaches for focused module search.
Forest nutrient and carbon pools at Walker Branch watershed: changes during a 21-year period

A 21-yr perspective on changes in nutrient and C pools on undisturbed upland forest sites is provided. Plots originally representing four cover types have been sampled three times. On each plot, forest biomass, forest floor, and soil, to a depth of 60 cm, were measured, sampled, and analyzed for Ca, Mg, C, N, and P. Exchangeable soil Ca and Mg have declined in most soils. Despite the low exchangeable Ca, cumulative sequestration in the biomass has exceeded the soil pool, suggesting that soil supplies below 60 cm are satisfying the biomass demand. Extractable soil P also declined, with means ranging from 4.2 to 18.2 kg ha{sup {minus}1}, as a result of reductions in the mineral soil and Oi horizon. The loss of extractable soil P exceeded biomass sequestration in all but one plot, suggesting abiotic soil processes as the removal mechanism. Soil C and N were either stable, although highly variable, or declined, which was unexpected in these undisturbed sites. The net C balance of these sites was controlled by aboveground sequestration, which offset changes in the soil and forest floor. Soil parent material and geomorphic setting strongly influenced the changes in soil properties during the 21-yr period, reflecting themore » importance of those factors in assessing soil nutrient and C cycles over that of forest cover type. The variability encountered in the periodic soil measurements highlights the difficulty in detecting temporal changes in soil chemical properties. « less
Influence of spacial and temporal laser beam characteristics on thin-film ablation

Solar irradiation is a vast and plentiful source of energy. The use of photovoltaic (PV) devices to convert solar energy directly to electrical energy is an elegant way of sustainable power generation which can be distributed or in large PV plants based on the need. Solar cells are the small building blocks of photovoltaics and when connected together they form PV modules. Thin film solar cells require significantly less energy and raw materials to be produced, as compared to the dominant Si wafer technologies. CIGS thin film solar cells are considered to be the most promising thin film alternative due to its proven high efficiency. Most thin film PV modules utilise monolithic integration, whereby thin film patterning steps are included between film deposition steps, to create interconnection of individual cells within the layered structure. The state of the art is that CIGS thin film modules are made using one laser patterning step (P1) and two mechanical patterning steps (P2 and P3). Here we present work which successfully demonstrates the replacement of mechanical patterning by laser patterning methods. The use of laser ablation promises such advantages as increased active cell area and reduced maintenance and downtime required for regular replacement of mechanical tools. The laser tool can also be used to transform CIGS into a conducting compound along a patterned line. We have shown that this process can be performed after all semiconductor layers are deposited using a technique we call laser micro-welding. By performing patterning at the end of the process flow P2 and P3 patterning could be performed simultaneously. Such solutions will further reduce manufacturing times and may offer increased control of semiconductor interfaces. While showing promising performance on par with reference processes there are still open questions of importance for these novel techniques, particularly that of long term stability. Thin film modules are inherently sensitive to moisture and require reliable encapsulation. Before the techniques introduced here can be seen industrially they must have achieved proven stability. In this work we present a proof of existence of stable micro-welded interconnections.
Leaching Behavior of Salt Wastes Conditioned with Sodalite Blended with Two Different Glass Powders

Two different glass powders (a commercially available glass frit and a borosilicate glass) have been used as blending agents for sodalite, an aluminosilicate mineral able to condition chloride salt wastes from pyrometallurgical processes. The synthesis of the mineral phase has been made through a process recently proposed by Idaho National Laboratory in USA, starting from a homogeneous powder of nepheline, chloride salts and glass. The mix, put into an alumina crucible, was introduced in a furnace inside an argon-atmosphere glove-box. The furnace temperature was then raised to 925 C, where it was kept for 7 hours. Leach tests under static conditions, according to ASTM C1285-02, have then been carried out on the final waste forms at room temperature (23 C) and in an oven at 90 C. SEM investigations have also been made before and after leach tests, in order to check the status of the powders. In particular the effect of the leaching process on the surface of the sodalite grains at 90 C from 30 to 150 days has been evidenced. The results obtained in the present study have been usefully compared to those from a similar test on a sodalite added with a glass frit by Idaho National Laboratory. Financial support from the Nuclear Fission Safety Program of the European Union is gratefully acknowledged (project ACSEPT, contract FP7-CP-2007-211 267).
Locally Linear Models on Face Appearance Manifolds with Application to Dual-Subspace Based Classification

Recently, there has been a flurry of research on face recognition based on multiple images or shots from either a video sequence or an image set. This paper is also such an attempt in multiple-shot face recognition. Specifically, we propose a novel nonparametric method that first extracts discriminating local models via clustering. We apply a hierarchical distance-based clustering procedure according to some distance measure on the appearance manifold to cluster similar face images together. Based on the local models extracted, we then construct the intrapersonal and extrapersonal subspaces. Given a new test image, the angle between the projections of the image onto the two subspaces is used as a distance measure for classification. Since a test example contains multiple face images in multiple-shot face recognition, the final classification combines the classification decisions of all individual test images via a majority voting scheme. We compare our method empirically with some previous methods based on a database of video sequences of human faces, showing that out method significantly outperforms other methods.
Thought suppression and treatment outcome in late-life depression

This study examined severity of depression, age of onset, and thought suppression as predictors of treatment outcome. Measures were taken pre-treatment, post-treatment, and at six-month follow-up in 34 depressed older adults receiving the treatment protocol described in Lynch, Morse, Mendelson & Robins (Dialectical behavior therapy for depressed older adults, American Journal of Geriatric Psychiatry, 11, 33–45, 2003). Severity and chronicity of depression and higher levels of thought suppression were associated with higher depressive symptoms six months after treatment. Findings are consistent with research suggesting that severity and chronicity of depression predict poor clinical outcome. In addition, these results provide preliminary evidence that the tendency to cope with unwanted thoughts by deliberate attempts to not experience such thoughts may be an important pre-treatment predictor of outcome among depressed older adults. Larger studies are needed to explore whether thought suppression mediates long-term recovery from depression.
The Role of Compensatory Mutations in the Emergence of Drug Resistance

Pathogens that evolve resistance to drugs usually have reduced fitness. However, mutations that largely compensate for this reduction in fitness often arise. We investigate how these compensatory mutations affect population-wide resistance emergence as a function of drug treatment. Using a model of gonorrhea transmission dynamics, we obtain generally applicable, qualitative results that show how compensatory mutations lead to more likely and faster resistance emergence. We further show that resistance emergence depends on the level of drug use in a strongly nonlinear fashion. We also discuss what data need to be obtained to allow future quantitative predictions of resistance emergence.
Framework for personalized multimedia summarization

We extend and validate methods of personalization to the domain of automatically created multimedia summaries. Based on a previously performed user study of 59 people we derived a mapping of personality profile information to preferred multimedia features. This article describes our summarization algorithm. We define constraints for automatic summary generation. Summaries should consist of contiguous segments of full shots, with duration proportional to the log of video length, selected by an objective function of total "importance" of features, with heuristic rules for deciding the "best" combination of length and importance. We validated the summaries with a user study of 32 people. They were asked to answer a shortened series of personality queries. Using this current user profile, together with the earlier genre-specific reduced mapping and with automatically derived features, we automatically generated two summaries for each video: one optimally matched, and one matched to the "opposite" personality. Each user evaluated both summaries on a preference scale for four each of: news, talk show, and music videos. From a statistical analysis we find statistically significant evidence of the effectiveness of personalization on news and music videos, with no evidence of user subpopulations. We conclude for these genres that our claim, of a universal mapping from certain measured personality traits to the computable creation of preferred multimedia summaries, is supported.
Sparse Embedding-based Domain Adaptation for Object Recognition | NIST

Domain adaptation algorithms aim at handling the shift between source and target domains. A classifier is trained on images from the source domain; and the classifier recognizes objects in images from the target domain. In this paper, we present a joint subspace and dictionary learning framework for domain adaptation. Our approach simultaneously exploits the low-dimensional structures in two domains and the sparsity of features in the projected subspace. Specifically, we first learn domain-specific subspaces from the source and target domains respectively that can decrease the mismatch between source and target domains. Then we project features from each domain onto their domainspecific subspaces. From the projected features, a common domain-invariant dictionary for both domains is learned. Our approach handles domain shift caused by different classes of features; e.g., SURF and SIFT. In addition, the features can have different dimensions. Our framework applies to both cross-domain adaptation (cross-DA) and multiple source domain adaptation (multi-DA). Our experimental results on the benchmark dataset show that our algorithm outperforms the state of the art. Suppose that we have P domains, and the first P − 1 domains are source domains while the last domain is the target domain. Let Xπ ∈ Rdπ×Nπ denote the feature representation of Nπ samples in the π-th domain, where each column in Xπ denotes a sample and dπ is the feature dimension in the π-th domain. Our goal is to jointly learn domain-specific subspaces Wπ ∈ Rm×dπ for each domain and a common domain-invariant dictionary D ∈ Rm×J . The objective function is formulated as follows:
Towards Dynamic Word Sense Discrimination with Random Indexing

Most distributional models of word similarity represent a word type by a single vector of contextual features, even though, words commonly have more than one sense. The multiple senses can be captured by employing several vectors per word in a multi-prototype distributional model, prototypes that can be obtained by first constructing all the context vectors for the word and then clustering similar vectors to create sense vectors. Storing and clustering context vectors can be expensive though. As an alternative, we introduce Multi-Sense Random Indexing, which performs on-the-fly (incremental) clustering. To evaluate the method, a number of measures for word similarity are proposed, both contextual and non-contextual, including new measures based on optimal alignment of word senses. Experimental results on the task of predicting semantic textual similarity do, however, not show a systematic difference between singleprototype and multi-prototype models.
A single-planar integrated self-heterodyne receiver with a built-in beam-steerable array antenna for 60-GHz-band video transmission systems

This paper presents a compact self-heterodyne receiver with a 24-element beam-steerable array antenna using varactor diodes for 60-GHz-band video transmission systems. An MMIC down-converter is integrated with the antenna substrate. The radiation elements of the antenna, are fed in series by a circuit based on microstrip-to-slotline transitions and slotline-to-microstrip transitions. A feed network of the symmetric structure is developed by fully using the in-phase and anti-phase power dividing techniques. In the feed network, variable phase shifters using varactor diodes are inserted to steer the beam direction, and impedance transformers are introduced to increase the steering angle. We fabricated the antenna and measured the antenna characteristics. Furthermore, an MMIC down-converter was mounted on the antenna substrate for a 60-GHz-band self-heterodyne video transmission receiver. The reception performances were evaluated by using a BS (Broadcasting-satellite) digital signal. The antenna gain is about 15 dBi, and the bandwidth is more than 2 GHz. Experimental results show that the antenna is capable of about 16-degree beam steering at 60 GHz. Moreover, in the self-heterodyne receiver, the C/N and BER (Bit Error Rate) patterns can be steered within about 16 degrees by changing the control voltage.
Engineering of actinomycetes using CRISPR/Cas9 technologies

1 The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kogle Alle 6, 2970 Hørsholm, Denmark; 2 Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Center for Systems and Synthetic Biotechnology, Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Republic of Korea
The Organization of Work and Innovative Performance A comparison of the EU-15

It is widely recognised that while expenditures on research and development are important inputs to successful innovation, these are not the only inputs. Further, rather than viewing innovation as a linear process, recent work on innovation in business and economics literatures characterises it as a complex and interactive process involving multiple feedbacks. These considerations imply that relevant indicators for innovation need to do more than capture material inputs such as R&D expenditures and human capital inputs. The main contribution of this paper is to develop EU-wide aggregate measures that are used to explore at the level of national innovation systems the relation between innovation and the organisation of work. In order to construct these aggregate measures we make use of micro data from two European surveys: the third European survey of Working Conditions and the third Community Innovation Survey (CIS-3). Although our data can only show correlations rather than causality they support the view that how firms innovate is linked to the way work is organised to promote learning and problem-solving.
Local features in biomedical image clusters extracted with independent component analysis

A neural network model for the identification and classification of malign and benign skin lesions from ALA-induced fluorescence images is presented. A self-organizing feature map or generative topographic mapping is used to cluster images patches according to their inherent local features, which then can be extracted with ICA. These components are used to distinguish skin cancer from benign lesions achieving an average classification rate of 70% so far.
Dual-Channel Cosine Function Based ITD Estimation for Robust Speech Separation

In speech separation tasks, many separation methods have the limitation that the microphones are closely spaced, which means that these methods are unprevailing for phase wrap-around. In this paper, we present a novel speech separation scheme by using two microphones that does not have this restriction. The technique utilizes the estimation of interaural time difference (ITD) statistics and binary time-frequency mask for the separation of mixed speech sources. The novelties of the paper consist in: (1) the extended application of delay-and-sum beamforming (DSB) and cosine function for ITD calculation; and (2) the clarification of the connection between ideal binary mask and DSB amplitude ratio. Our objective quality evaluation experiments demonstrate the effectiveness of the proposed method.