Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelet analysis and classification of Mitral regurgitation and normal heart sounds based on artificial neural networks

The application of wavelet transform for the heart sounds signal is described. The performance of integral wavelet transform and discrete wavelet transform for heart sounds analysis is discussed. The features from heart sounds were obtained from integral wavelet transform and used to train and test the artificial neural networks (ANN). The ANN was trained by 125 training data and tested with 52 data. The classification accuracy is 94.2%.
A Simple Decomposition Scheme for Large Real World Qualitative Constraint Networks

We improve the state-of-the-art in checking the satisfiability of large real world qualitative constraint networks (QCNs), by exploiting the loosely connected structure of their underlying graphs. We propose a simple decomposition scheme that retrieves the smaller QCNs that correspond to the biconnected component subgraphs of the underlying graph of a given large QCN, and show that our approach is sound for a qualitative constraint language that has a particular constraint property for atomic QCNs, namely, patchwork. Experimental evaluation shows that state-of-the-art reasoners can significanlty benefit from adopting this approach.
Predicting Hospitalization for Heat-Related Illness at the Census-Tract Level: Accuracy of a Generic Heat Vulnerability Index in Phoenix, Arizona (USA)

Background Vulnerability mapping based on vulnerability indices is a pragmatic approach for highlighting the areas in a city where people are at the greatest risk of harm from heat, but the manner in which vulnerability is conceptualized influences the results. Objectives We tested a generic national heat-vulnerability index, based on a 10-variable indicator framework, using data on heat-related hospitalizations in Phoenix, Arizona. We also identified potential local risk factors not included in the generic indicators. Methods To evaluate the accuracy of the generic index in a city-specific context, we used factor scores, derived from a factor analysis using census tract–level characteristics, as independent variables, and heat hospitalizations (with census tracts categorized as zero-, moderate-, or high-incidence) as dependent variables in a multinomial logistic regression model. We also compared the geographical differences between a vulnerability map derived from the generic index and one derived from actual heat-related hospitalizations at the census-tract scale. Results We found that the national-indicator framework correctly classified just over half (54%) of census tracts in Phoenix. Compared with all census tracts, high-vulnerability tracts that were misclassified by the index as zero-vulnerability tracts had higher average income and higher proportions of residents with a duration of residency < 5 years. Conclusion The generic indicators of vulnerability are useful, but they are sensitive to scale, measurement, and context. Decision makers need to consider the characteristics of their cities to determine how closely vulnerability maps based on generic indicators reflect actual risk of harm. Citation Chuang WC, Gober P. 2015. Predicting hospitalization for heat-related illness at the census-tract level: accuracy of a generic heat vulnerability index in Phoenix, Arizona (USA). Environ Health Perspect 123:606–612; http://dx.doi. org/10.1289/ehp.1307868
Adoptive immunotherapy for indolent non-Hodgkin lymphoma and mantle cell lymphoma using genetically modified autologous CD20-specific T cells.

Adoptive immunotherapy with T cells expressing a tumor-specific chimeric T-cell receptor is a promising approach to cancer therapy that has not previously been explored for the treatment of lymphoma in human subjects. We report the results of a proof-of-concept clinical trial in which patients with relapsed or refractory indolent B-cell lymphoma or mantle cell lymphoma were treated with autologous T cells genetically modified by electroporation with a vector plasmid encoding a CD20-specific chimeric T-cell receptor and neomycin resistance gene. Transfected cells were immunophenotypically similar to CD8(+) effector cells and showed CD20-specific cytotoxicity in vitro. Seven patients received a total of 20 T-cell infusions, with minimal toxicities. Modified T cells persisted in vivo 1 to 3 weeks in the first 3 patients, who received T cells produced by limiting dilution methods, but persisted 5 to 9 weeks in the next 4 patients who received T cells produced in bulk cultures followed by 14 days of low-dose subcutaneous interleukin-2 (IL-2) injections. Of the 7 treated patients, 2 maintained a previous complete response, 1 achieved a partial response, and 4 had stable disease. These results show the safety, feasibility, and potential antitumor activity of adoptive T-cell therapy using this approach. This trial was registered at www.clinicaltrials. gov as #NCT00012207.
Clonal Selection Algorithm with Adaptive Mutation and Roulette Wheel Selection

In this paper, roulette wheel selection strategy and adaptive mutation operation were introduced to the basic immune clonal selection algorithm (ICSA) in order to overcome premature convergence and stagnation at the end stage of iterative optimization. The method was utilized to optimize two types of typical testing functions and the simulation results show that the algorithm can improve the ability of searching the global optimum and yield superior results compared with the basic immune clonal selection algorithm.
Branch-and-cut Algorithms for Integer Programming, Branch-and-cut

Branch-and-cut methods are exact algorithms for integer programming problems. They consist of a combination of a cutting plane method with a branch-and-bound algorithm. These methods work by solving a sequence of linear programming relaxations of the integer programming problem. Cutting plane methods improve the relaxation of the problem to more closely approximate the integer programming problem, and branch-and-bound algorithms proceed by a sophisticated divide and conquer approach to solve problems. The material in this entry builds on the material contained in the entries on cutting plane and branch-and-bound methods. Perhaps the best known branch-and-cut algorithms are those that have been used to solve traveling salesman problems. This approach is able to solve and prove optimality of far larger instances than other methods. Two papers that describe some of this research and also serve as good introductions to the area of branch-and-cut algorithms are [21, 32]. A more recent work on the branch-and-cut approach to the traveling salesman problem is [1]. Branch-and-cut methods have also been used to solve other combina-torial optimization problems; recent references include [8, 10, 13, 23, 24, 26]. For these problems, the cutting planes are typically derived from studies of the polyhedral combinatorics of the corresponding integer program. This enables the addition of strong cutting planes (usually facet defining inequalities), which make it possible to considerably reduce the size of the branch-and-bound tree. Far more detail about these strong cutting planes can be found elsewhere in this encyclopedia , for example in the entry on cutting plane methods for integer programming. Branch-and-cut methods for general integer programming problems are also of great interest It is usually not possible to efficiently solve a general integer programming problem using just a cutting plane approach, and it is therefore necessary to also to branch, resulting in a branch-and-cut approach. A pure branch-and-bound approach can be sped up considerably by the employment of a cutting plane scheme, either just at the top of the tree, or at every node of the tree. For general problems, the specialized facets used when solving a specific combinatorial optimization problem are not available. Some useful families of general inequalities have been developed; these include cuts based on knap-and Fenchel cutting planes [9]. All of these families of cutting planes are discussed in more detail later in this entry. The software packages MINTO [30] and ABACUS [28] implement branch-and-cut algorithms to solve integer programming problems. The …
Sequential Labeling with Latent Variables: An Exact Inference Algorithm and its Efficient Approximation

Latent conditional models have become popular recently in both natural language processing and vision processing communities. However, establishing an effective and efficient inference method on latent conditional models remains a question. In this paper, we describe the latent-dynamic inference (LDI), which is able to produce the optimal label sequence on latent conditional models by using efficient search strategy and dynamic programming. Furthermore, we describe a straightforward solution on approximating the LDI, and show that the approximated LDI performs as well as the exact LDI, while the speed is much faster. Our experiments demonstrate that the proposed inference algorithm outperforms existing inference methods on a variety of natural language processing tasks.
Architectural Patterns for Data Mediation in Web-centric Information Systems

For over two decades, Web-centric information management has considerably changed business processes of organisations in the private and public sector. The Web itself has emerged from a fairly static collection of hypertext documents to a dynamic network of objects providing information services, i.e., the socalled Object-Web [6]. Today, many organisations provide access to their information systems (IS) by means of Web services. Moreover, the Web is no longer restricted to traditional computing hardware but it invades the world of mobile and smart devices. We can identify three main waves in the evolution of Web-centric systems. The first wave had its peak in the mid 90’s; Organisations discovered the Web as an environment for marketing their products and publishing information to a growing community of users. The second, still ongoing wave has been focused on business-to-business e-commerce and federated Web services. The third wave of connectivity is on the horizon and targets the integration of “every-day-things” like cell phones, PDAs, and household appliances as Web clients based on emerging W3C standards like UDDI and SOAP. In this paper, we discuss a collection of general architectural patterns that can be applied to systematically building such “third generation” Web information systems. We then specialize these patterns with respect to current middleware solutions applied to a real world case study of a third generation Web IS in the domain of Health Care.
SOCIAL SECURITY: A FINANCIAL APPRAISAL ACROSS AND WITHIN GENERATIONS

This paper computes the expected present value of Social Security retirement benefits and taxes for households of different marital circumstances, incomes, and age cohorts. Also computed are the net gain or loss from participation in the system, the expected internal rate of return it offers various participants, and the marginal linkage between benefits and contributions. All computations are made for the 1985 Social Security and income tax laws. The general results are that Social Security offers vastly different terms to households in different circumstances. The net gain or loss varies by $ 200,000 and the real internal rate of return on contributions ranges from negative numbers to 6.3 percent for households of different ages, income levels, and marital status. These differences are far greater than the widely debated distributional effects of relevant income tax alternatives. We also find that there is a great deal of variance in the marginal linkage of benefits and taxes with most households facing a situation where the incremental present value of benefits is only zero to thirty cents per extra dollar of taxes paid.
Music tagging with Name that Tune ( tentative project name )

The results of this project have multiple applications. Determining optimal preview clips can help potential customers select music before purchasing it and also allow users to quickly scan through the pieces of a playlist to ensure continuity. Tagging music with its representative clip allows computers to present music search results to users in a more native, informative format than just words. Furthermore, search speed of music can become more competitive with text search if a computer only needs to analyze a representative clip of the music.
Efficient SLAM algorithm with hybrid visual map in an indoor environment

In this paper, we propose a scheme of generating a hybrid visual map for SLAM. The hybrid visual map has two levels of map representations: 1) the absolute map representation of highly distinctive visual planes via EKF- SLAM and 2) the relative map representation of dense visual features for each visual plane via sparse information filter update. The absolute map can maintain its global consistency by matching the visual plane, the group of visual features. It improves data association and reduces the number of landmarks against individual visual features. Moreover, the relative map can reconstruct a 3-D map of visual features efficiently without loosing dense visual information. The performance of the proposed method was verified by the experimental results of consistent hybrid visual maps in an indoor environment.
Cross-Cultural Leadership Intelligence: Recommendations for Kenya

All leaders can improve their cultural intelligence (CQ) and every country can modify cultural norms toward advancing economically. CQ enables more effective cross-cultural leadership in the global economy. Based on analysis of the literature, experiences and survey results, our CQ recommendations start with self-assessment as key to successful cross-cultural interactions. In cross-cultural situations one must start by slowing down in order to develop more keen abilities to reflect on behaviors in order to generalize from what one discovers. Mental model development and flexibility, psychological hardness, curiosity, strategic thinking, and motivation all direct enhanced leadership across cultures. Aspiring cross-cultural leaders need guidelines for improvement. To meet these needs this paper builds on multiple-intelligence, leadership and crossing cultures research in order to propose useful global leadership models. The paper’s original contributions are: 1) guidelines for enhancing and selecting cross-cultural leaders; and, 2) “starting” point-example precepts for boosting economic development in Kenya.
A Separation Result for Secure Communication

Alice wants to communicate securely to Bob in the presence of an eavesdropper Eve. There are two resources available to facilitate this. First, Alice, Bob (and Eve) have access to dependent source observations. Secondly, there is a noisy broadcast channel from Alice to Bob and Eve. Under this general source and channel setup, we are interested in three classes of problems. First, what is the secret key generation capacity, where Alice and Bob agree on a secret key to the exclusion of Eve? Secondly, what is the secure communication capacity where Alice wants to convey an independent secret message to Bob? Thirdly, what is the optimal joint secure communication capacity and attainable state distortion, where Alice wants to convey to Bob both her state (source) observation unsecurely, under a distortion constraint, and an independent secure message? While a complete characterization of these problems under general source and channel models remains open, we can fully characterize several interesting special cases. In a nutshell, these special cases involve those where either the sources or the channel are individually incapable of generating useful secret common randomness between Alice and Bob in the presence of Eve; i.e., one of the resources by itself is useless in generating a secret key. Interestingly, the solutions for these cases expose the optimality of a separation architecture at multiple scales. First, there is an optimal decoupling between the use of the correlated sources from the use of the noisy channel. Thus, when the latter is the useless resource, this separation implies that it can be abstracted away as a noiseless public bit-pipe of capacity equal to the capacity of the channel from Alice to Bob. Secondly, in this situation, for the secure communication problem, there is a separation in the use of this finite rate public bit-pipe between a key generation first-phase and a secure message transmission second-phase that uses the first-phase key as a one-time pad.
Potential for adaptive evolution at species range margins: contrasting interactions between red coral populations and their environment in a changing ocean

Studying population-by-environment interactions (PEIs) at species range margins offers the opportunity to characterize the responses of populations facing an extreme regime of selection, as expected due to global change. Nevertheless, the importance of these marginal populations as putative reservoirs of adaptive genetic variation has scarcely been considered in conservation biology. This is particularly true in marine ecosystems for which the deep refugia hypothesis proposes that disturbed shallow and marginal populations of a given species can be replenished by mesophotic ones. This hypothesis therefore assumes that identical PEIs exist between populations, neglecting the potential for adaptation at species range margins. Here, we combine reciprocal transplant and common garden experiments with population genetics analyses to decipher the PEIs in the red coral, Corallium rubrum. Our analyses reveal partially contrasting PEIs between shallow and mesophotic populations separated by approximately one hundred meters, suggesting that red coral populations may potentially be locally adapted to their environment. Based on the effective population size and connectivity analyses, we posit that genetic drift may be more important than gene flow in the adaptation of the red coral. We further investigate how adaptive divergence could impact population viability in the context of warming and demonstrate differential phenotypic buffering capacities against thermal stress. Our study questions the relevance of the deep refugia hypothesis and highlights the conservation value of marginal populations as a putative reservoir of adaptive genetic polymorphism.
System-Level Design Space Exploration Methodology for Energy-Efficient Sensor Node Configurations: An Experimental Validation

For sensor nodes deployed at small distances, computation energy along with radio energy determines the battery life. We have proposed a system-level design space exploration methodology in [1] for searching an energy-efficient error-correcting code (ECC). This methodology takes into account the computation and the radio energy in an integrated manner. In this paper, we validate this methodology by deploying the Imote2 nodes and measuring energy values under different operating modes, e.g., with and without ECC. In this process, we propose a validation framework and node energy model. Experimental results validate the methodology and show that with ECC we can save up to 14% transmitter energy under a certain set of conditions. The main contribution of this paper is that it establishes experimentally that our methodology is effective in exploration of various node configurations and finding an energy-efficient solution.
Integrative 3D recording methods of historic architecture Burg Hohenecken castle from southwest Germany

This paper explores the methodology and application of laser scanning and photogrammetric recording methods to a very complex castle ruin. These methods allow for exact measurements to be made and the production of 3D digital models of the structure in question. The models built from the respective data combine the measuring strength of laser scanning with the visual aesthetics of photogrammetry. The case study is the medieval castle Burg Hohenecken in the city of Kaiserslautern in southwest Germany. Once digitized as a 3D model, the castle can be virtually controlled and examined, providing an opportunity to determine the age and potentially to reconstruct the castle from the different periods of it construction and expansion. Future analyses will include the identification of the different stone types and ages from the different building phases, the viewsheds from each respective building phase and perhaps the discovery of structures which have been completely lost.
Health status, epidemiological profile and prospects: Eastern Mediterranean Region.

BACKGROUND This article aims at providing an overview of the current epidemiological situation in the heterogeneous Eastern Mediterranean Region (EMR). It is one in a series of eight articles appointed by the International Epidemiological Association to improve the epidemiological situation. METHODS Several resources were used to extract morbidity, mortality and risk factors data that contribute mostly to the burden of disease and highlight health inequalities. Medline search was used to estimate epidemiological publications output by country. Indexing status of Index Medicus for the Eastern Mediterranean (IMEMR) journals in Medline/PubMed was checked. A questionnaire was designed to collect data from epidemiological associations on type of work and workforce. Authors' knowledge and networks were used to get a perspective on the training, research and funding sources. RESULTS Large inequalities exist between EMR nations especially ones pertaining to social conflicts. The EMR age-standardized disability-adjusted life years rate per 1000 population is higher than the global one, with most contribution of communicable diseases in low- and middle-income countries (45%) and non-communicable diseases in high-income countries (64%). Iran and Pakistan have the highest number of publications from 1996-2012, but Kuwait has the highest rate of publications per 100,000 population. The majority of IMEMR journals are not indexed in Medline/PubMed. Masters in Public Health is the most common form of training. CONCLUSIONS Efforts are required to ameliorate the epidemiological situation. There is a dire need for health evidence-based policy change and for field training of epidemiologists.
Top-K high utility episode mining in complex event sequence

Mining high utility episodes in complex event sequences is an emerging topic in data mining. In utility mining, users set a minimum threshold and the episodes having higher utility than the threshold are reported. The utility framework introduced in episode mining provides more informative and usable knowledge as compared to frequent episode mining. However, it is diﬃcult for the user to set an appropriate minimum utility threshold. As the user cannot predict the count of mined episodes by the utility threshold, the number of reported episodes can vary hugely in accordance to the set threshold. To address this issue, in this thesis we propose an algorithm for mining Top-K high utility episode in complex event sequence. It discovers episodes with highest utility to ones with kth highest utility where the user can set the desired count of episodes, k. We also propose two diﬀerent strategies to reduce the search space by raising the minimum threshold eﬀectively. We conduct experiments on real dataset and show the eﬀectiveness of our approach.
Contact Geometry of Mesoscopic Thermodynamics and Dynamics

The time evolution during which macroscopic systems reach thermodynamic equilibrium states proceeds as a continuous sequence of contact structure preserving transformations maximizing the entropy. This viewpoint of mesoscopic thermodynamics and dynamics provides a unified setting for the classical equilibrium and nonequilibrium thermodynamics, kinetic theory, and statistical mechanics. One of the illustrations presented in the paper is a new version of extended nonequilibrium thermodynamics with fluxes as extra state variables.