Miracle-dz/UniFAR-FTUs huggingface dataset:
Resilient consensus for multi-agent systems with quantized communication

In this paper, we investigate the resilient consensus problem for multi-agent systems with quantized communication. We assume that each agent in the network can only exchange quantized information with its neighbors. A novel quantized-data based secure control law with built-in security mechanism is proposed to achieve consensus in the presence of attack agents. It is shown that for a directed network, as long as the number of attack nodes is bounded in each node' neighborhood, the consensus can be achieved with a given sufficient network connectivity. Finally, we offer a numerical example to demonstrate the validity of the derived results.
The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface tem- perature (SST) anomalies on interannual to decadal variabil- ity of South American precipitation. Two ensembles com- posed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the en- sembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of re- producibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the sum- mer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal vari- ance, which makes it a difficult phenomenon to predict. Al- ternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that as- sociated with the El Ni ˜ no - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the inten- sity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, how- ever, are confounded by the large internal variance in the re- gion. During MAM and JJA, the South Atlantic SST anoma- lies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.
Educational Research: A Personal and Social Process

Sources for thinking about and doing new paradigm research are reviewed. The discussion includes a large variety of nontraditional approaches that directly address the role of subjectivity and consensus in research. Sources include literature on traditional research methods, qualitative methods, humanistic psychology, and action research. The review is organized in terms of the personal and social processes that affect an investigator, including a consideration of how our construction of reality depends on the methods of study we choose.
MPI-INF at the NTCIR-11 Temporal Query Classification Task

MPI-INF participated in the Temporal Query Intent Classication Task (TQIC) of the Temporalia track at NTCIR11. This paper describes our approach to address this specic task. Our overall strategy has been to rely on established o-the-shelf components (e.g., standard classiers from Weka and natural language processing methods from Stanford CoreNLP) and focus on feature engineering. Devised features include surface (e.g.,n-grams), linguistic (e.g., capturing whether the query is a question), and temporal (e.g., statistics about publication dates and temporal expressions). We provide details on their precise denition and report on their eectiveness.
Distortion optimization in enriched video traces for End-to-End video quality enhancement

Video compression and streaming over lossy wireless networks is the current trend in telecommunication and encouraged by major carriers to increase their services portfolio. However, the technological challenges are still tackled to enable the delivery of high quality video. In our previous work, we developed a per stream distortion model that is based on the extended Gilbert model. We expanded our definition of the verbose video trace file with embedded coefficients derived from our distortion model. These coefficients are video quality descriptors that we associate with Quality of Service parameters that are measured in real-simulation time. In this work, we devise an optimization algorithm that is based on the distortion model to enhance the received video quality in End-to-End (E2E) communications. Our optimization algorithm is tested in multiple simulations to verify its validity. We report the results from our simulations that indicate significant improvements when this optimization algorithm is deployed in Edge Routers in conjunction with our video stream distortion coefficients and network metrics.
Factor Analysis of the Preschool Behavioral and Emotional Rating Scale for Children in Head Start Programs

Strength-based assessment of behaviors in preschool children provides evidence of emotional and behavioral skills in children, rather than focusing primarily on weaknesses identified by deficit-based assessments. The Preschool Behavioral and Emotional Rating Scales (PreBERS) is a normative assessment of emotional and behavioral strengths in preschool children. The PreBERS has well-established reliability and validity for typically developing children as well as children with identified special education needs, but this has not yet been established for children in Head Start programs, who tend to be at high risk for development of emotional and behavioral concerns. This study explores the factorial validity of the PreBERS scores for a large sample of children participating in Head Start programs around the United States. Results not only confirm the fit of the four-factor model of the PreBERS for this population, but also demonstrate the application of a bifactor model to the structure of the PreBERS which, in turn, allows for the computation of model-based reliability estimates for the four subscales (Emotional Regulation, School Readiness, Social Confidence, Family Involvement) and overall strength index score. The implications suggest that the PreBERS items are reliable scores that can be used to identify behavioral strengths in preschool children in Head Start, and support planning of interventions to selectively address component skills to promote child social and academic success.
Decomposition-Based Transfer Distance Metric Learning for Image Classification

Distance metric learning (DML) is a critical factor for image analysis and pattern recognition. To learn a robust distance metric for a target task, we need abundant side information (i.e., the similarity/dissimilarity pairwise constraints over the labeled data), which is usually unavailable in practice due to the high labeling cost. This paper considers the transfer learning setting by exploiting the large quantity of side information from certain related, but different source tasks to help with target metric learning (with only a little side information). The state-of-the-art metric learning algorithms usually fail in this setting because the data distributions of the source task and target task are often quite different. We address this problem by assuming that the target distance metric lies in the space spanned by the eigenvectors of the source metrics (or other randomly generated bases). The target metric is represented as a combination of the base metrics, which are computed using the decomposed components of the source metrics (or simply a set of random bases); we call the proposed method, decomposition-based transfer DML (DTDML). In particular, DTDML learns a sparse combination of the base metrics to construct the target metric by forcing the target metric to be close to an integration of the source metrics. The main advantage of the proposed method compared with existing transfer metric learning approaches is that we directly learn the base metric coefficients instead of the target metric. To this end, far fewer variables need to be learned. We therefore obtain more reliable solutions given the limited side information and the optimization tends to be faster. Experiments on the popular handwritten image (digit, letter) classification and challenge natural image annotation tasks demonstrate the effectiveness of the proposed method.
Adaptive Galerkin Finite Element Methods for the Wave Equation

Abstract This paper gives an overview of adaptive discretization methods for linear second-order hyperbolic problems such as the acoustic or the elastic wave equation. The emphasis is on Galerkin-type methods for spatial as well as temporal discretization, which also include variants of the Crank-Nicolson and the Newmark finite difference schemes. The adaptive choice of space and time meshes follows the principle of \goaloriented" adaptivity which is based on a posteriori error estimation employing the solutions of auxiliary dual problems.
Historical Demography of an Endangered Salamander, Ranodon sibiricus (Amphibia, Urodela, Hynobiidae): A Reassessment

Chinese populations of the endangered Siberian salamander Ranodon sibiricus are reported to have diverged only about 120 years ago, and to have the lowest genetic diversity of any amphibian. However, these conclusions require verification, as the main range of the species is in Kazakhstan. Moreover, the generation time used for estimating divergence time has a weak ground. In order to clarify these problems, we investigated the molecular phylogenetic relationship and historical demography of the species covering its whole distribution range using the mitochondrial DNA region reported for Chinese population (1072 bp sequences of the control region), while conducting skeletochronological analysis to estimate accurate generation time. As a result, the range expansion was estimated at 88,000–50,000 YA, based on the generation time of 6–10 years. Degree of intraspecific genetic differentiation is actually very small, but, as a single species, is not so small as had been reported for Chinese population alone.
Image-based modeling and lighting

Perhaps the most prominent thread in the development of computer graphics has been the pursuit of photorealistic imagery. Starting from the vector graphics of the 1960s, the graphics community has developed progressively more advanced display hardware, geometr ic representat ions, surface reflectance models and i l lumination algorithms, and by the 1990s photoreal is t ic rendering has become a part of traditional computer graphics. While photorealistic renderings can now be achieved wi th t rad i t iona l computer graphics, they general ly do not come easily. First, creating realistic models is a time and talent-intensive task.With most software, the artist needs to build a detailed model piece by piece, and then specify the reflectance characteristics (color, texture, speculari~/, etc.) for all the various surfaces in the scene. Second, generating photorealistic renderings requires advanced techniques such as radiosity and global illumination, which tend to be very computationally intensive. In brief, model ing tends to be hard, and rendering is slow. For applications such as interior design, architectural planning, simulation, virtual museums and cultural heritage, the objects and environments that one wishes to render using the computer often exist within the real wor ld . In such cases, the model ing and rendering challenges increase considerably: since people are famil iar with what the results should look like, they will have higher expectations of the quality of the results. However, objects and environments in the real world have a very useful property as well: they can be photographed.Additionally, a great deal of research has been done in the last several years to model the geometry and appearance of objects and scenes from photographs. Computer vision concerns the development of algorithms to derive various sorts of information from digital images. The process of recover ing 3D structure f rom 2D photographs, now known as image-based modeling, has been one of its central endeavors. Conversely, the process of photorealistically rendering objects and scenes from images and geometry is known as image-based rendering. As the models come from photographs, modeling need not be hard, and since the shading also comes f rom the images, rendering need not be slow. In the next few sections, I'll discuss a number of image-based modeling techniques and some projects that have used them in conjunction with image-based rendering.
Privately Matching k-mers

We construct the first noninteractive protocols for several tasks related to private set intersection. We provide efficient protocols for three related problems, each motivated by a particular kind of genomic testing. Set intersection with labelling hides the intersecting set itself and returns only the labels of the common elements, thus allowing a genomics company to return diagnoses without exposing the IP of its database. Fuzzy matching with labelling extends this to allow matching at a particular Hamming distance, which solves the same problem but incorporates the possibility of genetic variation. Closest matching returns the item in the server’s database closest to the client’s query this can be used for taxonomic classification. Our protocols are optimised for the matching of k-mers (sets of k-length strings) rather than individual nucleotides, which is particularly useful for representing the short reads produced by next generation sequencing technologies.
Bounding Volumes for Proteins: A Comparative Study

A chain tree is a data structure for representing changing protein conformations. It enables very fast detection of clashes and free potential energy calculations. The efficiency of chain trees is closely related to the bounding volumes associated with chain tree nodes. A protein subchain associated with a node of a chain tree will clash with another subchain only if their bounding volumes intersect. It is therefore essential that bounding volumes are as tight as possible while intersection tests can be carried out efficiently. We compare the performance of four different types of bounding volumes in connection with the rotation of protein bonds. It is observed that oriented bounding boxes are not as good as could be expected judging by their extensive use in various applications. Both rectangular- and line-swept spheres are shown to have very good tightness of fit but the line-swept, or even simple spheres, are shown to be significantly faster because of quick overlap checks. We also investigate how the performance of the recently introduced adjustable chain trees is affected by different bounding volume types.
Research on the control method for high speed locomotion legged robot

In the field of legged robot, the researchers are no longer satisfied with the robot walking at low speed, and pursue more dynamic high speed locomotion. Based on the SLIP model, the paper analyzed the relationship between the leg impedance and the velocity of the robot, and obtained the rule between the impedance parameters and the velocity, the high-speed locomotion of the robot was realized by the impedance control based on force. The correctness of control algorithm is proved through the results of simulation experiments. Finally, the experiment platform of high speed locomotion was built, and the correctness and effectiveness of the active compliance control algorithm based on impedance control was further verified by the high speed impedance running experiment.
Systematic population-based assessment of cancer risk in first-degree relatives of cancer probands.

BACKGROUND Cancer has long been recognized to have a familial component. Elevated risks for cancers at the same site for relatives of cancer probands have been reported for both common cancers and a number of the rarer cancer sites. For a particular cancer site, however, the estimated risks to relatives have varied considerably depending on criteria for selection of probands, how cancers were determined in relatives, and overall study design. Not surprisingly, the estimated risks of other cancers in relatives of probands with cancer at a given site have been subject to even more variation. PURPOSE The aim of this study was to use the Utah Population Database resource to systematically study familial clustering of 28 distinct cancer site definitions among first-degree relatives (parents, siblings, and off-spring) of cancer probands. METHODS We estimated familial relative risks from the Utah Population Database by identifying all cases of cancer in these first-degree relatives. These observed values were compared with those expected based on cohort-specific internal rates calculated from 399,786 relatives of all individuals in the Utah Population Database known to have died in Utah. RESULTS All sites showed an excess of cancers of the same site among relatives, with thyroid and colon cancers and lymphocytic leukemia showing the highest familial risks. When the analyses were restricted to cases with early ages at diagnosis, increased familial components for most cancer sites became evident. A significant difference in familial relative risk (FRR) between male (FRR = 4.04; 95% confidence interval [CI] = 3.13-5.07) and female (FRR = 2.24; 95% CI = 1.54-3.08) probands was found for colon cancer. Highly significant familial associations (one-sided; P < .001) were found among breast, colon, and prostate cancers and between breast and thyroid cancers. Statistically significant (one-sided, P < .01) associations were also found between tobacco-associated sites (lung, larynx, lip, and cervix). CONCLUSIONS This study represents a unique comprehensive population-based study of familial cancer. The familial associations reported here will be useful in generating hypotheses about specific genetic and environmental factors that can be tested in genetic linkage and case-control studies.
Tree-based model for breast cancer prognostication.

PURPOSE To define prognostic groups for recurrence-free survival in breast cancer, assess relative effects of prognostic factors, and examine the influence of treatment variations on recurrence-free survival in patients with similar prognostic-factor profiles. PATIENTS AND METHODS We analyzed 1,055 patients diagnosed with stage I-III breast cancer between 1990 and 1996. Variables studied included socioeconomic factors, tumor characteristics, concurrent medical conditions, and treatment. The primary end point was recurrence-free survival (RFS). Multivariable analyses were performed using recursive partitioning and Cox proportional hazards regression. RESULTS The most significant difference in prognosis was between patients with fewer than four and those with at least four positive nodes (P <.0001). Four distinct prognostic groups (5-year RFS, 97%, 78%, 58%, and 27%) were developed, defined by the number of positive nodes, tumor size, progesterone receptor (PR) status, differentiation, race, and marital status. Patients with fewer than four positive nodes and tumor < or = 2 cm, PR positive, and well or moderately differentiated had the best prognosis. RFS in this group was unaffected by type of adjuvant therapy (P =.38). Patients with at least four positive nodes and PR-negative tumors had the worst prognosis, and those treated with tamoxifen plus chemotherapy had the best outcome in this group (P =.0001). Among patients in the two intermediate-risk groups, those treated with tamoxifen or a combination of tamoxifen and chemotherapy had the best outcome. CONCLUSION Lymph node status, PR status, tumor size, differentiation, race, and marital status are valuable for prognostication in breast cancer. The prognostic groups derived can provide guidance for clinical trial design, patient management, and future treatment policy.
Ethnocentrism and Causal Attribution in a South Indian Context

Hindu Ss were asked to attribute the behavior of in-group (Hindu) and out-group (Muslim) members performing socially desirable or undesirable acts in terms of internal and external causes for the behavior. Subjects made internal attributions of in-group members performing socially desirable acts and external attributions for undesirable acts. The converse was true for attributions made by the Hindu Ss with respect to the same behavior performed by Muslims. The results were discussed in terms of the importance of attribution theory principles for studying prejudice and the relationship between attitudes and behavior.
Transcription Factor ATF2 Cooperates with v-Jun To Promote Growth Factor-Independent Proliferation In Vitro and Tumor Formation In Vivo

ABSTRACT ATF2 belongs to the bZIP family of transcription factors and controls gene expression via 8-bp ATF/CREB motifs either as a homodimer or as a heterodimer—for instance, with Jun—but has never been shown to be directly involved in oncogenesis. Experiments were designed to evaluate a possible role of ATF2 in oncogenesis in chick embryo fibroblasts (CEFs) in the presence or absence of v-Jun. We found that (i) forced expression of ATF2 cannot alone cause transformation, (ii) overexpression of ATF2 plus v-Jun specifically stimulates v-Jun-induced growth in medium with a reduced amount of serum, and (iii) the efficiency of low-serum growth correlates with the activity of a Jun-ATF2-dependent model promoter in stably transformed CEFs. Analysis of ATF2 and Jun dimerization mutants showed that the growth-stimulatory effect of ATF2 is likely to be mediated by v-Jun–ATF2 heterodimers since (i) v-Jun-m1, a mutant with enhanced affinity for ATF2, induces growth in low-serum medium much more efficiently than v-Jun, when expressed alone or in combination with ATF2; and (ii) ATF2/fos, a mutant that efficiently binds to v-Jun but is unable to form stable homodimers, shows enhanced oncogenic cooperation with v-Jun. In addition, we examined the role of ATF2 in tumor formation by subcutaneous injection of CEFs into chickens. In contrast to v-Jun, v-Jun-m1 gave rise to numerous fibrosarcomas while coexpression of ATF2 and v-Jun-m1 led to a dramatic development of fibrosarcomas visible within 1 week. Together these data demonstrate that overexpressed ATF2 potentiates the ability of v-Jun-transformed CEFs to grow in low-serum medium in vitro and contributes to the formation of tumors in vivo.
Toward an ontology-enhanced information filtering agent

Whereas search engines assist users in locating initial information sources, often an overwhelmingly large number of ULRs is returned, and the task of browsing websites rests heavily on users. The contribution of this work is developing an information filtering agent (IFA) that assists users in identifying out-of-context web pages and rating the relevance of web pages. An IFA determines the relevance of web pages by adopting three heuristics: (i) detecting evidence phrases (EP) constructed from WORDNET's ontology, (ii) counting the frequencies of EP and (iii) considering the nearness among keywords. Favorable experimental results show that the IFA's ratings of web pages are generally close to human ratings in many instances. The strength and weaknesses of the IFA are also discussed.