Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Coordinated Mobile Sensor Control Target Tracking in Multiple Wireless Sensor Networks

: Wireless Sensor Networks (WSNs) is highly distributed network of small, lightweight wireless nodes. It monitors the environment or system by measuring physical parameters such as temperature, pressure, humidity. A wireless sensor network is a collection of nodes organized into a cooperative network. The existing presented Mobile sensor controller is used to measure the mobile target signal’s time of arrival (TOA). It’s related to tracking signal-emitting purpose of mobile targets which is used to navigated mobile sensors based on signal reception. Mobile target’s position is unknown so that they acquire from TOA. Both the mobile target and mobile sensor are used to estimate their locations before they directing mobile sensor’s movement to follow their target. TOA measurements are easy to acquire the mobile target. However, in Distributed Coordinated Mobile Sensor Control Target Tracking (DCM-SCT) scheme provides the formulation work which is done through the control of multiple cooperating autonomous sensor platforms. The proposed work provides an intelligent mobile sensor platform with high level of state information to the behavior-based mobile target tracking control system. Sensors are considered as autonomous agents and sensor motion control are based on gradient control trace with the target helps to reduce tracking error. Multiple objective functions are allows to reactive control in complex environments with multiple constraints. Simulations were conducted to measure the performance of in terms of DCM-SCT which has Location privacy level, Number of latency per packets, delivery rate, average end to end delay and control packets.
Location awareness using Angle-of-arrival based circular-PD-array for visible light communication

LEDs (Light Emitting Diodes) are considered by many researcher to represent the next-generation lighting technology. Furthermore indoor LED lighting has a potential to converge with IT technology such as Visible Light Communication (VLC) based Location Awareness. In this paper, we suggest Angle of Arrival (AOA) estimation algorithm under VLC environment in order to find out the location of a light source (LED) using circular-PD-array. We propose truncated-weighting method in order to enhance the accuracy of estimated AOA. Through simulations, we confirm that the number of PDs in circular-PD-array affects the AOA estimation error performance of a light source. In addition, our proposed truncated-weighting scheme shows better AOA estimation performance than those of simple average and Max schemes. Based on AOA algorithms, we also investigate the performance indoor location estimation. As a consequence, we can final that our truncated scheme also shows better location awareness performance than other conventional ones.
A forgiving workplace: An investigation of forgiveness climate, individual differences and workplace outcomes

Although forgiveness has been studied for centuries, it is a relatively new area of study in organizational behavior. Organizational climate has a history of influencing individual behaviors. This dissertation considers how a climate of forgiveness may foster a willingness to forgive in individuals. A measure of forgiveness climate is developed and empirically examined. The results of this study support the hypothesis that a cohesive/supportive climate and a trustworthy/integrity climate relate to a climate of forgiveness. Furthermore, this study examines the effects of climate on willingness to forgive. A scenario-based scale to measure willingness to forgive workplace offenses is developed. Willingness to forgive is found to be positively related to job satisfaction and OCB. On the other hand, willingness to forgive was found to be negatively related to job stress and performance. Two individual differences, psychological collectivism and narcissism, were examined as moderators. However, their moderating effect was not supported by the analyses.
Visualizing bregman voronoi diagrams

Voronoi diagrams are fundamental geometric structures that partition the space into elementary regions of influence defining discrete proximity graphs and dually well-shaped Delaunay triangulations [Aurenhammer & Klein, 2000]. In this video, we explain and illustrate a recent generalization of Voronoi diagrams [Nielsen et al., 2007] to a wide class of distortion measures called Bregman divergences [Banerjee et al., 2005].
A Longitudinal Study of Income Differences in the Height-BMI Relation among U.S. Children Ages 6 to 14

ABSTRACT Previous work has shown a positive height-obesity association in U.S. children that is more pronounced in those from lower-income families than in those from higher-income families. That work has been limited to cross-sectional analysis. This study evaluates income differentials in the inter-temporal associations between childhood height and obesity in U.S. children ages 6 to 14. Pooled samples of 9,670 female and 10,110 male children from the U.S. Early Childhood Longitudinal Study—Kindergarten Cohort (ECLS-K) were evaluated in multilevel mixed effects models. The results indicated a modest height-income interaction such that the concurrent height-obesity association was weaker at higher incomes. This strengthened into adolescence for females and weakened for males. With respect to height growth, for lower-income males, being shorter before the typical start of the growth spurt (≈ 9 years) and experiencing faster later growth (between 11 and 14 years) were attributes less strongly associated with subsequent obesity. There were no indicated income interactions with height growth in females.
CMOS Circuit Speed and Buffer Optimization

An improved timing model for CMOS combinational logic is presented. The model is based on an analytical solution for the CMOS inverter output response to an input ramp. This model yields a better understanding of the switching behavior of the CMOS inverter than the step-response model by considering the slope of the input waveform. Essentially, the propagation delay is shown to be the sum of the step-response delay and an input dependent delay that may account for as much as 50-100 percent of the total delay. The matching between the ramp input and the characteristic input waveforms is shown to be easily performed for excellent agreement in output response and propagation delay. Even though the short-circuit current is neglected, its influence is shown to be small and may be corrected. As an example, the timing model is used to optimize CMOS output buffers for minimum delay. If the intrinsic output load capacitance is included in the model, the optimum tapering factor is shown to be not e but a value in the range 3-5 depending on process parameters and design style. Also, due to the input dependence of the propagation delay, the last inverter stage in the buffer should have a larger tapering factor than the other stages for minimum delay.
A noninvasive method for coronary artery diseases diagnosis using a clinically-interpretable fuzzy rule-based system

Background: Coronary heart diseases/coronary artery diseases (CHDs/CAD), the most common form of cardiovascular disease (CVD), are a major cause for death and disability in developing/developed countries. CAD risk factors could be detected by physicians to prevent the CAD occurrence in the near future. Invasive coronary angiography, a current diagnosis method, is costly and associated with morbidity and mortality in CAD patients. The aim of this study was to design a computer-based noninvasive CAD diagnosis system with clinically interpretable rules. Materials and Methods: In this study, the Cleveland CAD dataset from the University of California UCI (Irvine) was used. The interval-scale variables were discretized, with cut points taken from the literature. A fuzzy rule-based system was then formulated based on a neuro-fuzzy classifier (NFC) whose learning procedure was speeded up by the scaled conjugate gradient algorithm. Two feature selection (FS) methods, multiple logistic regression (MLR) and sequential FS, were used to reduce the required attributes. The performance of the NFC (without/with FS) was then assessed in a hold-out validation framework. Further cross-validation was performed on the best classifier. Results: In this dataset, 16 complete attributes along with the binary CHD diagnosis (gold standard) for 272 subjects (68% male) were analyzed. MLR + NFC showed the best performance. Its overall sensitivity, specificity, accuracy, type I error (α) and statistical power were 79%, 89%, 84%, 0.1 and 79%, respectively. The selected features were “age and ST/heart rate slope categories,” “exercise-induced angina status,” fluoroscopy, and thallium-201 stress scintigraphy results. Conclusion: The proposed method showed “substantial agreement” with the gold standard. This algorithm is thus, a promising tool for screening CAD patients.
Magneto-elastic oscillations of neutron stars: exploring different magnetic field configurations

We study magneto-elastic oscillations of highly magnetized neutron stars (magnetars) which have been proposed as an explanation for the quasi-periodic oscillations (QPOs) appearing in the decaying tail of the giant flares of soft gamma-ray repeaters (SGRs). We extend previous studies by investigating various magnetic field configurations, computing the Alfv´ en spectrum in each case and performing magneto-elastic simulations for a selected number of models. By identifying the observed frequencies of 28 Hz (SGR 1900+14) and 30 Hz (SGR 1806-20) with the fundamental Alfv´ en QPOs, we estimate the required surface magnetic field strength. For the magnetic field configurations investigated (dipole-like poloidal, mixed toroidal-poloidal with a dipole-like poloidal component and a toroidal field confined to the region of field lines closing inside the star, and for poloidal fields with an additional quadrupole-like component) the estimated dipole spin-down magnetic fields are between 8 10 14 G and 4 10 15 G, in broad agreement with spin-down estimates for the SGR sources producing giant flares. A number of these models exhibit a rich Alfv´ en continuum revealing new turning points which can produce QPOs. This allows one to explain most of the observed QPO frequencies as associated with magneto-elastic QPOs. In particular, we construct a possible configuration with two turning points in the spectrum which can explain all observed QPOs of SGR 1900+14. Finally, we find that magnetic field configurations which are entirely confined in the crust (if the core is assumed to be a type I superconductor) are not favoured, due to difficulties in explaining the lowest observed QPO frequencies (f . 30 Hz).
Comparison of a major heat-stable microtubule-associated protein in HeLa cells and 190-kDa microtubule-associated protein in bovine adrenal cortex.

A heat-stable microtubule-associated protein (MAP) with a molecular weight of 190,000, termed 190-kDa MAP, has been purified from bovine adrenal cortex (Murofushi, H. et al. (1986) J. Cell Biol. 103, 1911-1919). Immunoblotting experiments using an antibody against this MAP revealed that several kinds of culture cells derived from human tissues contain proteins with an apparent molecular weight of 180,000 reacting with the antibody. Indirect immunofluorescence microscopic observation of HeLa cells showed that the immunoreactive protein co-exists with microtubules, indicating that the protein is one of the HeLa MAPs. A heat-stable MAP with a molecular weight of 180,000, termed here HeLa 180-kDa MAP, was purified by the taxol-dependent procedure (Vallee, R.B. (1982) J. Cell Biol. 92, 435-442) and successive co-polymerization with brain tubulin. This protein was the most abundant MAP in HeLa cells, suggesting that the MAP is identical to the major HeLa MAP previously reported by Bulinski and Borisy (Bulinski, J.C. & Borisy, G.G. (1980) J. Biol. Chem. 255, 11570-11576) and Weatherbee et al. [1980) Biochemistry 19, 4116-4123). It was shown that, like bovine adrenal 190-kDa MAP, yet distinct from brain MAP2 and tau, purified HeLa 180-kDa MAP does not interact with actin filaments. This common characteristic of the two MAPs along with the same heat-stability strongly suggests that they are members of the same group of MAPs. The fact that HeLa 180-kDa MAP reacts with an antibody against bovine adrenal 190-kDa MAP means that they share common epitopes, in other words, common local amino acid sequences. However, the limited proteolytic patterns of the two MAPs with S. aureus V8 protease and chymotrypsin were distinct from each other, suggesting the presence of large differences in the overall primary structures between bovine adrenal 190-kDa MAP and HeLa 180-kDa MAP.
Presentation of a new gender dependent feature selection approach for diagnosis of Parkinson disease using speech signal processing

Parkinson, is the second most common neurodegenerative disease after Alzheimer and no absolute cure has yet been found for it; however, the progression rate can be lowered with early diagnosis. Minor voice disorders are the first symptoms of this disease and they appear in almost 90% of the patients. The aim of this article to find the features that can create more meaningful difference between healthy and patient with Parkinson (PWP). For this purpose a Gaussian mixture model (GMM) is proposed to rank features based on its separability for each specific gender. We have used an existing database consisting of 195 samples computing 132 dysphonia measures and selection 22 features that have the most accurate classification. We also achieve correct disease classification performance of 88.89% and 86.05% for male and female respectively using a kernel support vector machine classifier and applying only 4 extracted features from any gender.
Allograft transmission of hepatitis C during the window period: Weighing the new risks and costs in the era of donor shortage

Organ shortages have necessitated utilization of allografts from Public Health Service (PHS) increased risk deceased donors. Such organs are gifted by donors with proximate social risk factors for transmission of viral hepatitis and human immunodeficiency virus (HIV). 1 Such allografts are increasingly available with the current opioid epidemic, often from firsttime and naïve opiate users who are otherwise healthy, enhancing transmission risk and diminishing the sensitivity of pretransplant viral screening.2 A “window period” in which antibodies to hepatitis C (HCV) remain undetectable for several weeks following initial exposure affords an interval in which infection may elude screening serology. Two patients recently contracted “window period” infections at our center, posing implications for informed consent of potential recipients as well as treatment coverage by thirdparty payers (Table 1).
The Importance of NOT Learning from Experience

In this paper we argue that learning correctly from software development experience can be a difficult task and that, frequently, there is not enough information available to draw valid conclusions. In our opinion, a focus on how to learn from experience should include a focus on how to avoid incorrect learning from experience. This includes a focus on when we should not learn from experience. We have tried to transfer general findings from human judgement studies and other sources to a software context and, in particular, to an experience database context. We believe that it is especially important to avoid incorrect reasoning from experience when establishing experience databases to spread experience within an organisation. The lack of focus on how to avoid incorrect reasoning may be a major reason for, as far as we have observed, the lack of success of implementation of software development experience databases. If we cannot trust the contents of an experience database, or the contents do not lead to better judgement processes, then experience databases are not very useful. The remainder of this paper is organised as follows. Section 2 gives an example illustrating problems we face when attempting to learn from experience. Section 3 discusses typical learning from experience fallacies and techniques to avoid them. Section 4 concludes and describes further work.
Rawlsian altruism with perfect discrimination leads to social efficiency

ABSTRACT Recent studies draw attention on the highly specialized capacity of human beings in recognizing altruists versus cheaters in social interactions. These results hint at the existence of specialized abilities that support discriminating behavior in strategic interactions. In this paper, we explore the implications of discriminating behavior in the study of the indirect evolutionary selection of selfish versus altruistic motivations in the context of generic 2×2 base games, and in particular for coordination and cooperation scenarios. We find that inequality averse (Rawlsian) altruism can enforce under rather general conditions socially optimal outcomes, including cases where selfishness cannot, such as in prisoner’s dilemmas. Inequality seeking (Nietzschian) altruism in no case improves upon Rawlsian altruism in terms of social optimality of outcomes, and often does worse. In the cooperation scenario in particular, Nietzschean altruism never manages to implement the cooperative outcome. Under perfect discrimination, moreover, inequality averse (Rawlsian) altruism often evolves at the expense of selfishness. These results suggest that the development of sophisticated discrimination abilities may be strongly adaptive in supporting fairness-oriented forms of pro-sociality in humans in the context of social dilemmas and coordination problems.
Peak-to-average power ratio reduction versus digital pre-distortion in OFDM based systems

In this paper we evaluate the effect of applying peak-to-average power ratio (PAPR) reduction and digital pre-distortion (DPD) on radio frequency power amplifiers when an orthogonal frequency division multiplexing (OFDM) signal is used. The PAPR reduction method, presented as a convex problem, is based on reshaping the time domain signal by redistributing its energy in the frequency domain, with respect to constraints on in-band and out-of-band errors. The DPD method consists of modeling the behavior of the power amplifier using a parallel Hammerstein model, and then extracting its inverse parameters based on the indirect learning approach. The cases where PAPR and DPD are applied separately and combined, are studied and investigated. Power amplifier figures of merit are evaluated. A good performance is shown when combining both pre-processing techniques up to a certain operating point where DPD performance deteriorates. Solutions to improve the DPD performance at strong compression are suggested.
CCS-Based Dynamic Logics for Communicating Concurrent Programs

This work presents three increasingly expressive Dynamic Logics in which the programs are CCS processes (sCCS-PDL, CCS-PDL and XCCS-PDL). Their goal is to reason about properties of concurrent programs and systems described using CCS. In order to accomplish that, CCS's operators and constructions are added to a basic modal logic in order to create dynamic logics that are suitable for the description and verification of properties of communicating, concurrent and non-deterministic programs and systems, in a similar way as PDL is used for the sequential case. We provide complete axiomatizations for the three logics. Unlike Peleg's Concurrent PDL with Channels, our logics have a simple Kripke semantics, complete axiomatizations and the finite model property.
The Interaction of Accrual Management and Hedging : Evidence from Oil and Gas Firms

We appreciate the comments and suggestions we received from the anonymous referees and Mary Barth (the associate editor), from workshop participants at the joint Oregon-ABSTRACT: This research investigates whether oil and gas producing firms use discretionary accruals and hedging with derivatives as substitutes to manage earnings volatility. We examine firms primarily engaged in oil exploration and drilling since we can identify two kinds of risks to which these firms are exposed that can cause earnings volatility. These are oil price risk and exploration risk. While firms can hedge oil price risk with derivative instruments, markets do not exist in which they can hedge the operational risk of unsuccessful drilling. Discretionary accrual choices and hedging with derivatives can both be used to reduce volatility caused by oil price and exploration risks, while only hedging can reduce cash flow volatility induced by oil price fluctuations. Empirically, we consider the decision of whether or not to hedge oil price risk, and then, given that hedging occurs, we allow for simultaneous decis ions regarding the extent of hedging and the extent of smoothing with discretionary accruals. The results indicate that, after controlling for hypothesized determinants of hedging and smoothing with discretionary accruals, managers make decisions about the extent of hedging oil price risk independent of decisions about smoothing with discretionary accruals, but they then make decisions about the extent of smoothing with discretionary accruals based on the extent of their hedging and they do so in a manner that treats the extent of hedging and the extent of smoothing with discretionary accruals as substitute mechanisms for smoothing income. Data Availability: All data used in this research are from publicly available sources.
T Cell Receptor Mimic Peptidesand Their Potential Application in T-Cell-Mediated Diseas e

Background: A T cell receptor (TCR) peptide was designed that mimics the intramembranous amino acid sequence of the TCR chain. Prior studies had shown that this mimic peptide would inhibit TCR signaling. This study was designed to investigate the use of this mimic peptide for the treatment of T-cell-mediated skin diseases. Methods: Synthesized mimic peptides were first tested for their T-cell-inhibitory effect in proliferation assays. Afterwards, mimic peptides were applied to murine ear skin prior to application of a contact allergen and tested for their inhibitory effect in the model of murine allergic contact sensitivity. The effect of epicutaneous treatment with the peptide was also tested on patients with T-cell-mediated skin disease. Results: Mimic peptide potently inhibited proliferation of CD4+ and CD8+ T cells when added to allogeneic proliferation assays using dendritic cells as antigen-presenting cells (APCs). Suppression of the proliferative capacity could be overcome by addition of an anti-CD3 monoclonal antibody. When applied to murine ear skin prior to application of a contact allergen, mimic peptide efficiently blocked ear swelling responses in mice. In humans, application of mimic peptide for the treatment of various diseases resulted in amelioration or even cure in patients suffering from atopic dermatitis, psoriasis or lichen planus. Conclusions: TCR mimic peptide efficiently abrogates T-cell-mediated immune responses in mice and man in vitro and in vivo. The potential immunosuppressive effect of the drug is discussed.
HPV triage of women with atypical squamous cells of undetermined significance: a 3‐year experience in an Italian organized programme

Objective: The purpose of our study was to determine if Hybrid Capture II assay(HCII) on Liquid Based Cytology (LCB) improves the accuracy (higher sensitivity, similar specificity) than the repeat conventional Pap smear in smears with Atypical Squamous Cell (ASC) of Undetermined Significance diagnosis.