Miracle-dz/UniFAR-FTUs huggingface dataset:
User-Adapted Clinical Decision Support Systems

Clinical Decision Support Systems (CDSSs) have been one of the challenging real-world applications of artificial intelligence techniques for decades. CDSSs built so far mainly deal with explicit medical knowledge, typically encoded into a knowledge base. The rationale is that medical personal knowledge may be updated or time constraints limit physicians’ ability to properly manage that knowledge. However, inter-user variability due to subjectivity in feature evaluation has been typically ignored when building clinical decision support systems. In some cases implicit medical knowledge can be important to share, especially for novices’ education. In this work we present an approach for building CDSSs facing this problem through different artificial intelligence techniques: a machine learning approach for a critiquing module and a case based reasoning approach for a consulting module. The purpose is to build a system accounting for the specific skill an expertise of the user, providing new or enough information to take
Clinical Associations of Human T-Lymphotropic Virus Type 1 Infection in an Indigenous Australian Population

Introduction In resource-poor areas, infectious diseases may be important causes of morbidity among individuals infected with the Human T-Lymphotropic Virus type 1 (HTLV-1). We report the clinical associations of HTLV-1 infection among socially disadvantaged Indigenous adults in central Australia. Methodology and Principal Findings HTLV-1 serological results for Indigenous adults admitted 1st January 2000 to 31st December 2010 were obtained from the Alice Springs Hospital pathology database. Infections, comorbid conditions and HTLV-1 related diseases were identified using ICD-10 AM discharge morbidity codes. Relevant pathology and imaging results were reviewed. Disease associations, admission rates and risk factors for death were compared according to HTLV-1 serostatus. HTLV-1 western blots were positive for 531 (33.3%) of 1595 Indigenous adults tested. Clinical associations of HTLV-1 infection included bronchiectasis (adjusted Risk Ratio, 1.35; 95% CI, 1.14–1.60), blood stream infections (BSI) with enteric organisms (aRR, 1.36; 95% CI, 1.05–1.77) and admission with strongyloidiasis (aRR 1.38; 95% CI, 1.16–1.64). After adjusting for covariates, HTLV-1 infection remained associated with increased numbers of BSI episodes (adjusted negative binomial regression, coefficient, 0.21; 95% CI, 0.02–0.41) and increased admission numbers with strongyloidiasis (coefficient, 0.563; 95% CI, 0.17–0.95) and respiratory conditions including asthma (coefficient, 0.99; 95% CI, 0.27–1.7), lower respiratory tract infections (coefficient, 0.19; 95% CI, 0.04–0.34) and bronchiectasis (coefficient, 0.60; 95% CI, 0.02–1.18). Two patients were admitted with adult T-cell Leukemia/Lymphoma, four with probable HTLV-1 associated myelopathy and another with infective dermatitis. Independent predictors of mortality included BSI with enteric organisms (aRR 1.78; 95% CI, 1.15–2.74) and bronchiectasis (aRR 2.07; 95% CI, 1.45–2.98). Conclusion HTLV-1 infection contributes to morbidity among socially disadvantaged Indigenous adults in central Australia. This is largely due to an increased risk of other infections and respiratory disease. The spectrum of HTLV-1 related diseases may vary according to the social circumstances of the affected population.
XIAP 3′-untranslated region as a ceRNA promotes FSCN1 function in inducing the progression of breast cancer by binding endogenous miR-29a-5p

The non-coding 3′-untranslated region (UTR) of genes play an important role in the regulation of microRNA (miRNA) functions, since it can bind and inactivate multiple miRNAs. Herein, we report that ectopic expression of XIAP 3′UTR increased human breast cancer cells proliferation, colony formation, migration, invasion and xenograft tumor growth and suppressed tumor cell death. To investigate this process, we further correlated the genome-wide transcriptional profiling with the gene expression alterations after transfecting XIAP 3′UTR in MCF-7 cells. We identified a robust, genome-wide mechanism of cell migration, motility and epithelial to mesenchymal transition by which mediated by a previously described cellular component movement factor FSCN1. Expression of XIAP and FSCN1 were up-regulated synergistically after transfecting XIAP 3′UTR in vitro and in vivo. Interactions between XIAP and FSCN1 appear to be a key determinant of these processes. Co-transfection with Dicer siRNA reversed the XIAP 3′UTR-mediated oncogenicity, suggesting the miRNAs might be involved in that process. Furthermore, we demonstrated that one miRNA, miR-29a-5p, can bind to both the XIAP and FSCN1 3′UTRs and play an important role in that interactions. We showed that the 3′UTR of XIAP was able to antagonize miR-29a-5p, and resulted in the increased translation of XIAP and FSCN1. Thus, our findings reveal important new insights into how XIAP 3′UTR works, suggesting that the non-coding XIAP 3′UTR serves as a competitor for miRNA binding and subsequently inactivates miRNA functions, by which XIAP 3′UTR frees the target mRNAs from being repressed.
The He II Emitting Nebula N44C in the Large Magellanic Cloud: Optical/Ultraviolet Spectroscopy of the Nebula and Its Ionizing Star

We present HST spectroscopy and imaging, along with new ground-based spectroscopy and ROSAT HRI imaging, of the He II emitting nebula N44C and its ionizing star. A GHRS spectrogram of the ionizing star yields a spectral type of about O7 for the star. The lack of P Cygni profiles for Si IV and C IV indicates that the star is not a supergiant. The nebular abundances in the ionized gas are consistent with average abundances for LMC H II regions, with the possible exception that nitrogen may be enhanced. Enrichment by a former evolved companion star is not evident. A long-slit echelle spectrogram in Hα + [N II] shows no evidence for high-velocity gas in N44C. This rules out high-velocity shocks as the source of the nebular He II emission. A 108 ks ROSAT HRI image of N44C shows no X-ray point source to a 3 σ upper limit LX < 1034 ergs s-1 in the 0.1-2.0 keV band. Based on new measurements of the electron density in the He II emitting region, we derive recombination timescales of ≈20 yr for He+2 and ≈4 yr for Ne+4. If N44C is a fossil X-ray ionized nebula, this places severe constraints on when the putative X-ray source could have turned off. The presence of strong [Ne IV] emission in the nebula is puzzling if the ionizing source has turned off. It is possible the system is related to the Be X-ray binaries, although the O star in N44C does not show Be characteristics at the present time. Monitoring of X-rays and He II emission from the nebula, as well as a radial velocity study of the ionizing star, are needed to fully understand the emission line spectrum of N44C.
SecuFone : Android Security Advisor Tejas Padliya

Android is one of the most popular mobile operating system (OS). Android is currently developed by the Google and other developers. It is an open source OS, based on the Linux kernel. Android can be used on smartphones, tablets, smartwatches and other devices. Android supports different types of applications, hardwares and firmwares. The Android operating system has different flavors and versions due to its open nature. This can lead to security and privacy concerns. Google Play Store is the most popular online app store for Android. As of 2015, more than 1.6 million applications have been listed on the Google Play Store [1]. In this project, I develop ‘SecuFone: Android Security Advisor’ an Android application. SecuFone evaluates the security of the overall system and provides advisory (recommendation) to improve their security. It evaluates security by using a hierarchical system. Hierarchical system uses fuzzy logic to provide users with the generalized score based on the metrics. The recommendations and score generated by the application helps users to enhance their privacy and security of their devices. General Terms: Experimentation, Measurement, Security, Theory
Pneumoconiosis's Gross Tissue Imaging Classification Based on Morphological Feature Description

Referring to pneumoconiosis's gross tissue imaging classification, it is fatal to know the importance of distinguishing lung nodule from macule and how many nodules and macule the pneumoconiosis's gross tissue image really get. in achieving the distinguishing and counting results, the morphology processing method and some auxiliary digital image processing methods are adopted. after processing, the statistic work begins. the statistic results of abundant candidate parameters give us the chance to pick the parameter performing extremely well. in that way, the classification of pneumoconiosis's gross tissue images is quite feasible.
ay 2 01 3 Semistability of Nonlinear Systems Having a Continuum of Equilibria and Time-Varying Delays

In this report, we develop a semistability analysis framewo rk f r nonlinear systems with bounded timevarying delays with applications to stability analysis of m ultiagent dynamic networks with consensus protocols in the presence of unknown heterogeneous time-varying dela ys along the communication links. We show that for such a nonlinear system having nonisolated equilibria, if the system asymptotically converges to a constant time-delay system and this new system is semistable, then th e original time-varying delay system is semistable. In proving our results, we extend the limiting differential equation approach to time-varying delay systems and also develop some new convergence results for functional di fferential equations.
Volitron: On a Psychodynamic Robot and Its Four Realities

This paper discusses the concept of Volitron - a controller to make its host robot increase its competence in such activities as self-initiated exploration of an environment, new goal acquisition, and planning/executing of actions while taking into account predicted behaviors of objects of interest. There are four key elements in Volitron's structure: a model of perceived reality, a model of desired reality, a model of ideal reality and a model of anticipated reality. The task of a robot's working memory includes producing images of the robot itself imitating another subject's activities and sending the images to a model of desired reality. A tension (a concept borrowed from psychoanalysis) arising from the differences between a perceived reality and a desired reality is a source of a motivation toward action. The final decision to take an action is based on a comparison of the model of anticipated reality with that of ideal reality. The interaction of Volitron's elements are described in the paper. Furthermore, a computational model of working memory (WM) and its psychological justification are provided.
Varun Gupta: Research Statement

My research interests are in developing theoretical foundations for designing and analyzing large-scale systems, such as data centers, and cloud computing infrastructures. With the increasing size of these systems, and the rapid deployment of data centers, trial and error or simulations are not viable building tools, and more than ever, there is a need for analytical tools to aid our understanding of these systems. My work combines stochastic modeling and analysis theory, optimization theory, and mechanism design to address these challenges. While there is a rich literature on analysis of large systems, the new constraints and opportunities presented by changing applications, as well as new performance metrics such as energy consumption, necessitate revisiting the classical tools and modernizing them.
2-D enhanced Hammerstein behavior model for concurrent dual-band power amplifiers

A two-dimensional enhanced Hammerstein (2-D EH) behavior model is proposed for accurate behavioral modeling capability of concurrent dual-band power amplifiers (PAs). The proposed model is based on the two-box modeling technique to alleviate the number of coefficient used in the model. Compared to the two-dimensional memory polynomial (2-D MP) model, the proposed model requires less coefficient, while maintaining the similar modeling performance, because the static nonlinearity and dynamic behavior are separately estimated. The modeling performances of the models are accessed in terms of the normalized mean square error and adjacent channel error power ratio. Moreover, the linearization capabilities of the models are compared by compensating the nonlinearities of the concurrent dual-band PA. In the experiment, the PA is excited by two wideband code division multiple access 1-FA signals at 1.8 GHz and 2.411 GHz. The modeling assessment and linearization performance clearly show that the proposed 2-D EH outperforms the 2-D MP.
The possible application of international accounting standards in China

This thesis is a single case study on Chinese accounting, the research question it attempts to answer is the possible application of international accounting standards in China. In order to answer the research question, it first studies the differences of contexts between international accounting and Chinese accounting, subsequently, from the perspective of conceptual framework, elucidates the dissimilarities between Chinese accounting and international accounting and the causes which bring about these differences. The final conclusion is that China has not yet possessed the necessary conditions for the application of international accounting standards.
Object Recognition Using Hierarchical SVMs

The paper deals with the object recognition problem. The objective is to localize and recognize the known objects in different orientations on cluttered background. As a learning tool we choose support vector machines (SVMs). To eliminate the problem caused by cluttered background we organize the image pixels in tree structures, which enable us to deal only with the object pixels. Both, one- and two-class SVMs are combined in the recognition process. One-class SVMs, used at the first stage, allow us to avoid the “nonobject” class generation as required by two-class SVM for object localization task. Two-class SVMs are applied to further resolve the recognition process when necessary. As demonstrated by experimental results the proposed method reduces the number of erroneously recognized objects.
Encouraging the Development of Renewable Energy: The Role of Cooperatives

The development of Renewable Energy (RE) has become a major societal challenge. Even though RE technology is improving fast, the general public has been slow to adopt it. Meanwhile many RE cooperatives have been created; they act as social entrepreneurs in utilizing the social capital of a community to engage the public. Thus, the purpose of this chapter is to consider how they can contribute to the adoption of RE. The author uses an exploratory research design with a multiple case approach drawing on nine RE cooperatives. The chapter discusses a number of actions implemented by cooperatives in order to develop the adoption of RE. These are related to the diminishing of the RE costs, the use of educational campaigns, and the setting of RE projects at local level; the specific status of cooperatives is another facilitating factor. The author concludes by drawing future directions for research and stressing the cultural challenges for the RE cooperative model.
Multi-objective evolutionary algorithm-based optimal posture control of humanoid robots

This paper proposes a multi-objective evolutionary algorithm-based optimal posture controller to generate an optimal trajectory of humanoid robots against external disturbance using an iterative linear quadratic regulator (ILQR) and concurrently optimize multiple performance criteria. As the dimensionality of nonlinear system increases, it is difficult to find the weighting matrices of cost function in ILQR. In the proposed method, this problem is solved by employing a multi-objective quantum-inspired evolutionary algorithm (MQEA) to obtain nondominated solutions of the weighting matrices generating various optimal trajectories that satisfy multiple performance criteria. Among numerous nondominated solutions generated from MQEA, fuzzy measure and fuzzy integral are employed for global evaluation by integrating the partial evaluation of each of them over criteria with respect to user's degree of consideration for each criterion. The effectiveness of the proposed method is verified by computer simulations for the problem of balancing the posture of a humanoid robot against external impulse force, where the robot is modeled by a four-link inverted pendulum.
Approximate Modularity

A set function on a ground set of size n is approximately modular if it satisfies every modularity requirement to within an additive error, approximate modularity is the set analog of approximate linearity. In this paper we study how close, in additive error, can approximately modular functions be to truly modular functions. We first obtain a polynomial time algorithm that makes O(n2 log n) queries to any approximately modular function to reconstruct a modular function that is O(√n)-close. We also show an almost matching lower bound: any algorithm world need super polynomially many queries to construct a modular function that is o(√(n/log n))-close. In a striking contrast to these near-tight computational reconstruction bounds, we then show that for any approximately modular function, there exists a modular function that is O(log n)-close.
The Price-Rate Duality: Theory of Basis Spreads

After the Subprime Crisis of 2007, basis spreads quoted for swaps and cross currency swaps rose. Until that moment, these spreads could be considered negligible from a pricing point of view and, as a consequence of this, valuation systems did not include these spreads as relevant variables. However, for as long as the size of these spreads did not return to the previous level, their impact in pricing had to be considered. The most standard model consists in the substitution of the interest rate curve by several rate curves depending on: either the tenors in order to estimate their forwards (for pricing basis swaps), or the currency chosen as local currency in order to estimate discount factors (for pricing cross currency swaps). The model proposed in this paper postulates the existence of a Price-Rate duality in the swap market in order to get a deeper understanding of this phenomenon. Furthermore, this model establishes a new way of reducing the number of curves that the multi-curve model needs.
(K0.5Na0.5)NbO3 based lead free piezoelectrics with expanded temperature usage range

Lead free materials 0.95(K0.5Na0.5)NbO3-0.05LiSbO3 modified by CaTiO3 (CT) (1¿3wt%) have been synthesized by conventional sintering. All samples exhibited pure perovskite phase with a tetragonal structure at room temperature. The Curie temperature was found to decrease with increasing CT addition in KNN-LS ceramics, while the orthorhombic to tetragaonl polymorphic phase transition was found to shift further downward from room temperature to lower than ¿50°C, expanding the temperature usage range. The piezoelectric coefficient d31 and electroemchanical coupling factor k31 for CT (1wt%) modified KNN-LS materials were found to be on the order of ¿90pC/N and ¿28.5% at room temperature, respectively, comparable to those values of pure KNN-LS. Together with its broadened temperature usage range, makes the CT modified materials promising candidates for sensor and transducer applications.
DWA TECHNIQUE TO IMPROVE DAC OF SIGMA-DELTA FRACTIONAL-N FREQUENCY SYNTHESIZER FOR WIMAX

A first order of DWA (Data Weighted Averaging) algorithm with third order sigma-delta modulator is proposed for application in sigma-delta fractional-N frequency synthesizer for WiMAX. In addition, this paper discusses the impact of mismatch between Digital-to-Analog convertor (DAC) unit elements. The simulation results show the effectiveness of the DWA technique in reduction of spurs, also DWA technique proves its ability to solve DAC unit elements mismatch. The fractional spur noise is converted into a broadband. Quantization noise with DWA is improved by – 10 dB if the element mismatch 0.01 and – 5 dB if the element mismatch 0.08 with 8 bit PFD/DAC. Matlab (V.7) program is used for simulation.
A Hybrid Collaborative Filtering Algorithm Based on User-Item

Collaborative filtering is one of the most important technologies in e-commerce recommendation system. Traditional similarity measure methods work poorly when the user rating data are extremely sparse. Aiming at this issue a hybrid collaborative filtering is proposed. This method used a novel similarity measure method to predict the target item rating and it fused the advantages of the user-based algorithm and item-based algorithm with the control factor α. The experimental results show that this improved algorithm obviously enhances the recommended accuracy, and provide better recommendation quality.
Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage and connectivity, little attention has been paid to the minimization of sensors' movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance of sensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. The combination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solution to the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently.