Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement Errors of Expected-Return Proxies and the Implied Cost of Capital

Despite their popularity as proxies of expected returns, the implied cost of capital's (ICC) measurement error properties are relatively unknown. Through an in-depth analysis of a popular implementation of ICCs by Gebhardt, Lee, and Swaminathan (2001) (GLS), I show that ICC measurement errors can be not only nonrandom and persistent, but can also be associated with firms' risk or growth characteristics, implying that ICC regressions are likely confounded by spurious correlations. Moreover, I document that biases in GLS' measurement errors are driven not only by analysts' systematic forecast errors but also by functional form assumptions, so that correcting for the former - a primary focus of the ICC literature - is insufficient by itself. From these findings, I argue that the choice between ICCs and realized returns involves a tradeoff between bias and efficiency, and suggest that realized returns should be used in conjunction with ICCs to make more robust inferences about expected returns.
Forward-backward Machine Transliteration between English and Chinese Based on Combined CRFs

The paper proposes a forward-backward transliteration system between English and Chinese for the shared task of NEWS2011. Combined recognizers based on Conditional Random Fields (CRF) are applied to transliterating between source and target languages. Huge amounts of features and long training time are the motivations for decomposing the task into several recognizers. To prepare the training data, segmentation and alignment are carried out in terms of not only syllables and single Chinese characters, as was the case previously, but also phoneme strings and corresponding character strings. For transliterating from English to Chinese, our combined system achieved Accuracy in Top-1 0.312, compared with the best performance in NEWS2011, which was 0.348. For backward transliteration, our system achieved top-1 accuracy 0.167, which is better than others in NEWS2011.
Can contesting orientations predict grittier, more self-controlled athletes?

Abstract Grit and self-control are highly desired qualities of character in the sport arena. This two-study investigation used a new theoretical approach, contesting theory, to examine whether contesting orientations could predict these characteristics among intercollegiate athletes. Contesting theory identifies two distinct modes of cognitively processing the meaning and purpose of contesting, one rooted in a contest-is-partnership metaphor and the other a contest-is-war metaphor. Study 1 (N = 799) found that contesting orientations added incremental utility beyond demographic and control variables to the prediction of the two dimensions of grit (perseverance and consistency). Specifically, the partnership orientation positively predicted higher grit scores. Study 2 (N = 1179) replicated the findings of Study 1 with only minor variations and also demonstrated that contesting orientations add to the prediction of self-control. Results are discussed in terms of the practical implications for sport practitioners and, more broadly, the value of contesting theory to positive psychology.
Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification

The paper recasts the problem of feature location in source code as a decision-making problem in the presence of uncertainty. The main contribution consists in the combination of two existing techniques for feature location in source code. Both techniques provide a set of ranked facts from the software, as result to the feature identification problem. One of the techniques is based on a scenario based probabilistic ranking of events observed while executing a program under given scenarios. The other technique is defined as an information retrieval task, based on the latent semantic indexing of the source code. We show the viability and effectiveness of the combined technique with two case studies. A first case study is a replication of feature identification in Mozilla, which allows us to directly compare the results with previously published data. The other case study is a bug location problem in Mozilla. The results show that the combined technique improves feature identification significantly with respect to each technique used independently
SYNCHRONIZATION OF ASYMPTOTICALLY PERIODIC BEHAVIORS IN COUNTABLE CELLULAR SYSTEMS

We address the question of frequencies locking in coupled differential systems and of the existence of (component) quasi-periodic solutions of some kind of differential systems. These systems named cellular systems are quite general as they deal with countable number of coupled systems in some general Banach spaces. Moreover, the inner dynamics of each subsystem does not have to be specified. We reach some general results about how the frequencies locking phenomenon is related to the structure of the coupling map, and therefore about the localization of a certain type of quasi-periodic solutions of differential systems that may be seen as cellular systems. This paper gives some explanations about how and why synchronized behaviors naturally occur in a wide variety of complex systems.
The Identification of Gut Neuroendocrine Tumor Disease by Multiple Synchronous Transcript Analysis in Blood

Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) are increasing in both incidence and prevalence. A delay in correct diagnosis is common for these lesions. This reflects the absence of specific blood biomarkers to detect NENs. Measurement of the neuroendocrine secretory peptide Chromogranin A (CgA) is used, but is a single value, is non-specific and assay data are highly variable. To facilitate tumor detection, we developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets: NEN tissue (n = 15), NEN peripheral blood (n = 7), and adenocarcinoma (n = 363 tumors). The candidate gene signature was examined in 130 blood samples (NENs: n = 63) and validated in two independent sets (Set 1 [n = 115, NENs: n = 72]; Set 2 [n = 120, NENs: n = 58]). Comparison with CgA (ELISA) was undertaken in 176 samples (NENs: n = 81). 51 significantly elevated transcript markers were identified. Gene-based classifiers detected NENs in independent sets with high sensitivity (85–98%), specificity (93–97%), PPV (95–96%) and NPV (87–98%). The AUC for the NEN gene-based classifiers was 0.95–0.98 compared to 0.64 for CgA (Z-statistic 6.97–11.42, p<0.0001). Overall, the gene-based classifier was significantly (χ2 = 12.3, p<0.0005) more accurate than CgA. In a sub-analysis, pancreatic NENs and gastrointestinal NENs could be identified with similar efficacy (79–88% sensitivity, 94% specificity), as could metastases (85%). In patients with low CgA, 91% exhibited elevated transcript markers. A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.
PID Robust Control via Genetic Algorithms and MATHEMATICA Facilities C

PID controllers have found extensive industrial applications for several decades. Recently, mixed H2/H• optimal control problems have received a great deal of attention from the viewpoint of theoretical design. Mixed H2/H• control design approaches are useful for robust performance for systems under parameter perturbation and uncertain disturbance. In this paper, a design procedure is proposed to tune PID controller parameters to achieve mixed H2/H• optimal performance. Since the criterion that must be optimized is of integral type, and the constraints are imposed by the robust control, the problem to be solved is a highly nonlinear minimization problem, in which many local minima may exist. Genetic algorithms are parallel, global search techniques that emulate natural genetic operators. Because a genetic algorithm simultaneously evaluates many points in the parameter space, it is more likely to converge to the global solution. MATHEMATICA is powerful symbolic calculus software, which also will be used in the paper to illustrate better the results. Some illustrative examples confirm that good performance can be achieved by the proposed method.
Research of Minimum Energy Consumption Topology Construction in Wireless Sensor Networks

Commenced with the local topology structure of wireless sensor networks, the energy consumption efficiency of single-hop and multi-hop communication is studied. With extremum method, the relation of energy consumption in single-hop and multi-hop communication was compared and then the alternative was given. Moreover, we obtain a theorem that the energy-saving relay region exists in the multi-hop communication node. Based on the theorem, the construction of whole minimum energy consumption topology in wireless sensor network is proposed. In the end, the varying regulation of the energy-saving relay region with the position between nodes is analyzed in the experiments. The experiments analyzed the varying regulation of the energy-saving relay region with the positions of nodes, and finally the correctness and rationality of the minimum energy consumption topology construction was validated.
Using pareto-optimality for solving multi-objective unequal area facility layout problem

A lot of optimal and heuristic algorithms for solving facility layout problem (FLP) have been developed in the past few decades. The majority of these approaches adopt a problem formulation known as the quadratic assignment problem (QAP) that is particularly suitable for equal area facilities. Unequal area FLP comprises a class of extremely difficult and widely applicable optimization problems arising in many diverse areas to meet the requirements for real-world applications. Unfortunately, most of these approaches are based on a single objective. While, the real-world FLPs are multi-objective by nature. Only very recently have meta-heuristics been designed and used in multi-objective FLP. They most often use the weighted sum method to combine the different objectives and thus, inherit the well-known problems of this method. As of now, there is no formal approach published for the unequal area multi-objective FLP to consider several objectives simultaneously. This paper presents an evolutionary approach for solving multi-objective unequal area FLP using multi-objective genetic algorithm that presents the layout as a set of Pareto-optimal solutions optimizing multiple objectives simultaneously. The experimental results show that the proposed approach performs well in dealing with multi-objective unequal area FLPs which better reflects the real-world scenario.
XSLTVM-an XSLT Virtual Machine

A method and apparatus for producing a tire such that the tire has a visible contrasting reference line consisting of a die line ridge produced coincidentally with the extrusion of the tread of the tire and a color contrasting ink applied to the peak surface of the die line ridge by a particularly described inking apparatus. The reference line so produced enables objective visual comparison of the position of the reference line relative to the position of the parting line visible in the cured tire as removed from the mold such that deviations of the reference line with respect to the parting line clearly indicate a tire having an objectionable dissymmetry with respect to its equatorial plane and such that the tire can be removed from the production stream. The reference line so produced and particularly the die line ridge have advantages over previously employed centerline tracking methods and apparatus. The foregoing abstract is not to be taken as limiting the invention of this application, and in order to understand the full nature and extent of the technical disclosure of this application, reference must be made to the accompanying drawing and the following detailed description.
ECG Diagnostics based on the Filter-Bank Signal Processing and ANN / SVM Classification

Processing and classification of electrocardiogram (ECG) recordings are some of the most challenging fields of biomedical signal processing owing to the fact that ECG signals commonly exhibit complex temporal morphology and contain numerous artifacts of data collection process. This paper presents a comparative analysis between the Artificial Neural Networks and Support Vector Machines classification performances based on the feature vectors developed from the Filter-Bank processing of ECG signal. The system is evaluated in the context of Supraventricular Arrhythmia diagnostics. FIR Filter-Bank decomposes the ECG waveform into a various frequency components and enables independent temporal and spectral processing of ECG signal. The feature vectors are developed as a set of statistical measures that describe the energy distribution in the individual sub-bands. The considered statistical descriptors include mean, variance, skewness and kurtosis. In this paper, a systematic study of diagnostic performance is imposed on the choice of feature vector. An optimal Filter-Bank size is ascertained and the relevance of individual frequency bands is evaluated. Furthermore, the diagnostic relevance of statistical descriptors is assessed. The experimental results demonstrate that optimization of feature vectors, in terms of sub-band selection and statistical descriptor choices, leads to a considerable reduction in the feature vector size and to an improvement in the classification accuracy rate. Key-Words: Biomedical signal processing; ECG diagnostics; filter-banks; support vector machines; ANN
Evaluation of Collision Detection and Reaction for a Human-Friendly Robot on Biological Tissues

Up to now, mostly blunt human-robot impacts were investigated in the robotics literature. In this context, the influence of robot mass and velocity during rigid impacts with and without the possibility of the human being clamped was quantified. In this paper an analysis of soft-tissue injuries caused by sharp tools which are mounted on/grasped by a robot and an evaluation of possible countermeasures are carried out as the next step down the road to full safety for robots in physical Human-Robot Interaction. To our knowledge for the first time in robotics, we present various experimental results with biological tissues showing the high performance of our collision detection and reaction schemes even for contacts with sharp tools.
Personalized optimization for android smartphones

As a highly personalized computing device, smartphones present a unique new opportunity for system optimization. For example, it is widely observed that a smartphone user exhibits very regular application usage patterns (although different users are quite different in their usage patterns). User-specific high-level app usage information, when properly managed, can provide valuable hints for optimizing various system design requirements. In this article, we describe the design and implementation of a personalized optimization framework for the Android platform that takes advantage of user's application usage patterns in optimizing the performance of the Android platform. Our optimization framework consists of two main components, the application usage modeling module and the usage model-based optimization module. We have developed two novel application usage models that correctly capture typical smartphone user's application usage patterns. Based on the application usage models, we have implemented an app-launching experience optimization technique which tries to minimize user-perceived delays, extra energy consumption, and state loss when a user launches apps. Our experimental results on the Nexus S Android reference phones show that our proposed optimization technique can avoid unnecessary application restarts by up to 78.4% over the default LRU-based policy of the Android platform.
Z-States Algebra for a Tunable Multi-Party Entanglement-Distillation Protocol

W-States have achieved the status of the standard fully symmetric entangled states, for many entanglement application purposes. Z-States are a generalization of W-States that display an elegant algebra, enabling short paths to desired results. This paper describes Z-States algebra starting from neat definitions and laying down explicitly some fundamental theorems on composition and distillation, needed for applications. These theorems are synthesized into a generic tunable Entanglement-Distillation Protocol. Applications are readily developed based upon the tunable protocol. A few examples are provided to illustrate the approach generality. A concomitant graphical representation allows fast comprehension of the protocol inputs, operations and outcomes.
The Story of One: Humanity scholarship with visualization and text analysis

Most critiques of The Making of Americas (Paris 1925) by Gertrude Stein contend that the text deconstructs the role narrative plays in determining identity by using indeterminacy to challenge readerly subjectivity. The current perception of Making as a postmodern text relies on the notion that there is a tension created by frustrated expectations that result from the text's progressive disbandment of story and plot as the narrative unweaves into seemingly chaotic, meaningless rounds of repetitive words and phrases. Yet, a new perspective that is facilitated by digital tools and based on the highly structured nature of the text suggests that these instabilities can be resolved by the same seemingly nonsensical, non-narrative structures. Seeing the manner in which the structure of the text makes meaning in conversation with narrative alleviates perceived instabilities in the discourse. The discourse about identity formation is engaged—not dissolved in indeterminacy—to the extent that the reader can read the composition. One method for reading the composition of the text without relying on what becomes a non-existent framework based on plot is to view the progression of words according to a different framework, a framework that relies on comparative associations based on word usage. Using WordHoard, i we compared word usage between texts and text parts by calculating the log-likelihood ratio, which describes the size and significance of the difference between word frequencies in a base text versus a reference text. ii In this analysis, we measured word usage in The Making of Americans in comparison to two different sets of reference texts with more traditional narrative structures: (a) a set of 19 th century novels written (b) between the first and second half of Making, which it has been argued also represents different narrative trends (Clement 2008). Visualizing this information in Wordle iv —a word cloud application (Wattenberg & Viegas, 2008)—is useful primarily because it provides a visual overview of word frequencies that is easy to understand and to publish for reference. The Wordle application facilitates this kind of analysis by visualizing the list of words in a cloud that maximizes the space utilization on a computer screen by sizing the words by their relative frequencies. The more frequently a word occurs in a particular text (relative to another text) the larger the word appears. In the set of visualizations that accompany this discussion, v each cloud serves to visualize words that are more or less frequent …
Exploring the Role Teacher Perceptions Play in the Underrepresentation of Culturally and Linguistically Diverse Students in Gifted Programming

This qualitative study explored the role teacher perceptions play in the underrepresentation of culturally and linguistically diverse (CLD) students in gifted programming. Purposeful sampling was used to select six interview participants with at least 5 years of teaching experience. Each participant took part in two semistructured interviews over a 3-month period. Interviews were transcribed and analyzed using Auerbach and Silverstein’s highly structured analytic method. The findings indicate that “the language barrier” and the overemphasis on standardized testing contribute to the underrepresentation of CLD learners in gifted programming. In addition, the researcher identified a need for increased collaboration among educators during the gifted referral and identification processes as well as professional development to raise awareness about the issue of underserved populations in gifted education.
Coping and resilience: People’s innovative solutions

This Paper introduces the intertwined concepts of coping and resilience, with their varied dimensions. Beginning with brief stories that show how individuals, groups, communities and nations display both coping and resilience every day, the analysis shifts to the meaning of every day stress and adversity that have become inevitable parts of daily jigsaw puzzle of life. The paper also presents a bird’s eye view of the meaning of every day stress and adversity that has become inevitable parts of our daily life and brings in strengths perspective into resiliency and finally signals the efficacy of an inner strengths approach. ; ;
Post-quantum Authenticated Key Exchange from Ideal Lattices ̈

In this paper, we present a practical and provably secure two-pass AKE protocol from ideal lattices, which is conceptually simple and has similarities to the Diffie-Hellman based protocols such as HMQV (CRYPTO 2005) and OAKE (CCS 2013). Our protocol does not rely on other cryptographic primitives—in particular, it does not use signatures—simplifying the protocol and resting the security solely on the hardness of the ring learning with errors problem. The security is proven in the Bellare-Rogaway model with weak perfect forward secrecy. We also give a one-pass variant of our two-pass protocol, which might be appealing in specific applications. Several concrete choices of parameters are provided, and a proof-of-concept implementation shows that our protocols are indeed practical.
ICICLE: groupware for code inspection

ICICLE1 (“Intelligent Code Inspection Environment in a C Language Environment”) is a multifarious software system intended to augment the process of formal code inspection. It offers assistance in a number of activities, including knowledge-based analysis and annotations of source code, and computer supported cooperative discussion and finalization of inspectors' comments during inspection meetings. This paper reports the implementation of ICICLE and GroupWare issues encountered during testing; it is directed towards an audience interested in the implementation of GroupWare as well as those concerned with usability of software systems for computer-supported cooperative work (CSCW).