Miracle-dz/UniFAR-FTUs huggingface dataset:
A Secret-Sharing-Based Method for Authentication of Grayscale Document Images via the Use of the PNG Image With a Data Repair Capability

A new blind authentication method based on the secret sharing technique with a data repair capability for grayscale document images via the use of the Portable Network Graphics (PNG) image is proposed. An authentication signal is generated for each block of a grayscale document image, which, together with the binarized block content, is transformed into several shares using the Shamir secret sharing scheme. The involved parameters are carefully chosen so that as many shares as possible are generated and embedded into an alpha channel plane. The alpha channel plane is then combined with the original grayscale image to form a PNG image. During the embedding process, the computed share values are mapped into a range of alpha channel values near their maximum value of 255 to yield a transparent stego-image with a disguise effect. In the process of image authentication, an image block is marked as tampered if the authentication signal computed from the current block content does not match that extracted from the shares embedded in the alpha channel plane. Data repairing is then applied to each tampered block by a reverse Shamir scheme after collecting two shares from unmarked blocks. Measures for protecting the security of the data hidden in the alpha channel are also proposed. Good experimental results prove the effectiveness of the proposed method for real applications.
Cell segmentation and tracking in phase contrast images using graph cut with asymmetric boundary costs

We propose a new robust, effective, and surprisingly simple approach for the segmentation of cells in phase contrast microscopy images. The key feature of our algorithm is that it strongly favors dark-to-bright transitions at the boundaries of the (arbitrarily shaped) segmentation mask. The segmentation mask can be effectively found by a fast min-cut approach. The small but essential difference to standard min-cut based approaches is that our graph contains directed edges with asymmetric edge weights. Combined with a simple region propagation our approach yields better segmentation results on the ISBI Cell Tracking Challenge 2014 dataset than the top ranked methods. We provide an easy-to-use open-source implementation for ImageJ/Fiji and Matlab on our homepage.
Data cleaning and XML: the DBLP experience

With the increasing popularity of data-centric XML, data warehousing and mining applications are being developed for rapidly burgeoning XML data repositories. Data quality will no doubt be a critical factor for the success of such applications. Data cleaning, which refers to the processes used to improve data quality, has been well researched in the context of traditional databases. In earlier work we developed a knowledge-based framework for data cleaning relational databases. In this work, we present a novel attempt to apply this framework to XML databases. Our experimental dataset is the DBLP database, a popular online XML bibliography database used by many researchers.
Talbanken05: A Swedish Treebank with Phrase Structure and Dependency Annotation

We introduce Talbanken05, a Swedish treebank based on a syntactically annotated corpus from the 1970s, Talbanken76, converted to modern formats. The treebank is available in three different formats, besides the original one: two versions of phrase structure annotation and one dependency-based annotation, all of which are encoded in XML. In this paper, we describe the conversion process and exemplify the available formats. The treebank is freely available for research and educational purposes.
On MPC based trajectory tracking

This work proposes and investigates a tracking scheme for linear, constrained system based on a combination of model predictive control, virtual references and unknown input observers. In contrast to existing results the proposed approach allows to track a larger class of trajectories exactly: it does not require a reference model, does not need to assumes constant/periodic references or that the reference converges to a steady state. The scheme guarantees under mild conditions recursive feasibility independent of the reference and asymptotically exact tracking. It is computationally tractable, since only a convex quadratically constrained quadratic program or a convex quadratic program needs to be solved at each time step. We outline the applicability and the efficacy of the proposed approach using two examples.
Image encryption algorithm based on chaotic system

Traditional permutation encryption algorithm is not robustness for noise disturbing and shear transformation attacks. In order to ameliorate the security of image encryption algorithm, we present an image encryption algorithm based on location transformation. The algorithm permute image based on chaotic system and storage everyone pixel of the image in multi-place, this encrypted image is robustness for noise disturbing and shear transformation attack. An extended magic square matrix-generating algorithm is also presented and it improves on the efficiency of the magic square matrix-generating algorithm. The simulation results show that the effect of decrypting image is good when the encrypting image is modified by noise disturbing and shear transformation attack
Transmit Beamforming with Reduced Feedback Information in OFDM Based Wireless Systems

This paper considers a transmit beamforming scheme that works with reduced feedback information in OFDM based multiple-input single-output (MISO) wireless systems. The proposed scheme generates the beamforming weight using information on the previous beamforming weights and channel correlation, significantly reducing the amount of feedback signaling burden. The feedback signaling overhead can further be reduced with the use of clustering and interpolation techniques. Simulation results show that the proposed scheme outperforms conventional beamforming techniques, while using the same amount of feedback signaling overhead.
Chk1 protects against chromatin bridges by constitutively phosphorylating BLM serine 502 to inhibit BLM degradation

ABSTRACT Chromatin bridges represent incompletely segregated chromosomal DNA connecting the anaphase poles and can result in chromosome breakage. The Bloom's syndrome protein helicase (BLM, also known as BLMH) suppresses formation of chromatin bridges. Here, we show that cells deficient in checkpoint kinase 1 (Chk1, also known as CHEK1) exhibit higher frequency of chromatin bridges and reduced BLM protein levels compared to controls. Chk1 inhibition leads to BLM ubiquitylation and proteasomal degradation during interphase. Furthermore, Chk1 constitutively phosphorylates human BLM at serine 502 (S502) and phosphorylated BLM localises to chromatin bridges. Mutation of S502 to a non-phosphorylatable alanine residue (BLM-S502A) reduces the stability of BLM, whereas expression of a phospho-mimicking BLM-S502D, in which S502 is mutated to aspartic acid, stabilises BLM and prevents chromatin bridges in Chk1-deficient cells. In addition, wild-type but not BLM-S502D associates with cullin 3, and cullin 3 depletion rescues BLM accumulation and localisation to chromatin bridges after Chk1 inhibition. We propose that Chk1 phosphorylates BLM-S502 to inhibit cullin-3-mediated BLM degradation during interphase. These results suggest that Chk1 prevents deleterious anaphase bridges by stabilising BLM.
First Experimental Functionalization Results of SiC Nanopillars for Biosensing Applications

DNA biosensors based on silicon carbide nanowire bioFET (SiC NW bioFET) benefit from both biocompatibility and semiconducting properties of SiC. One of the device realization key points is the functionalization of the SiC NW. This process is composed of two main steps: silanization and DNA grafting. It has been successfully carried out on both SiC single crystals and SiC nanopillars. Evidences of DNA detection are given by X-Ray photoelectron Spectroscopy (XPS) and fluorescence microscopy.
LFSR-based Signatures with Message Recovery

In order to reduce key sizes and bandwidth, several LFSRbased (linear feedback shift register) public key cryptosystems and signature schemes have been proposed. Digital signatures with message recovery are useful for many applications in which small messages (e.g., 100 bits or so) should be signed. This paper first presents a new sequence operation, called DSO, based on existing sequence operations, and then proposes a LFSR-based signature scheme with message recovery and a LFSR-based signature scheme with partial message recovery. We support the proposed schemes with security analysis. Our schemes take the advantage that they require less computation complexity, less representation and less bandwidth than those required in their counterparts based on finite fields of Zq.
Modelling and Simulation of a SAR ADC with Internally Generated Conversion Signal

This paper presents the modeling and simulation of a 833.33 kS/s, 51. 279μW successive approximation register(SAR) Analog to Digital Converter(ADC) using 0. 18μm CMOS technology that uses internally generated signal for approximation for low power applications. The ADC is powered by single supply voltage of 1V. In our scheme, comparator output time and bit settling time of the Digital to Analog Converter(DAC) are utilized to generate a signal level such that the next step of the conversion can take place. This model is significant for Globally Asynchronous Locally Synchronous(GALS) system integration.
Predictive Modeling in Hostage and Barricade Incidents

The study examined 534 hostage and barricade incidents. Its objective was to present an integrated and formalized vision of current conceptualizations of critical incidents to optimize decision making. To this end, logistic regression and recursive partitioning models are presented and compared. In all, 18 distinct static and dynamic individual and situational factors were used to predict various outputs during this type of situation. Results highlight the importance of considering the origin of the emergency call and being barricaded in one's home in the assessment of perpetrator's propensity for violence, the fact that time is not always on the police's side during critical incidents, and the relatively minor importance of hostage taking in the general comprehension of these high-risk events.
MEASURING PUBLIC PREFERENCES FOR MULTIFUNCTIONAL ATTRIBUTES OF AGRICULTURE IN THE UNITED STATES

Abstract The paper examines U.S. citizens' attitudes toward the concept of multifunctional agriculture and their perceptions about its various attributes. While the concept has emerged as a major narrative shaping agricultural policies and WTO trade rules, there are considerable disagreements among researchers and policy-makers about what should be considered legitimate attributes of multifunctional agriculture, preventing WTO negotiations from moving forward. Results show that U.S. citizens rated national food security and environmental services as the most important multifunctional roles of U.S. agriculture, and national food security makes the largest contribution to explaining U.S. citizens' attitudes toward multifunctional agriculture.
Time Series of Continuous Proportions

SUMMARY A vector of continuous proportions consists of the proportions of some total accounted for by its constituent components. An example is the proportions of world motor vehicle production by Japan, the USA and all other countries. We consider the situation where time series data are available and where interest focuses on the proportions rather than the actual amounts. Reasons for analysing such times series include estimation of the underlying trend, estimation of the effect of covariates and interventions, and forecasting. We develop a state space model for time series of continuous proportions. Conditionally on the unobserved state, the observations are assumed to follow the Dirichlet distribution, often considered to be the most natural distribution on the simplex. The state follows the Dirichlet conjugate distribution which is introduced here. Thus the model, although based on the Dirichlet distribution, does not have its restrictive independence properties. Covariates, trends, seasonality and interventions may be incorporated in a natural way. The model has worked well when applied to several examples, and we illustrate with components of world motor vehicle production.
A language/action perspective on the design of cooperative work

In designing computer-based systems, we work within a perspective that shapes the design questions that will be asked and the kinds of solutions that are sought. This paper introduces a perspective based on language as action, and explores its consequences for practical system design. The language/action perspective is contrasted to a number of other currently prominent perspectives, and is illustrated with an extended example based on studies of nursing work in a hospital ward. We show how it leads to particular analyses of that work, which reveal potentials for creating new designs that can make the work (and the workers) more effective.
Estimation of induction motor speed based on artificial neural networks inversion system

As rotation speed is necessary for high-performance induction motor control, how to estimate the speed quickly and accurately is concerned by most scholars. On the analysis of theoretic invertibility of the induction motorpsilas mathematic model, a speed estimation based on neural networks inversion is proposed. The structure of multi-layer feed-forward neural network (MFNN) is trained by advanced backpropagation arithmetic. Also the achievement method and experiment results were given. The results show that the responses based on ANN inversion method can track the rotation speed quickly and accurately. The method proposed is effective in application.
Wavelet radiosity

Radiosity methods have been shown to be an effective means to solve the global illumination problem in Lambertian diffuse environments. These methods approximate the radiosity integral equation by projecting the unknown radiosity function into a set of basis functions with limited support resulting in a set of n linear equations where n is the number of discrete elements in the scene. Classical radiosity methods required the evaluation of n 2 interaction coefﬁcients. Efforts to reduce the number of required coefﬁcients without compromising error bounds have focused on raising the order of the basis functions, meshing, accounting for discontinuities, and on developing hierarchical approaches, which have been shown to reduce the required interactions to O ( n ). In this paper we show that the hierarchical radiosity formulation is an instance of a more general set of methods based on wavelet theory. This general framework offers a uniﬁed view of both higher order element approaches to radiosity and the hierarchical radiosity methods. After a discussion of the relevant theory, we discuss a new set of linear time hierarchical algorithms based on wavelets such as the multiwavelet family and a ﬂatlet basis which we introduce. Initial results of experimentation with these basis sets are demonstrated and discussed.
A Novel Hierarchical Convolutional Neural Network for Question Answering over Paragraphs

The question of classical Factoid Question Answering (FQA) task is always in the form of a single sentence. There also exists another kind of FQA task, whose question is a descriptive paragraph, such as quiz bowl question answering. Recently, some works try to automatically answer paragraph questions by applying machine learning methods. However, these methods neglect the correlation information between sentences in a paragraph and do not take full advantage of answer embedding information. In this paper, we propose a novel Hierarchical Convolutional Neural Network, called HCNN-E, to settle the task by considering ordinal information of sentences in paragraph and the information of answer embeddings. The experimental results on two public datasets demonstrate the effectiveness of proposed method, and the proposed method can achieve approximately 10% - 20% improvements, when comparing with the baselines.
Co-Factor Binding Confers Substrate Specificity to Xylose Reductase from Debaryomyces hansenii

Binding of substrates into the active site, often through complementarity of shapes and charges, is central to the specificity of an enzyme. In many cases, substrate binding induces conformational changes in the active site, promoting specific interactions between them. In contrast, non-substrates either fail to bind or do not induce the requisite conformational changes upon binding and thus no catalysis occurs. In principle, both lock and key and induced-fit binding can provide specific interactions between the substrate and the enzyme. In this study, we present an interesting case where cofactor binding pre-tunes the active site geometry to recognize only the cognate substrates. We illustrate this principle by studying the substrate binding and kinetic properties of Xylose Reductase from Debaryomyces hansenii (DhXR), an AKR family enzyme which catalyzes the reduction of carbonyl substrates using NADPH as co-factor. DhXR reduces D-xylose with increased specificity and shows no activity towards “non-substrate” sugars like L-rhamnose. Interestingly, apo-DhXR binds to D-xylose and L-rhamnose with similar affinity (Kd∼5.0–10.0 mM). Crystal structure of apo-DhXR-rhamnose complex shows that L-rhamnose is bound to the active site cavity. L-rhamnose does not bind to holo-DhXR complex and thus, it cannot competitively inhibit D-xylose binding and catalysis even at 4–5 fold molar excess. Comparison of Kd values with Km values reveals that increased specificity for D-xylose is achieved at the cost of moderately reduced affinity. The present work reveals a latent regulatory role for cofactor binding which was previously unknown and suggests that cofactor induced conformational changes may increase the complimentarity between D-xylose and active site similar to specificity achieved through induced-fit mechanism.
Role of ornithine decarboxylase/polyamine pathway in focal cerebral ischemia-reperfusion injury and its mechanism in rats.

OBJECTIVE To observe the role of ornithine decarboxylase (ODC)/polyamine pathway in focal cerebral ischemia-reperfusion injury and to explore its mechanism in rats. METHODS This study was randomly divided into 3 groups including sham-operation (sham) group, ischemia-reperfusion (I/R) group and α-difluoromethylornithine (DFMO) group (each group with 80 rats). In DFMO group, 300 mg/kg of DFMO was injected by tail vein 24 h before reperfusion. According to different time points (3 h, 12 h, 24 h, 48 h and 72 h) after reperfusion, each group was divided into 5 subgroups (each subgroup with 16 rats). RESULTS In I/R group, apoptosis began increasing 3 h after reperfusion, reached a peak 24 h after perfusion and began decreasing 48 h after perfusion. Compared with sham group, apoptosis significantly increased in I/R and DFMO groups (P<0.05). However, apoptosis was significantly lower in DFMO group than in I/R group at each time point (P<0.05). In I/R group, CHOP expression began increasing 3 h after reperfusion, reached a peak 24 h after perfusion and began decreasing 48 h after perfusion. CHOP expression was significantly lower in DFMO group than in I/R group at each time point (P<0.05). The level of polyamines was significantly higher in I/R and DFMO groups than in sham group, and in I/R group than in DFMO group 12 h, 24 h and 48 h, respectively (P<0.05). CONCLUSION Down-regulation of ODC/polyamine pathway may inhibit CHOP-mediated apoptosis caused by endoplasmic reticulum stress and plays a protective role in cerebral I/R injury.
Know Your Client and Know Your Team: A Complexity Inspired Approach to Understanding Safe Transitions in Care

Background. Transitions in care are one of the most important and challenging client safety issues in healthcare. This project was undertaken to gain insight into the practice setting realities for nurses and other health care providers as they manage increasingly complex care transitions across multiple settings. Methods. The Appreciative Inquiry approach was used to guide interviews with sixty-six healthcare providers from a variety of practice settings. Data was collected on participants' experience of exceptional care transitions and opportunities for improving care transitions. Results. Nurses and other healthcare providers need to know three things to ensure safe care transitions: (1) know your client; (2) know your team on both sides of the transfer; and (3) know the resources your client needs and how to get them. Three themes describe successful care transitions, including flexible structures; independence and teamwork; and client and provider focus. Conclusion. Nurses often operate at the margins of acceptable performance, and flexibility with regulation and standards is often required in complex sociotechnical work like care transitions. Priority needs to be given to creating conditions where nurses and other healthcare providers are free to creatively engage and respond in ways that will optimize safe care transitions.
Methyl-compound use and slow growth characterize microbial life in 2-km-deep subseafloor coal and shale beds

Significance Microbial cells are widespread in diverse deep subseafloor environments; however, the viability, growth, and ecophysiology of these low-abundance organisms are poorly understood. Using single-cell–targeted stable isotope probing incubations combined with nanometer-scale secondary ion mass spectrometry, we measured the metabolic activity and generation times of thermally adapted microorganisms within Miocene-aged coal and shale bed samples collected from 2 km below the seafloor during Integrated Ocean Drilling Program Expedition 337. Microorganisms from the shale and coal were capable of metabolizing methylated substrates, including methylamine and methanol, when incubated at their in situ temperature of 45 °C, but had exceedingly slow growth, with biomass generation times ranging from less than a year to hundreds of years as measured by the passive tracer deuterated water. The past decade of scientific ocean drilling has revealed seemingly ubiquitous, slow-growing microbial life within a range of deep biosphere habitats. Integrated Ocean Drilling Program Expedition 337 expanded these studies by successfully coring Miocene-aged coal beds 2 km below the seafloor hypothesized to be “hot spots” for microbial life. To characterize the activity of coal-associated microorganisms from this site, a series of stable isotope probing (SIP) experiments were conducted using intact pieces of coal and overlying shale incubated at in situ temperatures (45 °C). The 30-month SIP incubations were amended with deuterated water as a passive tracer for growth and different combinations of 13C- or 15N-labeled methanol, methylamine, and ammonium added at low (micromolar) concentrations to investigate methylotrophy in the deep subseafloor biosphere. Although the cell densities were low (50–2,000 cells per cubic centimeter), bulk geochemical measurements and single-cell–targeted nanometer-scale secondary ion mass spectrometry demonstrated active metabolism of methylated substrates by the thermally adapted microbial assemblage, with differing substrate utilization profiles between coal and shale incubations. The conversion of labeled methylamine and methanol was predominantly through heterotrophic processes, with only minor stimulation of methanogenesis. These findings were consistent with in situ and incubation 16S rRNA gene surveys. Microbial growth estimates in the incubations ranged from several months to over 100 y, representing some of the slowest direct measurements of environmental microbial biosynthesis rates. Collectively, these data highlight a small, but viable, deep coal bed biosphere characterized by extremely slow-growing heterotrophs that can utilize a diverse range of carbon and nitrogen substrates.