Miracle-dz/UniFAR-FTUs huggingface dataset:
GPS positioning in a multipath environment

We address the problem of GPS signal delay estimation in a multipath environment with a low-complexity constraint. After recalling the usual early-late estimator and its bias in a multipath propagation context, we study the maximum-likelihood estimator (MLE) based on a signal model including the parametric contribution of reflected components. It results in an efficient algorithm using the existing architecture, which is also very simple and cheap to implement. Simulations show that the results of the proposed algorithm, in a multipath environment, are similar to these of the early-late in a single-path environment. The performance are further characterized, for both MLEs (based on the single-path and multipath propagation) in terms of bias and standard deviation. The expressions of the corresponding Cramer-Rao (CR) bounds are derived in both cases to show the good performance of the estimators when unbiased.
Trade‐Offs between Immune Investment and Sexual Signaling in Male Mallards

Allocation trade‐offs between the immune system and sexual traits are central to current sexual selection hypotheses but remain contentious. Such trade‐offs could be brought about by the dual action of testosterone that stimulates sexual signals but also suppresses immune functions and/or by competition for carotenoids that can be deposited in ornaments or used as antioxidants in support of immune functions. We investigated the trade‐off between investment in immunity and maintenance of testosterone, carotenoids, and sexually selected, carotenoid‐based bill color in male mallards. Following a nonpathogenic immune challenge, facultative immune investment resulted in a syndrome of changes in allocation. Plasma carotenoids disappeared from circulation proportional to antibody production. In addition, the reflectance spectrum of the bill was affected; greater antibody production was associated with an increase in relative UV reflectance. Although changes in bill reflectance and plasma carotenoids were related, the relationship appeared more complex than direct competition with immunity. Finally, maintenance of testosterone was affected by immune investment: testosterone levels declined substantially when males produced more antibodies. Because males with high testosterone are preferred by females, the decline in testosterone, in addition to carotenoid depletion and effects on bill reflectance, could constitute a significant cost of immune investment.
Interference term elimination of the discrete wigner distribution using nonlinear filtering

This paper introduces a new nonlinear filtering approach for the removal of cross terms in the discrete Wigner distribution. Realizing that linear smoothing kernels are unable to completely cancel the cross-terms without compromising time-frequency concentration and resolution of the auto-terms, a nonlinear filtering algorithm is devised where the filter automatically adapts to the rapidly changing nature of the Wigner distribution plane. Varying the filter behavior from an identity operation at one extreme to a low pass linear filter at the other, a near optimal removal of cross terms is achieved. Unlike traditional smoothing and optimal kernel design techniques, this algorithm does not reduce the time-frequency resolution and concentration of the auto-terms.
Empirical Research on the Competency Model of Senior Researchers

According to the competency dictionary of Spencer, this research explores the component of senior researchers' competency in universities, and designs a scale of competency through the literature review, net information analysis, as well as the interviews of experts. To elaborate a model for senior researchers' competency, a total of 348 professors from 17 universities answered the questionnaire. The results of analysis reveal that the competency model of senior researchers in university is composed of three dimensions, such as research quality, research capability and management skills, which also include some different factors. The research qualities consist of achievement-oriented, confidence, cooperation and anti-pressure. The research capabilities include information mining, innovation abilities, and learning. The management skills contain team management, steering ability, and education.
Effective area calibration of the Reflection Grating Spectrometers of XMM-Newton. I. X-ray spectroscopy of the Crab nebula

The Crab nebula and pulsar have been widely used as a calibration source for X-ray instruments. The in-flight effective area calibration of the Reflection Grating Spectrometers (RGS) of XMM-Newton depend upon the availability of reliable calibration sources. We investigate how the absolute effective area calibration of RGS can be obtained using Crab as a standard candle. We have analysed RGS observations of the Crab using different instrument configurations and spatial offsets, and made use of previous determinations of the continuum spectrum of the nebula plus pulsar. Due to the high spectral resolution of the RGS, we resolve the main absorption edges and detect the strong 1s-2p absorption lines of neutral oxygen. We get an excellent fit to the Crab spectrum using this fixed continuum and the absorption spectrum determined by RGS. We get accurate column densities for the neutral atoms of H, N, O, Ne, Mg, and Fe, as well as a clear detection of Fe II and firm upper limits for other ions. Our data are in good agreement with earlier optical and UV spectroscopic measurements of some of these ions. We find solar abundances for N and O, while Ne is overabundant by a factor of 1.7 and Fe is underabundant by a factor of 0.8. We confirm that there is less dust in the line of sight compared to the prediction based on the absorption column. Our spectra suggest a more prominent role of ferric iron in the dust compared to ferrous iron. Our high-resolution observations confirm that Crab can be used as an X-ray calibration source. RGS spectra have determined the absorption spectrum towards Crab with unprecedented detail.
Design and implementation of MPPT controlled grid connected photovoltaic system

This paper proposes an intelligent method for maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insolation conditions and conversion of this solar energy into stabilized sine wave having low distortion factor (DF), so that the solar energy can be supplied to grid and can operate electrical and electronic devices efficiently. For the reduction of tracking time of maximum power from photovoltaic array and to obtain stabilized sine wave with very fast rise time for voltage stability, fuzzy logic control algorithm is implemented with the embedded microcontroller for improved performance as compared to conventional techniques. The system includes a photovoltaic array; a PWM controlled DC-DC, DC-AC converters, sensor circuits and zero crossing detector (ZCD). The designed MPPT controller regulates the converter output voltage by varying modulation index of the PWM pattern using MPPT algorithm and it maximizes the output power extracted from photovoltaic array. This paper discusses the low cost implementation of MPP algorithm in a 8-bit microcontroller using the tools and techniques to generate optimized real time code in C for ATMega8 microcontroller which will demonstrate how maximum power point tracker might provide elegant and efficient solution for increasing the efficiency of a solar system and connection of the extracted energy to grid which is based on experimental results rather than on mathematical models.
Leaf-cutting ant faecal fluid and mandibular gland secretion: effects on microfungi spore germination

The mandibular gland secretion (MGS) and the faecal fluid (FF) of the leaf-cutting ant Atta sexdens rubropilosa Forel affected the spore germination of selected microfungi isolated from nests of this insect. MGS was more effective than the FF, completely inhibiting the spore germination of four out of six microfungi species.
Gayathri Gandhamuneni Yumeng Wang

There are wide variety of clustering algorithms present to do the spatial clustering. In this paper, we are trying to compare two different types of Clustering algorithms DBScan and SATScan. We try to compare the 2 algorithms in a systematic and unbiased fashion. We consider the 3 factors for comparison between these 2 algorithms: Shape, Statistical Significance and Runtime. Runtime is compared both in terms of number of data points present and also the number of clusters present in the dataset. Finally, we also provide the situations in which both of these algorithms can be used. In order to have the unbiased comparison, we provide both the algorithms the same dataset and then try to compare them relative to the three comparison factors. DBScan algorithm with MATLAB and SATScan software have been used.
Low-complexity successive detection method for OFDM systems over doubly selective channels

Orthogonal frequency division multiplexing (OFDM) system is robust against inter-symbol interference (ISI) by increasing the symbol duration. However, for high-speed application, time variation of a multipath channel result in inter-carrier interference (ICI). It leads to the performance degradation. This works propose a low-complexity successive detection algorithm combined with the techniques of Newton's iterative matrix inversion method and successive detection method according to signal to noise ratio (SNR) in OFDM system. With the assumption of linearly varying channel impulse responses under fast fading conditions, the proposed algorithm reduces the complexity from O(N3) of conventional zero-forcing algorithm to O(N2) , meantime it mitigates the noise enhancement problem. In all, it surpasses the performance bound of zero-forcing (ZF) equalization.
Tracking for context extraction in athletic events

Personalisation of large scale athletic events requires camera-specific annotations to provide for reasoning about incidents being best viewed by specific cameras. This needs an automatic system for annotating athletes on the video streams, to be achieved by the use of person trackers. In this paper we present a novel approach towards combining scene segmentation, motion outliers, face and bib tracks into body hypotheses and tracking them across time. Preliminary evaluation results demonstrate the potential of the proposed approach.
Toward An Integration Of Social Learning And Individual Learning In Agent-Based Computational Stock Markets:The Approach Based On Population Genetic Programming

Artificial stock market is a growing field in the past few years. The essence of this issue is the interaction between many heterogeneous agents. In order to model this complex adaptive system, the techniques of evolutionary computation have been employed. Chen and Yeh (2000) proposed a new architecture to construct the artificial stock market. This framework is composed of a single-population genetic programming (SGP) based adaptive agent with a SA (Simulated Annealing) learning process and a business school. However, one of the drawbacks of SGP-based framework is that the traders can’t work out new ideas by themselves. The only way is to consult researchers in the business school. In order to make the traders more intelligent, we employ multi-population GP (MGP) based framework with the mechanism of school. This extension is not only reasonable, but also has the economic implications. How do the more intelligent agents influence the economy? Are the econometric properties of the simulation results based on MGP more like the phenomena found in the real stock market? In this paper, the comparison between SGP and MGP is studied from two sides. One is related to the micro-structure, traders’ behavior and believe. The other is macro-properties, the properties of time series. The line of research is helpful in understanding the foundation of economics and finance, and constructing more realistic economic models.
Resource allocation in cloud computing using agents

In cloud computing scenario, efficiency of application execution not only depends on quality and quantity of the resources in the data center, but also on underlying resource allocation approaches. An efficient resource allocation technique is necessary for building an efficient system. The objective of this work is to propose an agent based Best-Fit resource allocation scheme which increases utilization of the resources, lowers the service cost and reduces the execution time. The work employs two types of agents: user's cloudlet agent and provider's resource agent. Cloudlet agent is located at the client system, which collects job requirement and offers various QoS options for its execution. Resource agent at the server, uses Best-Fit approach to allocate resources for jobs received from Cloudlet agent. The proposed work is simulated and the results are compared with other agent based resource allocation approaches using First-Come-First-Serve and Round-Robin. It is observed that Best-Fit approach performs better in terms of VMs allocation, job execution time, cost and resource utilization.
Towards a national mapped classification of terrestrial ecosystems in Mongolia: a pilot study in the Gobi Desert region

In Mongolia, partners from national and aimag governments, academia and NGOs have developed regional conservation plans that balance the government commitment to protection of natural habitats with planned development of mineral resources and related infrastructure. A key input is a mapped classification of major habitat types, or ecosystems, to represent the range of natural habitats and function as a surrogate for biodiversity. We developed a GIS model to map ecosystems across the Mongolian Gobi Desert region by comparing the distribution of plant communities and major vegetation types, taken from field surveys and national maps, with patterns of above-ground biomass, elevation, climate and topography derived from remote sensing. The resulting mapped classification is organized as a hierarchy of 1) biogeographic regions, 2) terrestrial ecosystem types based on vegetation, elevation and geomorphology, and 3) landforms. This provides a first-iteration map to support landscape-level conservation planning and a model framework that can support field surveys and future model revisions, with other applications to land use planning, research, surveys and monitoring.
Scheduling distributed real-time systems by satisfiability checking

We present a SAT-based approach to the task and message allocation problem of distributed real-time systems. In contrast to the heuristic approaches usually applied to this problem, our approach is guaranteed to find an optimal allocation for realistic task systems running on complex target architectures. Our method is based on the transformation of such scheduling problems into nonlinear integer optimization problems. The core of the numerical optimization procedure we use to discharge those problems is a solver for arbitrary Boolean combinations of integer constraints. Optimal solutions are obtained by imposing a binary search scheme on top of that solver. Experiments show the applicability of our approach to industrial-size task systems.
Calibration factor estimation based on statistical modeling of scattering coefficient

The calibration factors of synthetic aperture radar (SAR) images are generally obtained by estimation of radar system parameters based on internal calibration and external calibration. In this paper, we propose a simple but efficient method to estimate the calibration factors based on statistical modeling of scattering coefficient. Taking expectation and variance on the linear form of calibration equation, we derive the analytical expressions of such estimator. Modeling the scattering coefficient as Rayleigh, heavy-tailed Rayleigh, log-normal, and Weibull distributions, respectively, we obtain the calibration factor estimators for two kinds of radar receivers: the linear receiver and the square-law receiver. Lastly, Monte Carlo simulation results are provided to demonstrate the efficiency of the proposed calibration factor estimator.
A Tandem Repeat in Decay Accelerating Factor 1 Is Associated with Severity of Murine Mercury-Induced Autoimmunity

Decay accelerating factor (DAF), a complement-regulatory protein, protects cells from bystander complement-mediated lysis and negatively regulates T cells. Reduced expression of DAF occurs in several systemic autoimmune diseases including systemic lupus erythematosus, and DAF deficiency exacerbates disease in several autoimmune models, including murine mercury-induced autoimmunity (mHgIA). Daf1, located within Hmr1, a chromosome 1 locus associated in DBA/2 mice with resistance to mHgIA, could be a candidate. Here we show that reduced Daf1 transcription in lupus-prone mice was not associated with a reduction in the Daf1 transcription factor SP1. Studies of NZB mice congenic for the mHgIA-resistant DBA/2 Hmr1 locus suggested that Daf1 expression was controlled by the host genome and not the Hmr1 locus. A unique pentanucleotide repeat variant in the second intron of Daf1 in DBA/2 mice was identified and shown in F2 intercrosses to be associated with less severe disease; however, analysis of Hmr1 congenics indicated that this most likely reflected the presence of autoimmunity-predisposing genetic variants within the Hmr1 locus or that Daf1 expression is mediated by the tandem repeat in epistasis with other genetic variants present in autoimmune-prone mice. These studies argue that the effect of DAF on autoimmunity is complex and may require multiple genetic elements.
Pengaruh Aerobic Exercise terhadap Psychological Wellbeing pada Mahasiswa dengan Beban Akademik Tinggi

Penelitian ini bertujuan untuk mengetahui adakah pergaruh aerobic exercise pada tingkat wellbeing pada mahasiswa dengan beban akademik tinggi. Tingkat well-being diukur menggunakan skala psychological well-being yang diturunkan dari 6 dimensi psychological well-being. Subjek penelitian ini berjumlah 51 mahasiswa Universitas A yang menempuh minimal 22 SKS dan aktif melakukan aerobic exercise. Analisis data dilakukan dengan statistik regresi menggunakan software SPSS. Hasil dari penelitian ini menunjukkan bahwa tidak ada pengaruh aerobic exercise terhadap tingkat well-being mahasiswa dengan beban akademik tinggi. Hal ini dapat dikaitkan dengan motivasi individu dalam berolahraga, sehingga pada penelitian selanjutnya disarankan untuk meneliti motivasi individu untuk berolahraga.
Nature of Glutamate Alterations in Schizophrenia: A Meta-analysis of Proton Magnetic Resonance Spectroscopy Studies.

IMPORTANCE Alterations in glutamatergic neurotransmission may be fundamental to the pathophysiology of schizophrenia, and the glutamatergic system is a target for novel therapeutic interventions in the disorder. OBJECTIVE To investigate the nature of brain glutamate alterations in schizophrenia by conducting a meta-analysis of glutamate proton magnetic resonance (MRS) spectroscopy studies. DATA SOURCES The MEDLINE database was searched for studies published from January 1, 1980, to April 1, 2015. Search terms included magnetic resonance spectroscopy, schizophrenia, psychosis, clinical or genetic high risk, and schizoaffective. Inclusion criteria were single voxel 1H-MRS studies reporting glutamate, glutamine or Glx values for a patient or risk group in comparison to a healthy volunteer group. STUDY SELECTION Fifty-nine studies were identified, which included 1686 patients and 1451 healthy individuals serving as controls. DATA EXTRACTION AND SYNTHESIS A random-effects, inverse-weighted variance model was used to calculate the pooled effect size. Mean values were extracted and verified independently. Effect sizes were determined for glutamate, glutamine, and Glx in brain regions that had been examined in at least 3 different studies. A secondary analysis grouped studies into those examining patients at different stages of illness (high risk, first-episode psychosis, or chronic schizophrenia). Effects of age, antipsychotic dose, and symptom severity were determined using meta-regression. RESULTS In schizophrenia, there were significant elevations in glutamate in the basal ganglia (Hedges g = 0.63; 95% CI, 0.15-1.11), glutamine in the thalamus (g = 0.56; 95% CI, 0.02-1.09), and Glx in the basal ganglia (g = 0.39; 95% CI, 0.09-0.70) and medial temporal lobe (g = 0.32; 95% CI, 0.12-0.52). No region showed a reduction in glutamate metabolites in schizophrenia. Secondary analyses revealed that elevated medial frontal Glx levels were evident in individuals at high risk for schizophrenia (g = 0.26; 95% CI, 0.05-0.46) but not in those with first-episode psychosis or chronic schizophrenia, whereas elevated Glx in the medial temporal lobe was seen with chronic schizophrenia (g = 0.40; 95% CI, 0.08-0.71) but not in the high-risk or first-episode groups. Meta-regression found no association with age, symptom severity, or antipsychotic dose. CONCLUSIONS AND RELEVANCE Schizophrenia is associated with elevations in glutamatergic metabolites across several brain regions. This finding supports the hypothesis that schizophrenia is associated with excess glutamatergic neurotransmission in several limbic areas and further indicates that compounds that reduce glutamatergic transmission may have therapeutic potential.
Programmable graphics: the future of interactive rendering

Recent innovations in computer hardware architecture---the arrival of multi-core CPUs, the generalization of graphics processing units (GPUs), and the imminent increase in bandwidth available between CPU and GPU cores---make a new era of interactive graphics possible. As a result of these changes, game consoles, PCs and laptops will have the potential to provide unprecedented levels of visual richness, realism, and immersiveness, making interactive graphics a compelling killer app for these modern computer systems. However, current graphics programming models and APIs, which were conceived of and developed for the previous generation of GPU-only rendering pipelines, severely hamper the type and quality of imagery that can be produced on these systems. Fulfilling the promise of programmable graphics---the new era of cooperatively using the CPU, GPU, and complex, dynamic data structures to efficiently synthesize images---requires new programming models, tools, and rendering systems that are designed to take full advantage of these new parallel heterogeneous architectures. Neoptica is developing the next-generation interactive graphics programming model for these architectures, as well as new graphics techniques, algorithms, and rendering engines that showcase the unprecedented visual quality that they make possible.