Miracle-dz/UniFAR-FTUs huggingface dataset:
Stock Liquidity and the Pricing of Earnings: A Comparison of China's Floating and Nonfloating Shares

The reform aimed at converting nonfloating shares to floating shares in China provides a setting in which shares are subject to different levels of liquidity constraints. We show that the severity of these constraints is inversely related to the extent to which earnings information is reflected in share prices. Specifically, before the reform, transfer prices of nonfloating shares reflect much less earnings information than the market prices of floating shares. After the reform, however, transfer prices of nonfloating shares reflect more earnings information, although the weights are still less than those found in market prices. Thus, China's unique setting shows that share liquidity affects the way earnings are priced in stock.
Complex Object Recognition Using a Biologically Plausible Neural Model

The complex object recognition tasks are still one big problem in neurocomputing today. This paper presents a method of detecting and recognizing complex objects, in cluttered environment, in a purely feed-forward way, being able to account for ultra-rapid visual categorization. We used a retinotopic architecture of simple spiking neurons with different types of receptive fields, organized in a hierarchical fashion similar to the mammal visual path. Fast shunting inhibition had been implemented using a rank-order coding similar to that described by S. Thorpe. The main advantage of the neural model proposed is that it accepts a very small number of training examples (4-7) being able to generalize very well. The model has been used to detect faces and automobiles in complex intensity images. Key-words: Scale independence; Rank order coding; Feed-forward; Receptive field; Neurocomputing.
Robust Multimodal Medical Image Elastic Registration Using RPM and Mean Shift

Landmark matching is widely applied in multimodal medical image registration. In this paper, a novel landmarks corresponding estimation combining robust point matching (RPM) and mean shift algorithm is proposed. At first, corners of images are detected to be the landmarks sets. Robust point matching algorithm is used to estimate the coarse transformation parameters between two landmark sets. Next, mean shift iterations are adopted to search the exact corresponding point positions in the two images based on the edge structure feature. Moreover, mutual information between two local regions and the topology relations between landmarks are analyzed to eliminate mis-matching landmarks. Finally, the deformed image is transformed by compact support thin-plate spline interpolation. Experiments show that the precision in location of corresponding landmarks is satisfied. The proposed technique is feasible and robust shown in the experiments of various multi-modal medical images registration.
A simple programming model for new-generation hardware

A large abstraction gap is emerging between new highly parallel hardware architectures and the von-Neumann model that underpins most software. Better compiler technologies or new programming models are needed to bridge this gap. In this paper, we propose a software architecture for an implementation of a compiler mapping a simple functional programming language to highly parallel FPGA hardware.
Responses to disruptive strategic innovation

When upstarts overthrow an industry's business model with disruptive strategic innovations (not the same as disruptive technological innovations), many established companies hurry to imitate. But others worry about playing two games at once. They contend that adopting the new way may damage the existing business because attackers utilize strategies that are not only different from but also in conflict with the industry leaders'. Two London Business School authors explain when to use which option or one of several new ones. Research into established companies' responses suggests five current approaches: focusing on one's own game and investing in it; ignoring the new strategy when it is not a threat; disrupting the disruptive innovation; playing two games; and scaling up the disruption. How a company responds depends on two main factors: motivation and ability. The company's motivation is determined by the rate at which the innovation is growing, how threatening it is to the main business and how strategically the new business is related to the existing one. The ability of an established company to respond is determined by its skills, resources, time, and the nature and size of the conflicts between the traditional and the new business. But, the authors say, just appreciating that the new ways of competing are not inherently superior is half the battle.
Job Classification in Cloud Computing: The Classification Effects on Energy Efficiency

One of the recent and major challenges in cloud computing is to enhance the energy efficiency in cloud data centers. Such enhancements can be done by improving the resource allocation and management algorithms. In this paper, a model that identifies common patterns for the jobs submitted to the cloud is proposed. This model is able to predict the type of the job submitted, and accordingly, the set of users' jobs is classified into four subsets. Each subset contains jobs that have similar requirements. In addition to the jobs' common pattern and requirements, the users' history is considered in the jobs' type prediction model. The goal of job classification is to find a way to propose useful strategy that helps improve energy efficiency. Following the process of jobs' classification, the best fit virtual machine is allocated to each job. Then, the virtual machines are placed to the physical machines according to a novel strategy called Mixed Type Placement strategy. The core idea of the proposed strategy is to place virtual machines of the jobs of different types in the same physical machine whenever possible, based on Knapsack Problem. This is because different types of jobs do not intensively use the same compute or storage resources in the physical machine. This strategy reduces the number of active physical machines which leads to major reduction in the total energy consumption in the data center. A simulation of the results shows that the presented strategy outperforms both Genetic Algorithm and Round Robin from an energy efficiency perspective.
Red Algae Lose Key Mitochondrial Genes in Response to Becoming Parasitic

Red algal parasites are unusual because the vast majority of them parasitize species with which they share a recent common ancestor. This strategy has earned them the name “adelphoparasites,” from the Greek, adelpho, meaning “kin. ” Intracellular adelphoparasites are very rare in nature, yet have independently evolved hundreds of times among the floridiophyte red algae. Much is known about the life history and infection cycle of these parasites but nearly nothing in known about their genomes. We sequenced the mitochondrial genomes of the free-living Gracilariopsis andersonii and its closely related parasite Gracilariophila oryzoides to determine what effect a parasitic lifestyle has on the genomes of red algal parasites. Whereas the parasite genome is similar to the host in many ways, the genes encoding essential proteins ATP8 and SDHC are pseudogenes in the parasite. The mitochondrial genome of parasite from a different class of red algae, Plocamiocolax puvinata, has lost the atp8 gene entirely, indicating that this gene is no longer critical in red algal parasite mitochondria.
Wavelet-based Texture Analysis

In this paper, texture analysis based on wavelet transformations is elaborated. The paper is meant as a practical guideline through some aspects of a wavelet-based texture analysis task. The following aspects of the problem are discussed: discrete and continuous wavelet decompositions, texture features for grey-level textures, extensions to colour texture and rotation-invariant features, and classi cation, including supervised image classi cation and unsupervised texture segmentation tasks. For these di erent aspects, a theoretical and practical survey is given, experiments and real-world applications of the literature are reviewed and some small-scale demonstration experiments are included.
The case for determinism in database systems

Replication is a widely used method for achieving high availability in database systems. Due to the nondeterminism inherent in traditional concurrency control schemes, however, special care must be taken to ensure that replicas don't diverge. Log shipping, eager commit protocols, and lazy synchronization protocols are well-understood methods for safely replicating databases, but each comes with its own cost in availability, performance, or consistency. In this paper, we propose a distributed database system which combines a simple deadlock avoidance technique with concurrency control schemes that guarantee equivalence to a predetermined serial ordering of transactions. This effectively removes all nondeterminism from typical OLTP workloads, allowing active replication with no synchronization overhead whatsoever. Further, our system eliminates the requirement for two-phase commit for any kind of distributed transaction, even across multiple nodes within the same replica. By eschewing deadlock detection and two-phase commit, our system under many workloads outperforms traditional systems that allow nondeterministic transaction reordering.
The Routes to Chaos in the Bitcoins Market

Рынок биткоинов является примером сложной системы, не имеющей устойчивого равновесия. Пользователи биткоинов делятся на две большие категории: 1) стремящиеся только к приросту капитала;2) функциональные пользователи, которые используют валюту, чтобы сэкономить на трансакционных издержках. Я определяю два пути, которые могут привести к хаосу на рынке биткоинов. Если присутствуют только искатели прироста капитала, то маршрут к хаосу идет через логистическое отображение. Еслиобе категории пользователей присутствуют, то маршрут к хаосу возможен с помощью отсроченного логистического отображения Эно. Вывод: чтобы не допустить хаос на рынке биткоинов, валютным биржам следует разрешить конвертацию биткоинов в доллары и наоборот, только если имеется связанная сделка покупки или продажи товаров или услуг, или если биткоины только что получены. Такое регулирование предотвращает хаос путем уменьшения воздействия на стоимость виртуальной валюты со стороны пользователей, ищущих прироста капитала. I argue that the bitcoins market is an example of a complex system without a stable equilibrium. The users of bitcoins fall into two broad categories: 1) Capital gain seekers: who have no functional use for the currency apart from an expectation of capital gains; 2) Functional users: who use the currency to save on transaction costs as it provides a less costly medium of exchange over traditional fiat currencies. I assume thateach category consists of mean-variance optimizers, and specify simple evolutionary dynamics for each category. I identify two simple routes to chaos in the bitcoins market. If only capital gain seekers are present, then one route to chaos is via the logistic map. If both categories of users matter then a possible route to chaos is via the delay logistic-Henon map. A policy recommendation follows: in order to pre-empt chaos in the bitcoins market, currency exchanges should be allowed to convert bitcoins into dollars and vice versa if and only if there is an associated transaction involving buying and selling of goods or services or if the bitcoins are freshly mined.Such a regulation pre-empts chaos by reducing the impact of capital gain seekers on the virtual currency’s value.
Issues and Dilemmas in Early Childhood Teacher Education.

EDRS PRICE MF01/PCO2 Plus Postage. DESCRIPTORS *Course Content; Criteria; Curriculum Development; Early Childhood Education; *Educational Needs; Educational Objectives; *Educational Practices; Higher Education; Preservice Teacher Education; Program Content; *Relevance (Education); *Student Evaluation; Teacher Educators; Teacher Responsibility; *Teacher Student Relationship IDENTIFIERS *Dilemmas of Schooling
A unifying probability measure for logic-based similarity conditions on uncertain relational data

A Boolean logic-based evaluation of a database query returns true on match and false on mismatch. Unfortunately, there are many application scenarios where such an evaluation is not possible or does not adequately meet user expectations about vague and uncertain conditions. Consequently, there is a need for incorporating impreciseness and proximity into a logic-based query language. A probabilistic approach known from Information Retrieval expresses the fulfilling of a condition by a probability of relevance. Besides relevance probabilities used in IR probabilistic databases have been established as a challenging research field. In this work we lay the theoretical basis for the combination of relevance probabilities and probabilistic databases evaluated by a unifying probability measure.
Collaborative studies on the development of national reference standards for potency determination of H7N9 influenza vaccine

The outbreak of human infections of a novel avian influenza virus A (H7N9) prompted the development of the vaccines against this virus. Like all types of influenza vaccines, H7N9 vaccine must be tested for its potency prior to being used in humans. However, the unavailability of international reference reagents for the potency determination of H7N9 vaccines substantially hinders the progress in vaccine development. To facilitate clinical development, we enlisted 5 participants in a collaborative study to develop critical reagents used in Single Radial Immunodiffusion (SRID), the currently acceptable assay for potency determination of influenza vaccine. Specifically, the hemagglutinin (HA) content of one vaccine bulk for influenza A (H7N9), herein designated as Primary Liquid Standard (PLS), was determined by SDS-PAGE. In addition, the freeze-dried antigen references derived from PLS were prepared to enhance the stability for long term storage. The final HA content of lyophilized antigen references were calibrated against PLS by SRID assay in a collaborative study. Importantly, application of these national reference standards to potency analyses greatly facilitated the development of H7N9 vaccines in China.
Towards Generic Camera Self-Calibration

We propose a generic approach for the self-calibration of general central cameras, i.e. cameras with a single optical center but otherwise unconstrained projection function. First we study the possibility of generic self-calibration for restricted motion scenarios such as pure rotation and pure translation. Then we propose an approach which relies on specific camera motions: pure rotations and pure translations. Combined with a dense image matching, this enables to reconstruct the projection rays for all pixels of a camera, i.e. to calibrate it. We have verified our algorithm through simulations and real experiments.
Folate intake, markers of folate status and oral clefts: is the evidence converging?

BACKGROUND The ability of folic acid in the periconceptional period to prevent the occurrence of neural tube defects has stimulated tremendous interest in its effects on other health outcomes. Its possible effect on oral clefts has generated considerable debate. The purpose of this systematic review and meta-analysis was to assemble evidence on the role of folate in the aetiology of cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO). METHODS Medline, PubMed, Embase, Science Citation Index and the HuGE Published Literature Database were searched to February 2007 for articles related to oral clefts and multivitamin use, dietary folate, folic acid fortification, biochemical markers of folate status and polymorphisms in 5,10-methylenetetrahydrofolate reductase (MTHFR) and other genes involved in folate metabolism. Random effects meta-analysis was conducted when appropriate. RESULTS Maternal multivitamin use was inversely associated with CL/P [odds ratio (OR) 0.75, 95% CI 0.65-0.88, based on 5717 cases and 59 784 controls] but to a lesser extent CPO (OR 0.88, 95% CI 0.76-1.01, 2586 cases and 59 684 controls). The volume of evidence on dietary folate, fortification and biochemical and genetic measures of folate status is substantially less; in aggregate, the evidence suggests that no association exists but there is substantial heterogeneity between studies. CONCLUSIONS The evidence is not converging and there is no strong evidence for an association between oral clefts and folic acid intake alone. Multivitamin use in early pregnancy, however, may protect against oral clefts, especially CL/P although this association may be confounded by other lifestyle factors associated with multivitamin use.
Improved CABAC design in H.264/AVC for lossless depth map coding

The depth map represents three-dimensional (3D) data and is used for depth image-based rendering (DIBR) to synthesize virtual views. Since the quality of synthesized virtual views highly depends on the quality of the depth map, we encode the depth map by lossless coding mode. However, context-based adaptive binary arithmetic coding (CABAC) for the H.264/AVC standard does not guarantee the best coding performance for lossless depth map coding because CABAC was originally designed for lossy coding. In this paper, we propose an improved coding method of CABAC for lossless depth map coding considering the statistical properties of residual data from lossless depth map coding. Experimental results show that the proposed CABAC method provides approximately 4.3% bit saving, compared to the original CABAC in H.264/AVC.
An Approach of Ontology Based Knowledge Base Construction for Chinese K12 Education

The increasing learning materials on the Internet bring the learners a flood of educational resources, along with many difficulties in the learning process. It becomes much harder for the learners to find the required resources and get the right knowledge from these unsorted resources. To give the learners a better learning experience and improve the efficiency of the education based on the Internet, an approach proposed to solve these problems by constructing an ontology based knowledge base for Chinese K12 education with high accuracy and efficiency. Since domain ontology is beneficial to knowledge representation, storage and sharing, and knowledge base has a high performance on knowledge retrieval, learners who use the applications built on the knowledge base will benefit in the learning process.
Multimodal circular filtering using Fourier series

Recursive filtering with multimodal likelihoods and transition densities on periodic manifolds is, despite the compact domain, still an open problem. We propose a novel filter for the circular case that performs well compared to other state-of-the-art filters adopted from linear domains. The filter uses a limited number of Fourier coefficients of the square root of the density. This representation is preserved throughout filter and prediction steps and allows obtaining a valid density at any point in time. Additionally, analytic formulae for calculating Fourier coefficients of the square root of some common circular densities are provided. In our evaluation, we show that this new filter performs well in both unimodal and multimodal scenarios while requiring only a reasonable number of coefficients.
Working memory abilities in children with autism spectrum disorder

The aim of the present study was to investigate possible differences on working memory abilities between children with Autism spectrum disorder and typical children. The potential facilitating effect of verbal mediation on working memory was investigated measuring children’s ability to use language-based encoding and rehearsal processes to enhance working memory. Method: Participants were divided into two groups: a group of 26 children diagnosed with Autism spectrum disorder (16 boys and 10 girls) and to a group of 25 typical controls (17 boys and 8 girls) matched on nonverbal intelligence. Examination of working memory was based on non-verbal variants of the non-spatial, self-ordered pointing test (SOPT) devised by Petrides and Milner (1982). Both the Verbal Span Test and the Self-ordered tests were performed to the participants. Results: The resulting profile on memory abilities in children with autism was characterized by relatively poor memory for complex verbal and visual test. The different pattern of memory performance between the two groups indicates that the more complex the task and the information being processed, the more taxed the resources of the memory system become. Discussion: The results provide useful information to take into consideration when designing interventions for children with Autism spectrum disorder in clinical and educational settings.
RepComment: A Fair Comment-Sentiment Representation System

Most Online Social Networks (OSNs) allow registered members to leave comments on particular entities. An entity can either be a person, a location, or a product. These comments have already become an important reference for many people in the daily life. However, a popular entity usually receives an extensive number of comments and it has become infeasible for users to read through all of them. In this demonstration, we propose Rep Comment, a fair comment-sentiment representation system based on a novel probability sampling model that can choose a small set of comments (samples) that are most resemble and representative for the original comment set. The proposed approximation algorithm significantly reduces the computation cost of the sampling problem while keeping relatively high accuracy.
The SimMed experience: medical education on interactive tabletops

We present SimMed, a novel tool for medical education that allows medical students to diagnose and treat a simulated patient in real-time. The students assume the roles of doctors, collaborating as they interact with the patient. To achieve immersion and support complex interactions for gaining procedural knowledge, the hybrid user interface combines elements of real-time Virtual Reality (VR) with multitouch input. On the one hand, SimMed features a simulated, life-sized patient that is rendered and reacts in real-time. On the other hand, a more conventional touch input interface allows access to a large variety of medical procedures and tools.
ICM: An efficient data association for SLAM in stochastic mapping

In this paper, iterative classification matching (ICM), a novel practical data association method, is proposed. ICM is an iterative approach to solve the data association problem which reconsiders the established observation-feature pairing and applies the quaternion approach to yield a least squares matching vector. The map features which are not associated with any observations are updated then by the obtained least squares matching vector to weaken the influence of the inaccurate vehicle pose estimation. Finally, the updated feature set and the unassociated observations are taken as a group of new inputs to perform the iteration again. The iteration is terminated until the discrepancy in mean square error falls below a preset threshold specifying the desired precision of the matching. Results of simulation experiments show that the proposed ICM method is an efficient solution to data association. Unlike ICNN (individual compatibility nearest neighbor), ICM can provide a robust solution in both simulated and real outdoor environments. Simultaneously, the computational cost of the proposed ICM algorithm is much lower than JCBB (joint compatibility branch and bound).