Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Public Auditing for Shared Data Storage with User Revocation in Cloud Computing

Cloud computing technology has matured, so cloud computing produces a wide range of cloud service. Cloud storage services are one of cloud services where cloud service provider can provide storage space to customers. Because cloud storage services bring a lot of convenience, many enterprises and users store the data to the cloud storage. However, the user will outsource data to the cloud storage service, but the user is difficult to manage remote data in the cloud. Therefore, how users verify data integrity is a major challenge. In recent years, public audit is used to verify data integrity by which the user allows other to verify the user's data. Because the feature of cloud service allows users to communicate with each other on the cloud platform, the cloud storage service allows the data owner to share their data to other users. Therefore, public auditing extends to the share data, so the original operation becomes not the same including signature, public audits, dynamic data and user revocation which generates on the situation of shared data. In the paper, we define the requirements of public auditing with shared data and explain four representative approaches which include analysis function, security, and performance requirements. Finally, we provide some topics for future research.
Shortening of the Lactobacillus paracasei subsp. paracasei BGNJ1-64 AggLb Protein Switches Its Activity from Auto-aggregation to Biofilm Formation

AggLb is the largest (318.6 kDa) aggregation-promoting protein of Lactobacillus paracasei subsp. paracasei BGNJ1-64 responsible for forming large cell aggregates, which causes auto-aggregation, collagen binding and pathogen exclusion in vitro. It contains an N-terminus leader peptide, followed by six successive collagen binding domains, 20 successive repeats (CnaB-like domains) and an LPXTG sorting signal at the C-terminus for cell wall anchoring. Experimental information about the roles of the domains of AggLb is currently unknown. To define the domain that confers cell aggregation and the key domains for interactions of specific affinity between AggLb and components of the extracellular matrix, we constructed a series of variants of the aggLb gene and expressed them in Lactococcus lactis subsp. lactis BGKP1-20 using a lactococcal promoter. All of the variants contained a leader peptide, an inter collagen binding-CnaB domain region (used to raise an anti-AggLb antibody), an anchor domain and a different number of collagen binding and CnaB-like domains. The role of the collagen binding repeats of the N-terminus in auto-aggregation and binding to collagen and fibronectin was confirmed. Deletion of the collagen binding repeats II, III, and IV resulted in a loss of the strong auto-aggregation, collagen and fibronectin binding abilities whereas the biofilm formation capability was increased. The strong auto-aggregation, collagen and fibronectin binding abilities of AggLb were negatively correlated to biofilm formation.
Principles of Artificial Economics In Animal Minds

This paper describes the results of a simulation using metrics associated with the principles of artificial economics in animal cognition. The main purpose of this research paper is to understand the principles of natural minds and adopt these principles in a simulation environment. This approach necessasarily requires the design and test of a range of simple and complex computational agents. The developed micro-agents in a fungus world testbed are designed to investigate artificial minds for animals and synthetic agents, drawing on qualities found in the natural minds. Qualities such as level of decision making, its cost function and utility behaviour (the microeconomic level), physiological and goal oriented behaviour are investigated.
On the Theoretical and Computational Analysis between SDA and Lap-LDA

Semi-supervised dimensionality reduction is an important research topic in many pattern recognition and machine learning applications. Among all the methods for semi-supervised dimensionality reduction, SDA and Lap-LDA are two popular ones. Both SDA and Lap-LDA can perform dimensionality reduction by preserving the discriminative structure embedding in the labeled samples as well as the manifold structure embedded both in labeled and unlabeled samples. But they apply different schemes for semi-supervised dimensionality reduction. SDA has added the manifold term to the objective function of LDA while Lap-LDA has added such term to the objective function of Least Square with certain class indicator. In this paper, we further analyze the schemes of two methods and build the equivalence between them by giving a certain condition. We then show their difference when the certain condition cannot be satisfied. Extensive simulations have been conducted based several datasets. Both theoretical analysis and simulation results confirm the analysis. Finally, motivated by the equivalence and differences between two methods, we then propose an improved approach for semi-supervised dimensionality reduction. The proposed approach is actually a two-stage approach and can obtain the optimal solution equivalent to Lap-LDA (in this first stage) and SDA (in the second stage) with less computational cost.
Prediction of Mortality Using On-Line, Self-Reported Health Data: Empirical Test of the Realage Score

Objective We validate an online, personalized mortality risk measure called “RealAge” assigned to 30 million individuals over the past 10 years. Methods 188,698 RealAge survey respondents were linked to California Department of Public Health death records using a one-way cryptographic hash of first name, last name, and date of birth. 1,046 were identified as deceased. We used Cox proportional hazards models and receiver operating characteristic (ROC) curves to estimate the relative scales and predictive accuracies of chronological age, the RealAge score, and the Framingham ATP-III score for hard coronary heart disease (HCHD) in this data. To address concerns about selection and to examine possible heterogeneity, we compared the results by time to death at registration, underlying cause of death, and relative health among users. Results The RealAge score is accurately scaled (hazard ratios: age 1.076; RealAge-age 1.084) and more accurate than chronological age (age c-statistic: 0.748; RealAge c-statistic: 0.847) in predicting mortality from hard coronary heart disease following survey completion. The score is more accurate than the Framingham ATP-III score for hard coronary heart disease (c-statistic: 0.814), perhaps because self-reported cholesterol levels are relatively uninformative in the RealAge user sample. RealAge predicts deaths from malignant neoplasms, heart disease, and external causes. The score does not predict malignant neoplasm deaths when restricted to users with no smoking history, no prior cancer diagnosis, and no indicated health interest in cancer (p-value 0.820). Conclusion The RealAge score is a valid measure of mortality risk in its user population.
Perception of Thai Tones in Hearing Impaired and Cochlear Implant Patients

Lexical tone perception in Thai adults with normal hearing and those with hearing impairment using hearing aids and using cochlear implants (CIs) has been investigated to evaluate the benefit of using either of them for tone perception. Tone perception pattern across three groups has been compared. Identification tests with white noise using a two alternative forced choice task were carried out to normal hearing subjects, while those with clean conditions were carried out to hearing impaired subjects (with and without hearing aids) Average percent correct responses, balanced confusion matrices were obtained and confusion pattern in each tone pair can be systematically compared. Further, discrimination test for tones was performed individually on four hearing-impaired adults with cochlear implants. Only clean stimuli were used in the test. The experimental results confirmed that comparing with normal hearing subjects, tone perception is affected by hearing loss. Surprisingly, hearing aids and CIs provide insufficient details for Thai tone perception and very minimal success can be achieved for both cases. However, it should be noted that this work is a preliminary study on the group of prelingually deafened adults who received the CI when they were an adult. Therefore, they had significantly long duration of auditory deprivation. In future work, further studies on postlingually deafened adults will be carried out.
Algorithms for Calculating Statistical Properties of Moving Points

Robust statistics and kinetic data structures are two frequently studied theoretical areas with practical motivations. The former topic is the study of statistical estimators that are robust to data outliers. The latter topic is the study of data structures for calculations on moving point sets. The combination of these two areas has not previously been studied. In studying this intersection, we consider these problems in the context of both an established kinetic framework (called KDS) that relies on advance point motion information and calculates properties continuously and a new sensor-based framework that uses discrete point observations. Using the KDS model, we present an approximation algorithm for the kinetic robust k-center problem, a clustering problem that requires k clusters but allows some outlying points to remain unclustered. For many practical problems that inspired the exploration into robustness, the KDS model is inapplicable due to the point motion restrictions and the advance flight plans required. Working towards a solution to the kinetic robust k-center problem on a framework that allows unrestricted point motion, we present a new framework for kinetic data that allows calculations on moving points via sensor-recorded observations. This new framework is one of the first within the computational geometry community to allow analysis of moving points without a priori knowledge of point motion. Analysis within this framework is based on the entropy of the point set’s motion, so efficiency bounds are a function of observed complexity instead of worst-case motion. A compression algorithm within this framework is presented. The focus of this proposal will be on examining robust statistical problems on kinetic data. These problems will be explored within the sensor-based framework. Specific questions to be answered will lead from the current compression algorithm to more complex statistical analyses.
Second-Order Sliding Mode Control of a Doubly Fed Induction Generator Driven Wind Turbine

This paper deals with power extraction maximization of a doubly fed induction generator (DFIG)-based wind turbine. These variable speed systems have several advantages over the traditional wind turbine operating methods, such as the reduction of the mechanical stress and an increase in the energy capture. To fully exploit this latest advantage, many control schemes have been developed for maximum power point tracking (MPPT) control schemes. In this context, this paper proposes a second-order sliding mode to control the wind turbine DFIG according to references given by an MPPT. Traditionally, the desired DFIG torque is tracked using control currents. However, the estimations used to define current references drive some inaccuracies mainly leading to nonoptimal power extraction. Therefore, using robust control, such as the second-order sliding mode, will allow one to directly track the DFIG torque leading to maximum power extraction. Moreover, the proposed control strategy presents attractive features such as chattering-free behavior (no extra mechanical stress), finite reaching time, and robustness with respect to external disturbances (grid) and unmodeled dynamics (generator and turbine). Simulations using the wind turbine simulator FAST and experiments on a 7.5-kW real-time simulator are carried out for the validation of the proposed high-order sliding mode control approach.
Comparison of Regularization Methods for Nucleon-Nucleon Effective Field Theory

The characteristics of a meaningful effective field theory (EFT) analysis are discussed and compared with traditional approaches to NN scattering. A key feature of an EFT treatment is a systematic expansion in powers of momentum, which is demonstrated using an error analysis introduced by Lepage. A clear graphical determination of the radius of convergence for the momentum expansion is also obtained. I use these techniques to compare cutoff regularization, two forms of dimensional regularization, and the dibaryon approach, using a simple model for illustration. The naturalness of the parameters and predictions for other observables are also shown.
Alice through the looking glass

We present Alice, a functional programming language that has been designed with strong support for typed open programming . It incorporates concurrency with data ﬂow synchronisation, higher-order modularity, dynamic modules, and type-safe pickling as a minimal and generic set of simple, orthogonal features providing that support. Based on these mechanisms Alice offers a ﬂexible notion of component, and high-level facilities for distributed programming.
IN SUPPORT OF PERSONALITY ASSESSMENT IN ORGANIZATIONAL SETTINGS

Personality constructs have been demonstrated to be useful for explaining and predicting attitudes, behaviors, performance, and outcomes in organizational settings. Many professionally developed measures of personality constructs display useful levels of criterion-related validity for job performance and its facets. In this response to Morgeson et al. (2007), we comprehensively summarize previously published meta-analyses on (a) the optimal and unit-weighted multiple correlations between the Big Five personality dimensions and behaviors in organizations, including job performance; (b) generalizable bivariate relationships of Conscientiousness and its facets (e.g., achievement orientation, dependability, cautiousness) with job performance constructs; (c) the validity of compound personality measures; and (d) the incremental validity of personality measures over cognitive ability. Hundreds of primary studies and dozens of meta-analyses conducted and published since the mid 1980s indicate strong support for using personality measures in staffing decisions. Moreover, there is little evidence that response distortion among job applicants ruins the psychometric properties, including criterionrelated validity, of personality measures. We also provide a brief evaluation of the merits of alternatives that have been offered in place of traditional self-report personality measures for organizational decision making. Given the cumulative data, writing off the whole domain of individual differences in personality or all self-report measures of personality from personnel selection and organizational decision making is counterproductive for the science and practice of I-O psychology.
Bioluminescent, Nonlytic, Real-Time Cell Viability Assay and Use in Inhibitor Screening

Abstract Real-time continuous monitoring of cellular processes offers distinct advantages over traditional endpoint assays. A comprehensive representation of the changes occurring in live cells over the entire length of an experiment provides information about the biological status of the cell and informs decisions about the timing of treatments or the use of other functional endpoint assays. We describe a homogeneous, nonlytic, bioluminescent assay that measures cell viability in real time. This time-dependent measurement allowed us to monitor cell health for 72 h from the same test samples, distinguish differential cell growth, and investigate drug mechanism of action by analyzing time- and dose-dependent drug effects. The real-time measurements also allowed us to detect cell death immediately (>75% signal decrease within 15 min of digitonin addition), analyze drug potency versus efficacy, and identify cytostatic versus toxic drug effects. We screened an oncology compound library (Z′ = 0.7) and identified compounds with varying activity at different time points (1.6% of the library showed activity within 3 h, whereas 35.4% showed a response by 47 h). The assay compared well with orthogonal endpoint cell viability assays and additionally provided data at multiple time points and the opportunity to multiplex assays on the same cells. To test the advantage of time-dependent measurements to direct optimal timing of downstream applications, we used the real-time cell viability assay to determine the ideal time to measure caspase activity by monitoring the onset of cell death and multiplexing a luminescent caspase activation assay on the same test samples.
Design and Analysis of a novel fan-out WLCSP structure

A novel wafer level chip scaled packaging (WLCSP) having the capability of the redistributing the electrical circuit is proposed herein to resolve the problem of assembling a fine pitched chip to a coarse pitched substrate. In the fan-out WLCSP, the chip is first attached to a specific 8" chip carrier, and then the trench between the chips are filled by the filler polymer. The solder bumps could be located on both the filler polymer and chip surface, but the fabrication of the fan-out WLCSP is similar to the conventional 8" WLCSP process. Because the packaging structure of the fan-out WLCSP differs from the conventional one, a series of coplanity and solder joint height experiment is conducted to verify the capability of mounting the said structure to the substrate. The experimental results indicated that the derivation of the fan-out WLCSP is approximated plusmn0.01 mm, which is acceptable in the surface mount technology of the substrate. Moreover, the nonlinear finite element (FE) method is applied to analyze the mechanical characteristics of the fan-out WLCSP. Moreover, both the solder joint reliability and the trace stress while the external thermal cycling loading is considered. The simulation result indicates that the distance between the solder joint and the edge of the chip and filler polymer was more sensitive than other the design parameters, and the said distance parameter would dominate the mechanical characteristic of the fan-out WLCSP
A new method for discovery of vegetation changes based on satellite ground photographs

The normalized difference vegetation index (NDVI) is widely used to detect ground vegetation based on remote-sensing satellite images. However, it is affected by deficiencies such as sensation to change in sun angle, atmospheric effects and noise contamination. As developing of high-resolution satellite ground photographs, a new approach of vegetation detection on ground photographs is proposed to automatically discover changes of vegetation on a specific area. The HSV color space is used to analyze vegetation areas, a new complexity index is defined to identify forest or grass. The experimental results show that the vegetation areas can be well separate from the Baidu satellite ground photographs and the changes of vegetation areas can be discovered using a set of new definitions of vegetation changes. The proposed method has potential to use in monitoring of plant ecology changes in agriculture, forestry human life environment. The new method can be used not only on the satellite ground photographs but also on the unmanned aerial vehicle images.
The Effect of Decision-Making Factors, Risk-Taking Propensity, and Environmental Conditions on Decision Making in Hazardous Outdoor Terrain

D espite the popularity of avalanche education courses, snow avalanches kill or injure hundreds of winter backcountry users each year (Tremper, 2001). From 1998 to 2008, there have been 308 avalanche-related fatalities in the United States and 129 in Canada (American Avalanche Association, n.d.). Experts claim that accidents are often a combination of both environmental factors and human factors (Fredston, Fesler, & Tremper, 1994). Investigation of variables present during decision-making in hazardous outdoor terrain may inform experiential educational programs designed to teach students about these factors and ultimately, increase safety in the outdoors.
Temporal Logic Patterns for Querying Qualitative Models of Genetic Regulatory Networks

Formal verification based on model checking provides a powerful technology to query qualitative models of dynamical systems. The application of model-checking approaches is hampered, however, by the difficulty for non-expert users to formulate appropriate questions in temporal logic. In order to deal with this problem, we propose the use of patterns, that is, high-level query templates capturing recurring questions which can be automatically translated to temporal logic. We develop a set of patterns for the analysis of qualitative models of genetic regulatory networks, which are sufficiently generic though to be useful in other application domains. The applicability of the patterns has been investigated by the analysis of a model of the network of global regulators controlling the carbon starvation response in Escherichia coli.
Deviation equations of Synge and Schild over ( L n , g )-spaces

Deviation equation of Synge and Schild has been investigated over dif-ferentiable manifolds with contravariant and covariant aﬃne connections (whose components diﬀer not only by sign) and metric [( L n , g )-spaces]. It is shown that the condition £ ξ u = 0 for obtaining this equation is only a suﬃcient (but not necessary) condition. By means of a non-isotropic (non-null) vector ﬁeld u [ g ( u, u ) = e 6 = 0] and the metric h u , orthogonal to it, a projected deviation equation of Synge and Schild has been obtained for the orthogonal to u vector ﬁeld ξ ⊥ and its square L 2 = g ( ξ ⊥ , ξ ⊥ ). For a given non-isotropic, auto-parallel and normalized vector ﬁeld u this equation could have some simple solutions.
The Soluble Heparin-Binding EGF-Like Growth Factor Stimulates EGF Receptor Trafficking to the Nucleus

Most ligands of epidermal growth factor receptor (EGFR) have the ability to induce EGFR translocation into the nucleus, where EGFR acts as an important transcriptional regulator. Soluble form of heparin-binding EGF-like growth factor (sHB-EGF) is one of the ligands for EGFR in many cell types; however, there is no evidence for the ability of sHB-EGF to induce EGFR nuclear importation. Here, we demonstrated that treatment of A431 cells with sHB-EGF resulted in nuclear localization of EGFR and such translocation occurs via retrograde pathway. It was shown by confocal microscopy and co-immunoprecipitation assay that the translocation complex consisted of both ligand and receptor. The chromatin immunoprecipitation assay showed the association of sHB-EGF–EGFR complex with promoter region of cyclin D1 in the cell nucleus and this association was prevented by application of EGFR kinase inhibitor AG-1478. The obtained data suggest that sHB-EGF acts similarly to other EGFR ligands and is capable to induce EGFR nuclear translocation as a part of ligand-receptor complex in a tyrosine phosphorylation-dependent manner.
Spatiotemporal Modular Arrangement for Energy Efficient Reconfigurable SoCs

In this paper, the proposed approach is assessed from not only its power-performance efficiency but also the accuracy of implemented algorithms on the real hardware environment. The real system treats pattern recognition and motion tracking. The former uses the subspace method and the latter adapts the Kanade-Lucas-Tomasi (KLT) algorithm. These algorithms are widely known in computer vision but the both approaches are unsuited for reconfigurable architectures because they include much complex calculation such as the extraction of a square root of 32-bit or 64-bit data width. But, these methods do not operate simultaneously. Thus, by adopting spatiotemporal reconfiguration pipeline, this paper also describes not only the reduction of configuration size but also the achievement of low power consumption with the same performance of the naive approach.