Response Function Model Research Articles

3D Compton image reconstruction method for whole gamma imaging

Compton imaging or Compton camera imaging has been studied well, but its advantages in nuclear medicine and molecular imaging have not been demonstrated yet. Therefore, the aim of this work was to compare Compton imaging with positron emission tomography (PET) by using the same imaging platform of whole gamma imaging (WGI). WGI is a concept that combines PET with Compton imaging by inserting a scatterer ring into a PET ring. This concept utilizes diverse types of gamma rays for 3D tomographic imaging. In this paper, we remodeled our previous WGI prototype for small animal imaging, and we developed an image reconstruction method based on a list-mode ordered subset expectation maximization algorithm incorporating detector response function modeling, random correction and normalization (sensitivity correction) for either PET and Compton imaging. To the best of our knowledge, this is the world’s first realization of a full-ring Compton imaging system. We selected 89Zr as an imaging target because a 89Zr nuclide emits a 909 keV single-gamma ray as well as a positron, and we can directly compare Compton imaging of 909 keV photons with PET, a well-established modality. We measured a cylindrical phantom and a small rod phantom filled with 89Zr solutions of 10.3 MBq and 10.2 MBq activity, respectively, for 1 h each. The uniform radioactivity distribution of the cylindrical phantom was reconstructed with normalization in both PET and Compton imaging. Coefficients of variation for region-of-interest values were 4.2% for Compton imaging and 3.3% for PET; the difference might be explained by the difference in the detected count number. The small rod phantom experiment showed that the WGI Compton imaging had spatial resolution better than 3.0 mm at the peripheral region although the center region had lower resolution. PET resolved 2.2 mm rods clearly at any location. We measured a mouse for 1 h, 1 d after injection of 9.8 MBq 89Zr oxalate. The 89Zr assimilated in the mouse bony structures was clearly depicted, and Compton imaging results agreed well with PET images, especially for the region inside the scatterer ring. In conclusion, we demonstrated the performance of WGI using the developed Compton image reconstruction method. We realized Compton imaging with a quality approaching that of PET, which is supporting a future expectation that Compton imaging outperforms PET.

Characterization of megahertz X-ray laser beams by multishot desorption imprints in PMMA.

Proper diagnostics of intense free-electron laser (FEL) X-ray pulses is indisputably important for experimental data analysis as well as for the protection of beamline optical elements. New challenges for beam diagnostic methods are introduced by modern FEL facilities capable of delivering powerful pulses at megahertz (MHz) repetition rates. In this paper, we report the first characterization of a defocused MHz 13.5-nm beam generated by the free-electron laser in Hamburg (FLASH) using the method of multi-pulse desorption imprints in poly(methyl methacrylate)(PMMA). The beam fluence profile is reconstructed in a novel and highly accurate way that takes into account the nonlinear response of material removal to total dose delivered by multiple pulses. The algorithm is applied to experimental data of single-shot ablation imprints and multi-shot desorption imprints at both low (10 Hz) and high (1 MHz) repetition rates. Reconstructed response functions show a great agreement with the theoretical desorption response function model.

Integration model of POSP measurement spatial response function

The particulate observing scanning polarimeter (POSP) measurement spatial response function (SRF) relates to the weighted contribution of each location within the measurement footprint, which is determined by the percentage of the dwell time of each location on the Earth surface to the overall sampling integration time. The SRF resulting from a combination of the equally weighted instantaneous field of view (IFOV) during integration is required for an accurate modeling. Simply using a mean value SRF assuming an equivalent weight at each sampling position instead of the actual SRF will inevitably introduce errors. Considering the data fusion between POSP and high spatial resolution sensors, a discrete integration method that takes the effect of actual weights into account is proposed in this paper. The simulation results of the integral model and the mean value model show that the larger the intensity change in the sampling area covered by the IFOV of the POSP during a single sampling, the more significant the difference between the two results. Meanwhile, the integration SRF is validated by resampling the simultaneous imaging polarization camera (SIPC) data, which is compared with POSP data acquired at the same time in an aerial experiment. The results show that the integration SRF model is more accurate to characterize the details of POSP measurement than the mean value SRF model. The proposed SRF reduces the root mean square error (RMSE) of convolved results and measurements by 5∼30% with different radiance contrast scene.

Latent D-Scoring Modeling: Estimation of Item and Person Parameters.

This study presents a latent (item response theory-like) framework of a recently developed classical approach to test scoring, equating, and item analysis, referred to as D-scoring method. Specifically, (a) person and item parameters are estimated under an item response function model on the D-scale (from 0 to 1) using marginal maximum-likelihood estimation and (b) analytic expressions are provided for item information function, test information function, and standard error of estimation for D-scores obtained under the proposed latent treatment of the D-scoring method. The results from a simulation study reveal very good recovery of item and person parameters via the marginal maximum-likelihood estimation method. Discussion and recommendations for practice are provided.

A neutron recoil-spectrometer for measuring yield and determining liner areal densities at the Z facility.

A proof-of-principle CR-39 based neutron-recoil-spectrometer was built and fielded on the Z facility. Data from this experiment match indium activation yields within a factor of 2 using simplified instrument response function models. The data also demonstrate the need for neutron shielding in order to infer liner areal densities. A new shielded design has been developed. The spectrometer is expected to achieve signal-to-background greater than 2 for the down-scattered neutron signal and greater than 30 for the primary signal.

ANALISIS RESPON PENAWARAN KOMODITI KEDELAI DI KABUPATEN TANJAB TIMUR

This study aims (1) to assess the factors of production and their effects on soybean production, and to investigate the ability of input levels, such as area and others to explain the response of production; and (2). assess the response of farmer supply to input prices, receipt of gross expectations, from related variables, and other exogenous variables.
 This research was conducted in 2017 in East Tanjab Regency. The method of analysis in its application is sorted based on the research objectives namely the Empirical Model of the Response Response Function. From the research, the results obtained from the soybean supply response model are strongly influenced by many factors. Among internal and external factors such as soybean prices, use of inputs, and seasons, which are quite relevant where soybean production increases because soybean prices increase. It also added that soybean production decreases when the input variables used are not in accordance with the provisions. As expected it was also found that the harvested area was also a significant determinant of crops. Furthermore it was found that soybean production increased during the rainy season. This finding is consistent with the fact that water availability is an important factor for soybean plants. The analysis also explained that soybean farmers in tidal land in the study area responded to the change in the use of efficient inputs. Supply of output is a response to soybean production. On input requests, many are sensitive to the use of labor, maintenance / harvesting labor. The elasticity of production obtained complements the part of the data base needed to evaluate the policy implications of using alternative inputs from soybean supply and input demand.
 Keywords: soybean, production, function

The impact of foreign direct investment on sustainable development in China.

The purpose of this paper is to investigate the impact of foreign direct investment (FDI) on sustainable development (SD) in China by using a regression model. Based on a panel date ranging from 1996 to 2016, this study makes an assessment of how development is sustained by means of an impose response function model. The findings revealed that, first, FDI has an insignificant influence on environmental quality in the long run but aids in financing physical capital deficits. Second, there exists the presence of the pollution halo hypothesis. In addition, in the short-term, pollution variables (sulfur dioxide and smoke and dust) cause significant variances on the amount of FDI inflows into China. However, they significantly lose their variation effect to FDI inflows in the long run due to the utilization of advanced technologies. Lastly, it is recommended that stricter environmental policies and strategies are implemented to curtail foreign investors from defaulting.

Sensitivity of the human auditory cortex and reward network to reverberant musical stimuli.

A room's acoustics can alter subjective impressions of music, including preference. However, little research has characterized the brain's response to room conditions. Functional magnetic resonance imaging (fMRI) was used to investigate the auditory and reward responses to concert hall stimuli. Before the fMRI testing, 18 participants rated their preferences to a solo-instrumental passage and an orchestral motif simulated in eight room acoustic conditions outside an MRI scanner to identify their most liked and disliked conditions. In the MRI, the most-liked (reverberation time, RT = 1.0-2.8 s) and most-disliked (RT = 7.2 s) conditions, along with the [anechoic and scrambled versions] anechoic and scrambled versions of the musical passages were presented. The auditory cortex was found to be sensitive to the temporal coherence of the stimuli as it exhibited stronger activations for simpler stimuli, i.e., the solo-instrumental and anechoic conditions, than for stimuli containing temporally incoherent auditory objects-the orchestral and reverberant conditions. In contrasts between liked and disliked reverberant stimuli, a reward response in the basal ganglia was detected in a region of interest analysis using a temporal derivative model of the hemodynamic response function. This response may indicate differences in preference between subtle variations in room acoustics applied to the same musical passage.

A novel asymmetrical peak broadening feature for a CdZnTe detector response function modeling using PHITS particle and heavy ion transport simulation code

In this paper we present the results of a detector response function modeling using a new version of PHITS Particle and Heavy Ion Transport Code with an advanced feature for asymmetrical peak broadening. Tests are performed on a room temperature medium resolution 500 mm3 CdZnTe detector of a quasi-hemispherical design with validation on a set of point source gamma-ray spectra with a range of energies from 59 keV up to 1332 keV. Performance assessment is conducted with respect to built-in spectra broadening capabilities using as default Gaussian as well as an asymmetrical peak shape models. Results of our study indicate that up to 200 keV energy range where peak asymmetry is not severe a default Gaussian peak shape broadening can be used. Beyond 200 keV the degree of CZT photopeak asymmetry becomes significant and requires an asymmetrical peak shape broadening. This asymmetry affects the low-energy side of the photopeaks and has a non-linear behavior with energy. We find that with a built-in feature of a tailed peak shape model introduced in the new version of PHITS code (ver. 3.10) asymmetrical peak shapes of CZT detectors can be approximated. The analysis routines and mathematical formalism are described in detail and results are presented.

Modelování makroekonomických agregátů české a slovenské ekonomiky pomocí var modelů

The aim of the paper is to analyse, model and compare selected macroeconomic variables of the Czech and Slovak economies and their dynamics using VAR models. This article shows an application of a selected model on real-time series of chosen macroeconomic indicators using four variables (R - interest rate, M - money supply (M2), P - price level (CPI), Y - GDP). We identify and test two long-run relationships. The following hypotheses have been confirmed: H1: a change in monetary aggregate affects a change in price level and a change in economic growth; H2: there is a causal relationship between GDP and M2; H3: there is a direct correlation between interest rates and the price level anticipated in the Fisher equation. The following methods are used: Granger causality, impulse response function, cointegration and error correction models. In the end, econometric models of macroeconomic time series are compared in the Czech and Slovak economies. The calculations used EViews software.

Frequency-Domain Electrothermal Impedance Spectroscopy of an Actively Switching Power Semiconductor Converter

This paper develops impedance spectroscopy for characterizing transient heat transfer in assembled power semiconductor converter systems. The method addresses limits associated with traditional methods, for e.g., data sheet transient thermal impedance curves are step responses that only characterize the junction-to-case spatial-domain segment. The presented method utilizes an actively switching semiconductor as a controlled modulator of dynamic loss (heat) injections, along with multiple temperature measurements, to form spatial electrothermal impedance frequency response function (FRF) models. Complementary investigations of numerical and analytical modeling methods yield a general, compact thermal model template, for interpreting measured FRFs. A pulsewidth modulated power converter with integrated die and heat sink temperature sensing was characterized with the spectroscopy method. Obtained ambient-referred and relative FRFs describe transient heat transfer, including fast (die-level) and slow (sink-level) modes, over frequency decades with coherence. The FRFs were parameterized and interpreted using the derived compact thermal model.

Finite-Time Learning Control Using Frequency Response Data With Application to a Nanopositioning Stage

Learning control enables significant performance improvement for systems that perform repeating tasks. Achieving high tracking performance by utilizing past error data typically requires noncausal learning that is based on a parametric model of the process. Such model-based approaches impose significant requirements on modeling and filter design. The aim of this paper is to reduce these requirements by developing a learning control framework that enables performance improvement through noncausal learning without relying on a parametric model. This is achieved by explicitly using the discrete Fourier transform to enable learning by using a nonparametric frequency response function model of the process. The effectiveness of the developed method is illustrated by application to a nanopositioning stage.

A Study on the the Lead-Lag Relationship between the CSI 300 Futures Market and Spot Market

Purpose - The purpose of this study was to examine the lead-lag relationship empirically between CSI 300 stock index futures and spot stocks based on five-minute high-frequency data. Design/methodology/approach - This study collected 23,495 five-minute data of the closing price of CSI 300 index and the closing price of CSI 300 stock index futures were taken as the research object, and the sample interval was selected from May 15, 2017 to May 15, 2019. The unit root test, cointegration test, vector error correction model, granger causality test and the impulse response and variance decomposition were hired In order to analyze the data. Findings - This paper attempts to study the lead-lag relationship between CSI-300 stock index futures and spot by empirical method. First, there is a long-term equilibrium relationship between the cointegration relation of the CSI300 index futures and the spot marke. Second, there is a significant causal relationship between stock index futures and spot, which lays the foundation for the lead-lag relationship between stock index futures and spot. Third, using VEC model to explore the lead-lag relationship between CSI 300 stock index futures and stock spot, stock index futures and spot guide each other, but the effect of stock index futures leading spot is very significant. Lastly, the interaction between the two markets is explored through the impulse response function model. The futures market is better at absorbing shocks than the spot market and the impact of the futures market on the spot market is not obvious. Research implications or Originality – In the CSI 300 index and the CSI 300 index futures market we found that the futures market has stronger shock absorption capacity than the spot market, and the futures market has no obvious response to the spot market agricultural machinery.

TPA and RCSA based frequency response function modelling for cutting forces compensation

In machining process, cutting forces are difficult to measure accurately due to the dynamic characteristic of measurement system. The cutting forces compensation requires the frequency response function (FRF), which cannot be measured in actual production. This paper proposes an effective method for FRF modelling and calculating based on transfer path analysis (TPA) and receptance coupling substructure analysis (RCSA). The measurement system is divided into three substructures: workpiece, table dynamometer with screws, joint surface between two previous substructures. The joint surface is simplified as a spring-damping model with contact stiffness and damping. The FRF of workpiece is obtained by finite element method (FEM), which is adjustable for different workpieces and tool positions. The FRF of dynamometer can be measured only by single impact test. The contact parameters can be identified by a few impact tests, which can be applied to other cutting conditions. The FRF between tool tip and dynamometer output is first derived based on TPA and RCSA. Second, a joint surface parameters identification algorithm as well as its simplified algorithm is presented through a few impact tests. Finally, impact tests and milling tests are implemented for parameters identification, algorithm verification and cutting forces compensation. The experimental results show that the proposed method has sufficient accuracy for the assembly FRF prediction.

THE DYNAMIC CORRELATION BETWEEN FISCAL SPENDING ON EDUCATION, HEALTH, CONSUMPTION AND STANDARD OF LIVING IN NIGERIA

The fiscal spending of the government have always been a strong instrument towards achieving development and recovering economy from recession. This paper investigates the long run and short run impact of three component of government expenditure (education, health, and consumption expenditure) on standard of living in Nigeria with time series data from 1981 to 2017. The study employs ordinary least square method of estimation on a range of equation models: Vector Error Correction Model (VECM) and the Impulse Responses Function Model. The result shows that fiscal spending on education, health, and consumption have a long run relationship with standard of living in Nigeria and the speed of adjustment towards long –run equilibrium is 61.45%, moderately high. The short run coefficient results reveals that education expenditure in both lag 1 &2 have a positive and significant impact on standard of living while health and consumption expenditure have insignificant impact on standard of living in Nigeria. Using Impulse Response Function model, we found that none of our fiscal spending variables (education expenditure, health and consumer spending) were able to emit positive impulses/shocks on the standard of living in Nigeria. The study recommends that government should ensure that fiscal spending on education, health, and consumption should be well managed, accounted for and the method should be transparent to the populace.

Hemodynamic Response Function Modeling to Determine the Areas with High Blood Supply in Block-Design fMRI Experiments

Background: Determining the activated brain areas due to different activities is one of the most common targets in functional magnetic resonance imaging (fMRI) data analysis, which could be carried out by hemodynamic response function (HRF) evaluation. The HR functions reflect changes of cerebral blood flow (CBF) in response to neural activity. Objectives: In this study, five models of HRF estimation were evaluated based on a simulated dataset. Models with higher accuracy were used to determine HRF parameters of the block-design fMRI data. Methods: The fMRI data were acquired in a 3 Tesla scanner. For block-design fMR imaging, CO2 gas was administered using a face-mask under physiological monitoring. Three patients with brain tumors were scanned. The fMRI data analysis was performed using the SPM 12 MATLAB toolbox. Akaike’s information criterion (AIC), Schwarz’ Bayesian (SBC), and mean square error (MSE) criteria were used to select the best HRF estimation model. Results: In simulation studies, the estimated HRFs by the canonical HRF plus its temporal derivative (TD), finite impulse response (FIR), and inverse logistic (IL) models were almost equal to the standard HRF. Mean square error, AIC, and SBC indices were ignorable for TD, FIR, and IL models (MSE/AIC/SBC magnitudes for TD, FIR, and IL models were 0.052/-1235.1/-1223.9, 0.055/-1206.4/-1194.9, and 0.068/-1091.5/-1049.2, respectively), which indicates that these models could accurately estimate HRF in block design fMRI studies. Conclusions: The HRF models could non-invasively evaluate the change of MR signal intensity under cerebrovascular reactivity (CVR) conditions and they might be helpful to investigate changes in human cerebral blood flow.

Upbeta -Decay spectrum, response function and statistical model for neutrino mass measurements with the KATRIN experiment

The objective of the Karlsruhe Tritium Neutrino (KATRIN) experiment is to determine the effective electron neutrino mass m(upnu _text {e}) with an unprecedented sensitivity of 0.2 hbox {eV}/hbox {c}^2 (90 %,hbox {C.L.}) by precision electron spectroscopy close to the endpoint of the upbeta -decay of tritium. We present a consistent theoretical description of the upbeta -electron energy spectrum in the endpoint region, an accurate model of the apparatus response function, and the statistical approaches suited to interpret and analyze tritium upbeta -decay data observed with KATRIN with the envisaged precision. In addition to providing detailed analytical expressions for all formulae used in the presented model framework with the necessary detail of derivation, we discuss and quantify the impact of theoretical and experimental corrections on the measured m(upnu _text {e}). Finally, we outline the statistical methods for parameter inference and the construction of confidence intervals that are appropriate for a neutrino mass measurement with KATRIN. In this context, we briefly discuss the choice of the upbeta -energy analysis interval and the distribution of measuring time within that range.

A unified framework for unconstrained and constrained ordination of microbiome read count data.

Explorative visualization techniques provide a first summary of microbiome read count datasets through dimension reduction. A plethora of dimension reduction methods exists, but many of them focus primarily on sample ordination, failing to elucidate the role of the bacterial species. Moreover, implicit but often unrealistic assumptions underlying these methods fail to account for overdispersion and differences in sequencing depth, which are two typical characteristics of sequencing data. We combine log-linear models with a dispersion estimation algorithm and flexible response function modelling into a framework for unconstrained and constrained ordination. The method is able to cope with differences in dispersion between taxa and varying sequencing depths, to yield meaningful biological patterns. Moreover, it can correct for observed technical confounders, whereas other methods are adversely affected by these artefacts. Unlike distance-based ordination methods, the assumptions underlying our method are stated explicitly and can be verified using simple diagnostics. The combination of unconstrained and constrained ordination in the same framework is unique in the field and facilitates microbiome data exploration. We illustrate the advantages of our method on simulated and real datasets, while pointing out flaws in existing methods. The algorithms for fitting and plotting are available in the R-package RCM.

Estimation of Hemodynamic Response Function in the Brain and Brain Tumors: Comparison of Inverse Logistic and Canonical Hemodynamic Response Function Models

Estimation of Hemodynamic Response Function in the Brain and Brain Tumors: Comparison of Inverse Logistic and Canonical Hemodynamic Response Function Models

RESPONSE FUNCTION FOR THE SRELATIVE INDEX IN CAMBISOL TREATED WITH AND WITHOUT BOVINE LIQUID BIOFERTILIZER

ABSTRACT The present study aimed at assessing the influence of physical properties associated with soil structure on the Srelative index. Two soil conditions under Ficus carica L. cultivation were studied (with or without liquid bovine biofertilizer in the irrigation water), in the 0-0.1 m and 0-0.3 m layers. Disturbed and undisturbed soil samples were collected from the above-mentioned layers and physical analyzes, pertinent to the study objective, were performed. The response function model was applied to verify how the soil independent physical variables influence on the Srelative index in the 0-0.1 m and 0-0.3 m layers, with 0 and 60% biofertilizer, being combined two to two. Once the response functions were known, the slopes of both functions were compared, being represented by the coefficients β11-β12 and β21-β22. This comparison enabled verifying whether there was an effect of the treatments on the response variable. In addition, the standard error of the difference between coefficients was calculated, and the Student's t-test applied. The method of multiple regression was also used to confirm the effect of the variables on the Srelative index for the 0-0.3 m layer in both treatments. Then, the variables with greater weight were selected by a backward elimination method to estimate the Srelative. The results showed that the Srelative index is strongly influenced by properties of the porous fraction, with total porosity and continuity of pores being of significant influence. Management with liquid bovine biofertilizer results in improvement in the soil structure, with effects measured by the Srelative index.