Miracle-dz/UniFAR-FTUs huggingface dataset:
Passivity analysis for uncertain signal processing systems

The problem of passivity analysis finds important applications in many signal processing systems such as digital quantizers, decision feedback equalizers and digital and analog filters. This paper considers the passivity analysis problem for a large class of systems which involve uncertain parameters, time delays, quantization errors, and unmodeled high order dynamics. By characterizing these and many other types of uncertainty using a general tool called integral quadratic constraints (IQCs), we present a solution to the problem of robust passivity analysis. More specifically, we determine if a given uncertain system is robustly passive. The solution is given in terms of the feasibility of a linear matrix inequality (LMI) which can be solved efficiently.
Measure observability by the generalized informational correlation

Informational correlation coefficient (ICC) can be used to measure the degree of observability for a system. In this paper, we define the generalized informational correlation coefficient (GICC), which is suitable for both discrete and continuous random variables. For the case in which the probability density functions (PDFs) are regularly supersummable, we obtain the exact value of GICC. Moreover, for the linear, stochastically autonomous system, we derive the explicit formula for the degree of observability, and prove the equivalence between the proposed measure and the traditional rank condition. Finally, a simple example is given to compare the discrete state case and the continuous state case.
pRoot: An Adaptable Wireless Sensor-Actuator Hardware Platform

The relative significance of available processing/memory resources and cost/power constraints for wireless sensor-actuator nodes depends on the application and use-case scenario. As an example, wireless automation applications usually have diverse processing/memory resource demands and energy constraints, and they bring forth development feasibility as one of the important decision criteria. For similar applications, adaptable platforms, supporting scaling between processing-memory resources and power consumption, and providing flexibility in use-case dependent hardware modifications are preferable. To the best of our knowledge, the available node platforms cannot be easily modified to support resource scaling and hardware flexibility simultaneously. In this paper, an adaptable node hardware architecture is introduced. The proposed platform can be utilized in several of roles for applications with diverse requirements, lowering the development-effort compared to alternative implementations. The practical problems of the architecture are elaborated and the details of their solutions are given. The feasibility of the introduced architecture is shown through an example implementation using off-the-shelf components, the pRoot node.
An XP Inspired Test-Oriented Life-Cycle Production Strategy for Building Embedded Biomedical Applications

The construction of embedded biomedical applications is an under explored topic. The status quo is for practitioners to utilize a production process which possesses no specific focus; meanwhile, the marketplace requires highly demanding characteristics from these products. The principal requirement is that most of these products need to be effectively defect free. This demands that the production process be directed towards this objective; and hence the focus of this paper is our initial attempts at designing and implementing such a process. Our new process is developed around transforming a subset of extreme programming from the world of desktop applications into a methodology for this new domain. The paper also discusses our experiences in developing test frameworks to support the domain and our objectives. Finally, the paper provides some pointers on our future plans for tackling the many unresolved issues that still exist in attempting to fully realize and support this new development process
GEOGRAPHIC VARIATION IN AVIAN INCUBATION PERIODS AND PARENTAL INFLUENCES ON EMBRYONIC TEMPERATURE

Abstract Theory predicts shorter embryonic periods in species with greater embryo mortality risk and smaller body size. Field studies of 80 passerine species on three continents yielded data that largely conflicted with theory; incubation (embryonic) periods were longer rather than shorter in smaller species, and egg (embryo) mortality risk explained some variation within regions, but did not explain larger differences in incubation periods among geographic regions. Incubation behavior of parents seems to explain these discrepancies. Bird embryos are effectively ectothermic and depend on warmth provided by parents sitting on the eggs to attain proper temperatures for development. Parents of smaller species, plus tropical and southern hemisphere species, commonly exhibited lower nest attentiveness (percent of time spent on the nest incubating) than larger and northern hemisphere species. Lower nest attentiveness produced cooler minimum and average embryonic temperatures that were correlated with longer incubation periods independent of nest predation risk or body size. We experimentally tested this correlation by swapping eggs of species with cool incubation temperatures with eggs of species with warm incubation temperatures and similar egg mass. Incubation periods changed (shortened or lengthened) as expected and verified the importance of egg temperature on development rate. Slower development resulting from cooler temperatures may simply be a cost imposed on embryos by parents and may not enhance offspring quality. At the same time, incubation periods of transferred eggs did not match host species and reflect intrinsic differences among species that may result from nest predation and other selection pressures. Thus, geographic variation in embryonic development may reflect more complex interactions than previously recognized.
Negotiation by abduction and relaxation

This paper studies a logical framework for automated negotiation between two agents. We suppose an agent who has a knowledge base represented by a logic program. Then, we introduce methods of constructing counter-proposals in response to proposals made by an agent. To this end, we combine the techniques of extended abduction in artificial intelligence and relaxation in cooperative query answering for databases. These techniques are respectively used for producing conditional proposals and neighborhood proposals in the process of negotiation. We provide a negotiation protocol based on the exchange of these proposals and develop procedures for computing new proposals.
An Efficient Algorithm for Finding Certain Minimum-Cost Procedures for Making Binary Decisions

This paper is concerned with a class of procedures for making true-false decisions which depend on the outcome of eo sequence of elementary, binary tests. Certain of these procedures, calJed s-procedures, are conveniently represented by Boolean expressions (whose variables represent the elementary, bil~ary tests) and are easily carried out. If we are given the cost of applying each elementary, bina.ry test and the (a priori) prob'~bility of its outcome, the (average) cost of a procedure may be computed. Th.e genera! problem treated is to find efficiently a minimum-cost procedure equiv,~dent to a given s-procedure with known costs and probabilities for its elementt~ry, binary tests. Among the facts proved are two theorems showing that, under certain1 coi~ditions, the s-procedure found by a specified , efficient algorithm has mhfimum cost. The theorems and the etticient algorithm are used to solve illustrative problems in ti, e areas of computer programming, solving mat}m-matical problems, personnel selection, and medical diagnosis.
Insulin-like growth factor-I, inflammatory proteins, and fibrosis in subjects with nonalcoholic fatty liver disease.

CONTEXT Inflammation may have a pathogenic role in the progression of nonalcoholic fatty liver disease (NAFLD); by contrast, the role of anti-inflammatory molecules has not been addressed. Low circulating levels of the anti-inflammatory molecule IGF-I have been described in subjects with NAFLD. OBJECTIVE The aim of the study was to elucidate the clinical significance of IGF-I in NAFLD and its relationship with inflammatory biomarkers and fibrosis. DESIGN AND SETTING We conducted a cross-sectional study and in vitro experiments on hepatic HepG2 cells at the Internal Medicine and Gastrointestinal and Liver Units of the Universities of Catanzaro and Palermo. SUBJECTS A total of 221 individuals with NAFLD diagnosed on ultrasonography (cohort 1) and 50 subjects with biopsy-proven NAFLD (cohort 2) participated in the study. INTERVENTION Liver ultrasonography was performed on cohort 1, and hepatic biopsies were obtained from cohort 2. MAIN OUTCOME MEASURES NAFLD fibrosis and Kleiner scores were calculated. IGF-I and inflammatory biomarker plasma concentrations were assessed with specific assays. In the in vitro study, real-time RT-PCR was used to assess the mRNA expression levels of acute-phase reactants. RESULTS In the first cohort, circulating IGF-I levels showed an inverse correlation with NAFLD fibrosis score and inflammatory biomarkers; similarly in the second cohort, liver IGF-I mRNA levels and the fibrosis score showed a negative relationship. Finally, we showed that IGF-I was able to directly modulate the expression of acute-phase reactants, decreasing C-reactive protein and fibrinogen levels and up-regulating albumin expression in HepG2 cells. CONCLUSIONS The present data suggest that evaluation of circulating IGF-I and proinflammatory markers might be useful to assess comprehensively the severity of the disease in individuals with NAFLD.
Subspace Clustering for Uncertain Data

Analyzing uncertain databases is a challenge in data mining research. Usually, data mining methods rely on precise values. In scenarios where uncertain values occur, e.g. due to noisy sensor readings, these algorithms cannot deliver highquality patterns. Beside uncertainty, data mining methods face another problem: high dimensional data. For finding object groupings with locally relevant dimensions in this data, subspace clustering was introduced. For high dimensional uncertain data, however, deciding whether dimensions are relevant for a subspace cluster is even more challenging; thus, approaches for effective subspace clustering on uncertain databases are needed. In this paper, we develop a method for subspace clustering for uncertain data that delivers high-quality patterns; the information provided by the individual distributions of objects is used in an effective manner. Because in uncertain scenarios a strict assignment of objects to single clusters is not appropriate, we enrich our model with the concept of membership degree. Subspace clustering for uncertain data is computationally expensive; thus, we propose an efficient algorithm. In thorough experiments we show the effectiveness and efficiency of our new subspace clustering method.
Keberterimaan Situs Pajak: Pengindusian Orientasi Tujuan Pembelajaran dan Norma Subyektif

This study investigates a new IS success model that predicts the net benefits of tax consultans’ works especially in Indonesia by inducing learning goal orientation and subjective norms. This research investigates initially the basic IS success model (DeLone dan McLean, 1992) using system quality, information quality, intention to use and net benefits. This study induces stepwisely learning goal orientation and subjective norms to this model to predict net benefits improvement of the IS success model. This study suggests that system quality and information quality enhance intention to use and users’ satisfaction, then they could make net benefits. This study finds low goodness of fit level of the basic model. The inducement of learning goal orientation to the basic model did not improve the level, neither did subjective norms. It means that tax information systems in Indonesia are still far from the IS that could be used as decision support systems or expert systems tools.
Estimating operator norms using covering nets

We present several polynomial- and quasipolynomial-time approximation schemes for a large class of generalized operator norms. Special cases include the 2→q norm of matrices for q>2, the support function of the set of separable quantum states, finding the least noisy output of entanglement-breaking quantum channels, and approximating the injective tensor norm for a map between two Banach spaces whose factorization norm through l^n_1 is bounded. These reproduce and in some cases improve upon the performance of previous algorithms by Brandao-Christandl-Yard and followup work, which were based on the Sum-of-Squares hierarchy and whose analysis used techniques from quantum information such as the monogamy principle of entanglement. Our algorithms, by contrast, are based on brute force enumeration over carefully chosen covering nets. These have the advantage of using less memory, having much simpler proofs and giving new geometric insights into the problem. Net-based algorithms for similar problems were also presented by Shi-Wu and Barak-Kelner-Steurer, but in each case with a run-time that is exponential in the rank of some matrix. We achieve polynomial or quasipolynomial runtimes by using the much smaller nets that exist in l_1 spaces. This principle has been used in learning theory, where it is known as Maurey's empirical method.
Robust Cross-Layer Design with Reinforcement Learning for IEEE 802.11n Link Adaptation

This paper proposes a link adaptation method for IEEE 802.11n, which can foresightedly co-optimize the modulation and coding scheme (MCS) in the PHY layer and the frame size in the MAC layer. The link adaptation method employs Markov decision process (MDP) for modeling this crosslayer design. By solving the MDP model with a reinforcement learning which does not require a prior knowledge about the wireless environment, the foresighted transmission strategy can be computed. The simulation results verify the proposed method and show that our proposed method can improve the goodput by 25% at most, compared with the MCS-oriented link adaptation method.
Texel programs for random-access antialiased vector graphics

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Suppression of Ongoing Experimental Autoimmune Encephalomyelitis by Neutralizing the Function of the p28 Subunit of IL-271

IL-27 is a recently defined family member of the long-chain, four-helix bundle cytokines, which consist of EBI3, an IL-12p40-related protein, and p28, an IL-12p35-related polypeptide. The role of IL-27 in the regulation of experimental autoimmune encephalomyelitis has never been studied. We show in this study that neutralizing the in vivo function of IL-27 by Abs against IL-27 p28 rapidly suppressed an ongoing long-lasting disease in C57BL/6 mice. These Abs were then used to determine the mechanistic basis of disease suppression. We show in this study that IL-27 is involved not only in the polarization of naive T cells undergoing Ag-specific T cell activation, but also in promoting the proliferation and IFN-γ production by polarized T cells, including the long term Th1 line that has been previously selected against the target encephalitogenic determinant. This may explain in part why neutralizing IL-27 suppresses an already established disease in a very rapid and significant manner.
A high-level view of Java applications

Static analysis of object-oriented applications has become widespread over the last decade, mainly in the context of compile-time optimizations. The paper describes how static analysis of virtual method calls can be employed to provide a high-level view of Java applications. The result is a method call graph that can be built from either source or bytecode, and a graphical browser that enables the user to analyze control flow and the coupling between classes and packages in an intuitive fashion, thereby supporting application design as well as refactoring and debugging. In order to achieve the necessary bijection between source and bytecode representations of classes, we implement a new approach based on source code pre-processing.
Weet in welke omgeving je eet. De invloed van muziek en kleur op eetgedrag.

Research on the influence of environmental variables show that music affects eating and drinking behavior. The music tempo affects the length of stay in a room and the amount of eating and drinking. Research shows that red color is the most associated color for restaurants, where they make references to famous restaurants with red interiors. Besides, it appears that a positive perception depends on the color of the interior. The examination of the use of color in the eating environment is scarce. This study asked the question: what effects music and color on the amount of food and drinking quantity? Are there differences between healthy and unhealthy choices for food and drink? Expectations are: in the slow music condition and in the blue walls condition people eat and drink more; and in the fast music condition and in the red walls condition people eat and drink less. In the first experiment, a single factor between subjects design (slow music condition, fast music condition and the control condition), compared 38 students. At group level the results show that in the control condition and in the slow music condition people ate more compared to the fast music condition. At the individual level similar significant differences were found in the eating behaviour. The results from the drinking behavior show that in the slow music condition people drank more than in the fast music condition. In the second experiment, also a single factor between subjects design (red walls condition, blue walls condition and the control condition), 39 athletes were compared. An important result in the color experiment is that in the control condition at group level more food was consumed than in de red wall condition. The individual level shows no significant differences in eating behavior. In the area of drinking are the main findings that in the blue walls condition people drank more. In summary, this means that music and color affect the amount of food and drink.
PocketPad: Using Handhelds and Digital Pens to Manage Data in Mobile Contexts

PocketPad is an information management system geared toward university students. The system is designed to support the capture, storage, browsing, editing and organization of handwritten notes via the complementary use of digital pens to capture information, handheld computers to browse and store prior information, and digital pens and handheld computers in combination to edit and organize information. Desktop computer software synchronizes the information from the digital pen and Pocket PC during editing and reorganization. Through the combined use of different hardware components supported by our software, we describe a system that bridges the paper-electronic information divide in mobile contexts. The system relies on human-in-the-loop techniques coupled with stroke timing to simplify coordination of content from different sources, rather than resorting to complex and often error-prone computer document recognition algorithms.
A cost-oriented reorganization reasoning for multiagent systems organization transitions

Current trends in the Multiagent Systems (MAS) researchcommunity, encourage to provide models able to de ne or-ganizations that can dynamically be adapted according tochanges in the environment or in the organization speci ca-tion. This dynamic adaptation involves modi cations in thestructure and behavior of a MAS, such as adding, removingor substituting components, that are done while the systemis running and without bringing it down [4]. The processthat changes an organization into a new one is commonlyknown as reorganization [5]. Most existing approaches for reorganization in MAS de neadaptation processes due to organizational changes. Some ofthese approaches propose solutions for reorganization whenchanges prevent the organization from satisfying current goals(such as when an agent leaves the organization) [3], otherapproaches focus reorganization as a process triggered bythe domain [11], but most of current approaches focus reor-ganization for achieving better utility [6, 10, 9].
Modified enzyme immunoassay for detecting Neisseria gonorrhoeae antigens

A commercial modification of an enzyme immunoassay (EIA) (Gonozyme; Abbott Laboratories, North Chicago, Ill.) for detection of Neisseria gonorrhoeae antigens was compared with conventional culturing. Specimens from males and females were collected at a sexually transmitted disease clinic; additional female specimens were collected at an obstetrics and gynecology clinic. EIA sensitivity and specificity for males were 100 and 98.6%, respectively (68 negative, 34 positive, 1 false-positive, and 0 false-negative). EIA sensitivity and specificity for female sexually transmitted disease clinic patients were 74.4 and 95.7%, respectively (66 negative, 29 positive, 3 false-positive, and 10 false-negative) EIA sensitivity and specificity for obstetrics and gynecology clinic patients were 100 and 99.2%, respectively (6 positive, 119 negative, 1 false-positive, and 0 false-negative). In female patients from whom multiple swab specimens were collected, the sequence of specimen collection and subsequent EIA analysis affected sensitivity.
Fast approximate subspace tracking (FAST)

A new fast and accurate algorithm for tracking singular values, singular vectors and the dimension of the signal subspace through an overlapping sequence of data matrices is presented. The accuracy of the algorithm approaches that of the Prony-Lanczos (PL) method with speed and accuracy superior to both the PAST and PASTd algorithms for moderate to large size problems. The algorithm is described for the special case of changes to two columns of the matrix prior to each update of principal singular vectors and values. Comparisons of speed and accuracy are made with the algorithms named above.