Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Distinction and Commonality across Multiple Domains Using Generative Model for Text Classification

The distribution difference among multiple domains has been exploited for cross-domain text categorization in recent years. Along this line, we show two new observations in this study. First, the data distribution difference is often due to the fact that different domains use different index words to express the same concept. Second, the association between the conceptual feature and the document class can be stable across domains. These two observations actually indicate the distinction and commonality across domains. Inspired by the above observations, we propose a generative statistical model, named Collaborative Dual-PLSA (CD-PLSA), to simultaneously capture both the domain distinction and commonality among multiple domains. Different from Probabilistic Latent Semantic Analysis (PLSA) with only one latent variable, the proposed model has two latent factors y and z, corresponding to word concept and document class, respectively. The shared commonality intertwines with the distinctions over multiple domains, and is also used as the bridge for knowledge transformation. An Expectation Maximization (EM) algorithm is developed to solve the CD-PLSA model, and further its distributed version is exploited to avoid uploading all the raw data to a centralized location and help to mitigate privacy concerns. After the training phase with all the data from multiple domains we propose to refine the immediate outputs using only the corresponding local data. In summary, we propose a two-phase method for cross-domain text classification, the first phase for collaborative training with all the data, and the second step for local refinement. Finally, we conduct extensive experiments over hundreds of classification tasks with multiple source domains and multiple target domains to validate the superiority of the proposed method over existing state-of-the-art methods of supervised and transfer learning. It is noted to mention that as shown by the experimental results CD-PLSA for the collaborative training is more tolerant of distribution differences, and the local refinement also gains significant improvement in terms of classification accuracy.
APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO EVALUATE WELD DEFECTS OF NUCLEAR COMPONENTS

Artificial neural networks (ANNs) are computational representations based on the biological neural architecture of the brain. ANNs have been successfully applied to a wide range of engineering and scientific applications, such as signal, image processing and data analysis. Although Radiographic testing is widely used for welding defects, it is unsuccessful in identifying some welding defects because of the nature of image formation and quality. Neoteric algorithms have been used for the purpose of weld defects identifications in radiographic images to replace the expert knowledge. The application of artificial neural networks in noise detection of radiographic films is used. Radial Basis (RB) and learning vector quantization (LVQ) were applied. The method shows good performance in weld defects recognition and classification problems.
Power-aware test pattern generation for improved concurrency at the core level

A functional automatic test pattern generation (ATPG) for embedded core testing is presented that meets power constraints requirements and time to market consideration. Quick turnaround time for the ATPG is obtained by utilizing compact sets of test vectors. Use of test functions for the embedded cores control the switching activity so that the generated test vectors meet constraints on power dissipation. Concurrency is guaranteed with the use of test functions (as opposed to patterns) and appropriate I/O pin TAM allocations during a compact ATPG process that benefit from pre-existing test vectors. Low power dissipation is also facilitated by test functions and is driven by a metric that requires that a very small portion of each core net-list is available
Autonomous chain network formation by multi-robot rescue system with ad hoc networking

The autonomous chain network formation by multi-robot rescue system is investigated. Chain networks connecting a base station and rescue robots are essential to reconnoiter distant spaces in disaster areas. The chains must be formed to assure communications among them and must be transformed if the target of exploration changes. These formations must be executed by autonomous movements of robots from reliable viewpoints in rescue operations. As the basis of their movements, we adopt autonomous classification of robots into search robots and relay robots. They act according to the behavior algorithms of each class of robot to form chain network threading the path to the distant spaces. The rule of the classification and the behavior algorithm refer forwarding table of each robot constructed for ad hoc networking. The results of simulations show that chain networks are formed and transformed by rescue robots appropriately for their reconnaissance to distant spaces even though three spaces exist beyond different corridors stemming from the safety zone where base station is established.
Intravascular tissue factor initiates coagulation via circulating microvesicles and platelets

Although tissue factor (TF), the principial initiator of physiological coagulation and pathological thrombosis, has recently been proposed to be present in human blood, the functional significance and location of the intravascular TF is unknown. In the plasma portion of blood, we found TF to be mainly associated with circulating microvesicles. By cell sorting with the specific marker CD42b, platelet‐derived microvesicles were identified as a major location of the plasma TF. This was confirmed by the presence of full‐length TF in microvesicles acutely shedded from the activated platelets. TF was observed to be stored in the α‐granules and the open canalicular system of resting platelets and to be exposed on the cell surface after platelet activation. Functional competence of the blood‐based TF was enabled when the microvesicles and platelets adhered to neutrophils, as mediated by P‐selectin and neutrophil counterreceptor (PSGL‐1, CD18 integrins) interactions. Moreover, neutrophil‐secreted oxygen radical species supported the intravascular TF activity. The pools of platelet and microvesicle TF contributed additively and to a comparable extent to the overall blood TF activity, indicating a substantial participation of the microvesicle TF. Our results introduce a new concept of TF‐mediated coagulation crucially dependent on TF associated with microvesicles and activated platelets, which principally enables the entire coagulation system to proceed on a restricted cell surface.
Selection and Evaluation of Potential Reference Genes for Gene Expression Analysis in the Brown Planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) Using Reverse-Transcription Quantitative PCR

The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects.
Essays on insider trading

In this paper, we focus on the patent application process at the United States Patent and Trademark Office (USPTO) to examine whether corporate insiders trade on superior information. The patent application process provides a unique research setting for at least two reasons: First, while prior research examining whether insiders trade on superior information often assumes that insiders are in the possession of private information, we can identify the exact point in time when insiders receive private information regarding the grant decision of pending patent applications from the USPTO. Second, the implementation of the American Inventors Protection Act (AIPA) in 2000 causes exogenous variation in the level of information asymmetry between insiders and outsiders regarding pending patent applications since it mandates publication of pending patent applications within 18 months of the patent application date regardless of whether a grant decision is already reached and communicated. Using detailed hand-collected data on high-impact patents granted to US companies, we find that insider purchasing activity increases significantly following the private communication between the USPTO and the firm but only if the private communication was not preceded by mandatory publication of the pending patent application. This chapter is based on a working paper that is coauthored with Katrin Hussinger and Frank Moers.
Valuing Global Public Goods: A European Delphi Stated Preference Survey of Population Willingness to Pay for Amazon Rainforest Preservation

The Amazon Rainforest is a global public good. As such, and given that 15 percent of the original Amazon forest area has already been lost, households worldwide might be willing to pay to reduce or avoid additional losses. A full elicitation of global preferences for valuing preservation of the current forest, using stated-preference population surveys, would be costly and time consuming. Alternatively, this paper uses a Delphi stated-preference technique in which 48 European environmental valuation experts were asked to provide"best guesses"on the possible outcomes of population surveys in their own countries and Europe as a whole. The expert judgments indicate willingness to pay in Europe for preserving the current Amazon Rainforest of about 28 Euro per household per year on average; a slightly lower value is inferred for a plan that allows a 10 percent future reduction from the current rainforest area. The income elasticity of experts'stated willingness to pay with respect to per-capita income in their own countries is in the range 0.5-0.8. These findings indicate that Delphi studies might be used more widely as a tool for global benefit transfer.
Traveling-salesman type competition and simultaneous move search algorithm

In this paper, we study a traveling-salesman type competition in which two salesmen independently visit n cities and compete with each other for the number of visiting cities. Similar competitions can be widely found in the real world such as in selling competitions and in the competitive gathering of scrap materials. The competition is modeled as a game such that players travel around various objects distributed in a given area and compete with each other in collecting the objects. In this game model, players move simultaneously, that is, not alternately. We present a novel scheduling algorithm suitable for the game model in which a move toward an object along the shortest path is taken as the basic move, and the move is stopped halfway when the opponent has the advantage. In the algorithm, the moves of the players can be dealt with quasi-alternately. However, a player can make several consecutive moves, and a move already made can be aborted. A position evaluation method based on the concept of territory is also presented. A simulation program is developed and competitions are held between computers or between a computer and a human being. It is confirmed that the algorithm and the position evaluation method can be effectively applied to the game model.
Structured Perturbations Part II: Componentwise Distances

In the second part of this paper we study condition numbers with respect to componentwise perturbations in the input data for linear systems and for matrix inversion, and the distance to the nearest singular matrix. The structures under investigation are linear structures, namely symmetric, persymmetric, skewsymmetric, symmetric Toeplitz, general Toeplitz, circulant, Hankel, and persymmetric Hankel structures. We give various formulas and estimations for the condition numbers. For all structures mentioned except circulant structures we give explicit examples of linear systems $A_{\varepsilon}x=b$ with parameterized matrix $A_{\varepsilon}$ such that the unstructured componentwise condition number is ${\mathcal O}(\varepsilon^{-1})$ and the structured componentwise condition number is ${\mathcal O}(1)$. This is true for the important case of componentwise relative perturbations in the matrix and in the right-hand side. We also prove corresponding estimations for circulant structures. Moreover, bounds for the condition number of matrix inversion are given. Finally, we give for all structures mentioned above explicit examples of parameterized (structured) matrices $A_{\varepsilon}$ such that the (componentwise) condition number of matrix inversion is ${\mathcal O}(\varepsilon^{-1})$, but the componentwise distance to the nearest singular matrix is ${\mathcal O}(1)$. This is true for componentwise relative perturbations. It shows that, unlike the normwise case, there is no reciprocal proportionality between the componentwise condition number and the distance to the nearest singular matrix.
The Optimality and Controllability of Monetary Policy Through Delegation with Consistent Targets

This paper uses two game-theory models, where monetary policy is first ineffective and then effective, to illustrate a delegation scheme that makes consistent policy optimal and controllable. The delegation scheme produces the minimization of both the social and the central bank loss functions. Minimizing the social loss function generates optimality conditions. Minimizing the central bank loss function produces controllability conditions. Optimality conditions depend on specific models, and controllability conditions do not. We propose a concept of consistent targets, which refer to the targets that satisfy both optimality and controllability conditions. Consistent policy proves optimal and controllable in both example models when the government delegates consistent targets to the central bank.
High Hospitalization Rates in Survivors of Childhood Cancer: A Longitudinal Follow-Up Study Using Medical Record Linkage

Hospitalization rates over time of childhood cancer survivors (CCS) provide insight into the burden of unfavorable health conditions on CCS and health care resources. The objective of our study was to examine trends in hospitalizations of CCS and risk factors in comparison with the general population. We performed a medical record linkage study of a cohort of 1564 ≥five-year CCS with national registers. We obtained a random sample of the general population matched on year of birth, gender and calendar year per CCS retrieved. We quantified and compared hospitalization rates of CCS and reference persons from 1995 until 2005, and we analyzed risk factors for hospitalization within the CCS cohort with multivariable Poisson models. We retrieved hospitalization information from 1382 CCS and 25583 reference persons. The overall relative hospitalization rate (RHR) was 2.2 (95%CI:1.9–2.5) for CCS compared to reference persons. CCS with central nervous system and solid tumors had highest RHRs. Hospitalization rates in CCS were increased compared to reference persons up to at least 30 years after primary diagnosis, with highest rates 5–10 and 20–30 years after primary cancer. RHRs were highest for hospitalizations due to neoplasms (10.7; 95%CI:7.1–16.3) and endocrine/nutritional/metabolic disorders (7.3; 95%CI:4.6–11.7). Female gender (P<0.001), radiotherapy to head and/or neck (P<0.001) or thorax and/or abdomen (P = 0.03) and surgery (P = 0.01) were associated with higher hospitalization rates in CCS. In conclusion, CCS have increased hospitalization rates compared to the general population, up to at least 30 years after primary cancer treatment. These findings imply a high and long-term burden of unfavorable health conditions after childhood cancer on survivors and health care resources.
A monopolist supplier and learning effects in technology adoption

The aim of this paper is to study the consequences of the introdution of supply side and learning efects in the process of technological adoption. Explicit consideration of supply side makes endogenous the price path, whereas the occurring of learning enables a better understanding of the coordination process. The model describes an open-loop two stage dynamic game of imperfect information:the players are a monopolist offering a cost reducing process innovation and two identical firms who, observing the innovation prices, are to simultaneously decide when to adopt it, in presence of learning by using and spillover. Open-loop equilibrium in symmetric adoption is the solution for incremental innovations, whereas for drastic innovations the resulting equilibrium might be one of diffusion or simultaneous adoption, both early and late, according to Y, the probability that adopters will choose to adopt early. Independently of the particular equilibrium wich will take place, drastic innovations's first period prices are always higher than incremental ones.
1 A Neural Model of Figure-Ground Organization

Psychophysical studies suggest that figure-ground organization is a largely autonomous process that guides—and thus precedes—allocation of attention and object recognition. The discovery of border ownership representation in single neurons of early visual cortex has confirmed this view. Recent theoretical studies have demonstrated that border ownership assignment can be modeled as a process of self-organization by lateral interactions within V2 cortex. However, the mechanism proposed relies on propagation of signals through horizontal fibers, which would result in increasing delays of the border ownership signal with increasing size of the visual stimulus, in contradiction with experimental findings. It also remains unclear how the resulting border ownership representation would interact with attention mechanisms to guide further processing. Here we present a model of border ownership coding based on dedicated neural circuits for contour grouping that produce border ownership assignment and also provide handles for mechanisms of selective attention. The results are consistent with neurophysiological and psychophysical findings. The model makes predictions about the hypothetical grouping circuits and the role of feedback between cortical areas.
Context-aware Data Mining using Ontologies

Data mining, which aims at extracting interesting information from large collections of data, has been widely used as an active decision making tool. Real-world applications of data mining require a dynamic and resilient model that is aware of a wide variety of diverse and unpredictable contexts. Contexts consist of circumstantial aspects of the user and domain that may affect the data mining process. The underlying motivation is mining datasets in the presence of context factors may improve performance and efficacy of data mining as identifying the factors, which are not easily detectable with typical data mining techniques. This paper proposes a context-aware data mining framework, where context will (1) be represented in ontology, (2) be automatically captured during data mining process (3) allow the adaptive behavior to carry over to powerful data mining. We have shown that the different behaviors and functionalities of our context-aware data mining framework dynamically generate information in dynamic, uncertain, and distributed medical applications.
Balancing configurability and efficiency in network support tools

New applications require dynamic configuration capability. A protocol kernel is a middleware application that glues a user defined set of protocols, allowing them to cooperate. One difficult in building protocol kernels is to balance the flexibility of adding and removing protocols with the efficiency of the mechanisms that support them. The paper presents an novel attempt to balance these requirements, extending recent results in this area. The proposed system, called Apia has the capability of dynamically select the protocols to be used, on a per message basis while allowing run-time reconfiguration of protocol stacks.
China Pear Value Chain: Implication for Smallholders

The objective of this paper is to describe different types of value chain, to capture value added activities of each chain, to discuss the organizational and institutional link in each value chain and its implications for the role of small farmers. We focus on two counties in Hebei and Zhejiang of China. Taking pear for example, analysis of value chain is conducted using data of representative samples of pear value chain. For each chain, value added activities, cost composition, profit distribution, organizational and institutional linkages are illustrated, and corresponding conclusions are indicated. After a systematic analysis of organizational and institutional linkage and value adding activities of every chain as well as cost-benefit analysis of smallholders, we found that: value-added of each value chain are different, smallholders hardly benefit from value chains of Hebei case. Farmer cooperatives are helpful for smallholders in terms of costs reducing and value adding. Influence of modern retailers such as supermarket in term of tradition fruit growers is limited in our cases. Downstream stage took most profit of value adding. Comprehensive supermarket is less competitive than professional fruit supermarket and even small fruit store in terms of procurement costs and operating costs. Taking household labor cost into account, net profit and labor compensation of large scale household are higher than that of middle or small scale farmers.