Large Observation Window Research Articles

Antidepressant exposure and long-term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder.

The use of antidepressants in major depressive disorder (MDD) has been reported to influence long-term risk of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD), but studies are conflicting. We used inverse probability weighted (IPW) Cox models with time-varying covariates in a retrospective cohort study among midlife veterans with MDD within the US Veterans Affairs healthcare system from January 1, 2000 to June 1, 2022. A total of 35,200 patients with MDD were identified. No associations were seen regarding the effect of being exposed to any antidepressant versus no exposure on AD/ADRD risk (events=1,056, hazard ratio=0.94, 95% confidence interval: 0.81 to 1.09) or the exposure to specific antidepressant classes versus no exposure. A risk reduction was observed for female patients in a stratified analysis; however, the number of cases was small. Our study suggests that antidepressant exposure has no effect on AD/ADRD risk. The association in female patients should be interpreted with caution and requires further attention. We studied whether antidepressant use was associated with future dementia risk. We specifically focused on patients after their first-ever diagnosis of depression. We used IPW Cox models with time-varying covariates and a large observation window. Our study did not identify an effect of antidepressant use on dementia risk. A risk reduction was observed in female patients, but the number of cases was small.

Probing multiscale dissolution dynamics in natural rocks through microfluidics and compositional analysis

Mineral dissolution significantly impacts many geological systems. Carbon released by diagenesis, carbon sequestration, and acid injection are examples where geochemical reactions, fluid flow, and solute transport are strongly coupled. The complexity in these systems involves interplay between various mechanisms that operate at timescales ranging from microseconds to years. Current experimental techniques characterize dissolution processes using static images that are acquired with long measurement times and/or low spatial resolution. These limitations prevent direct observation of how dissolution reactions progress within an intact rock with spatially heterogeneous mineralogy and morphology. We utilize microfluidic cells embedded with thin rock samples to visualize dissolution with significant temporal resolution (100 ms) in a large observation window (3 × 3 mm). We injected acidic fluid into eight shale samples ranging from 8 to 86 wt % carbonate. The pre- and postreaction microstructures are characterized at the scale of pores (0.1 to 1 µm) and fractures (1 to 1,000 µm). We observe that nonreactive particle exposure, fracture morphology, and loss of rock strength are strongly dependent on both the relative volume of reactive grains and their distribution. Time-resolved images of the rock unveil the spatiotemporal dynamics of dissolution, including two-phase flow effects in real time and illustrate the changes in the fracture interface across the range of compositions. Moreover, the dynamical data provide an approach for characterizing reactivity parameters of natural heterogeneous samples when porous media effects are not negligible. The platform and workflow provide real-time characterization of geochemical reactions and inform various subsurface engineering processes.

Noise reduction and 3D image restoration of single photon counting LiDAR using adaptive gating

Single photon LiDAR is considered as one of the most important tools in acquiring target information with high accuracy under extreme imaging conditions, as it offers single photon sensitivity and picosecond timing resolution. However, such technique sense the scene with the photons reflected by the target, thus resulting in severe degradation of image in presence of strong noise. Range gating with high-speed electronics is an effective way to suppress the noise, unfortunately, such technique suffers from manually selecting the parameters and limited gating width. This paper presents a target information extracting and image restoration method under large observation window, which first obtain the depth distribution of the target and extract the information within the range by analyzing the model of signal and noise, then further improve the image quality by adopting advanced image restoration algorithm and henceforth shows better results than those denoising method that purely relying on hardware. In the experiment, photon-per-pixel (PPP) was as low as 3.020 and signal-to-background ratio (SBR) was as low as 0.106, the proposed method is able to improve SBR with a factor of 19.330. Compared to classical algorithm named cross correlation, the reconstruction signal to noise ratio (RSNR) increased 33.520dB by further cooperating with advanced image restoration algorithm, thus improved the ability of sensing accurate target information under extreme cases.

TOPFLOW pressure chamber – Versatile techniques to simplify design and instrumentation of thermal fluid dynamic experiments at high pressure

Thermal hydraulic experiments at system pressures close to the reference reactor are difficult and costly. The pressure chamber technology described in the present paper was developed to improve the accessibility of the test fluid for an application of advanced instrumentation. The main idea consists in accommodating the actual test rig inside a pressure tank and operate it in pressure equilibrium with a filling gas in the chamber. In this way, the walls of the test equipment do not have to be designed as a pressure-bearing boundary. An important feature is a passive approach to maintain the needed very good pressure equilibrium between the fluid in the test setup and the filling gas of the chamber. It is in particular needed in experiments requiring high mass flows of steam supply. Auxiliary systems for pressurizing and cooling the chamber are described. Furthermore, several useful solutions of particular problems are presented, such as the accommodation of delicate devices, like high-speed cameras and infrared cameras, in the pressure chamber, a blurring-free imaging through large observation windows, the sealing of the latter, auxiliary equipment for an efficient handling of the test equipment and the design of penetrations for multiple electric signals through the pressure boundary. Finally, an overview of the experimental programs conducted by now is given, whereby the emphasis is put on examples of measuring results illustrating the potentials of the pressure chamber technology rather than on the scientific output of the given experimental programs.

Adaptive transverse blood velocity estimation in medical ultrasound: A simulation study

Undoubtedly, highly valuable information about vascular anomalies is attained by the examination of the blood flow profile. The chief drawback of the conventional medical ultrasound in preparation of the blood periodogram is the measurement system shortcoming at the beam to flow angles near 90°. Recently, a method based on transverse oscillation (TO) approach, known as “Fourth-order estimation”, has been developed to directly estimate the transverse power spectral density (PSD) of the fully transverse blood flow. One of the basic requirements to accomplish acceptable PSDs by this technique is the sufficiently large observation window. In this paper, two adaptive approaches for efficient estimation of the velocity spectrum of a fully transverse flow by a limited observation window length are described. The first proposed adaptive approach is based on the minimum variance adaptive spectral estimation in combination with the well-known TO technique (TO-MV). Then, by exploiting the eigenspace separation of the observed data to eliminate the contribution of the undesired components, the second technique (TO-EIBMV) is developed. The approaches are validated using Field II simulations for pulsating flow. The proposed methods are tested and compared to the conventional TO transverse spectral estimator by metrics of relative standard deviation (RSD) and relative bias (RB). One of the main achievements is the decrement of the required data samples for spectrogram estimation, which leads to a better temporal resolution. Moreover, for the analyzed adaptive techniques, the robustness of the estimation results for the beam to flow angles of 60–90° and vessel depths ranging from 20 mm to 60 mm are investigated.

Testing goodness of fit for point processes via topological data analysis

We introduce tests for the goodness of fit of point patterns via methods from topological data analysis. More precisely, the persistent Betti numbers give rise to a bivariate functional summary statistic for observed point patterns that is asymptotically Gaussian in large observation windows. We analyze the power of tests derived from this statistic on simulated point patterns and compare its performance with global envelope tests. Finally, we apply the tests to a point pattern from an application context in neuroscience. As the main methodological contribution, we derive sufficient conditions for a functional central limit theorem on bounded persistent Betti numbers of point processes with exponential decay of correlations.

Differential pulse‐amplitude modulation signalling for free‐space optical communications

To improve the bandwidth efficiency of free-space optical systems and at the same time to reduce the impact of the background noise, a differential M -ary pulse-amplitude modulation ( M -PAM) signalling scheme that uses two laser transmitters is proposed. The authors first consider the condition that the receiver perfectly knows the instantaneous channel coefficient and compare the performance of the proposed differential PAM with the conventional PAM signalling and show the improved performance when the background noise level is relatively high. Second , the practical situation where the receiver has to estimate the channel for signal detection is considered. The authors propose an estimation scheme based on the characteristics of the differential PAM signalling while requiring no pilot symbol transmission. The proposed data-aided channel estimation is performed on a sequence of received PAM symbols. The authors also show that for a sufficiently large observation window, the proposed estimation method allows achieving a performance close to the perfect channel knowledge.

Direct Position Determination of Coherent Pulse Trains Based on Doppler and Doppler Rate

Direct Position Determination (DPD) of coherent pulse trains using a single moving sensor is considered in this paper. Note that when a large observation window and relative maneuvering course between emitter and receiver both exist, the localization accuracy of Doppler frequency shift only based DPD will decline because of the noticeable Doppler frequency shift variations. To circumvent this problem, a Doppler frequency shift and Doppler rate based DPD approach using a single moving sensor is proposed in this paper. First, the signal model of the intercepted coherent pulse trains is established where the Doppler rate is taken into consideration. Then, the Maximum Likelihood based DPD cost function is given, and the Cramer–Rao lower bound (CRLB) on localization is derived whereafter. At last, the Monto Carlo simulations demonstrate that in one exemplary scenario the Doppler frequency shift variations are noticeable with a large observation window and the proposed method has superior performance to the DPD, which is only based on the Doppler frequency shift.

FSO channel estimation for OOK modulation with APD receiver over atmospheric turbulence and pointing errors

In the free-space optical (FSO) links, atmospheric turbulence and pointing errors lead to scintillation in the received signal. Due to its ease of implementation, intensity modulation with direct detection (IM/DD) based on ON–OFF-keying(OOK) is a popular signaling scheme in these systems. For long-haul FSO links, avalanche photo diodes (APDs) are commonly used, which provide an internal gain in photo-detection, allowing larger transmission ranges, as compared with PIN photo-detector (PD) counterparts. Since optimal OOK detection at the receiver requires the knowledge of the instantaneous channel fading coefficient, channel estimation is an important task that can considerably impact the link performance. In this paper, we investigate the channel estimation issue when using an APD at the receiver. Here, optimal signal detection is quite more delicate than in the case of using a PIN PD. In fact, given that APD-based receivers are usually shot-noise limited, the receiver noise will have a different distribution depending on whether the transmitted bit is ‘0’ or ‘1’, and moreover, its statistics are further affected by the scintillation. To deal with this, we first consider minimum mean-square-error (MMSE), maximum a posteriori probability (MAP) and maximum likelihood (ML) channel estimation over an observation window encompassing several consecutive received OOK symbols. Due to the high computational complexity of these methods, in a second step, we propose an ML channel estimator based on the expectation–maximization (EM) algorithm which has a low implementation complexity, making it suitable for high data-rate FSO communications. Numerical results show that for a sufficiently large observation window, by using the proposed EM channel estimator, we can achieve bit error rate performance very close to that with perfect channel state information. We also derive the Cramer–Rao lower bound (CRLB) of MSE of estimation errors and show that for a large enough observation window, this CRLB can be adequately tight.

Analysing structural diversity in two temperate forests in northeastern China

This contribution presents an analysis of the structural diversity in two temperate forest ecosystems in northeastern China, based on two large contiguous observational studies covering an area of 5.2ha (260×200m2) each. The total number of living trees in the conifer and broad-leaved forest (CBF) study area is 2927 per ha, comprising 37 species and 21 genera. The old growth forest (OGF) study area has 2276 trees per ha, including 22 species and 13 genera. Tree species are classified according to their community status as mature and immature canopy, subcanopy and shrub. A clustering process based on two distinct communities of the bivariate dbh/height distributions is used to differentiate between mature and immature canopy species. Numerical analysis is based on these four distinct cohorts. Despite advances in remote sensing, mapped tree data in large observation windows are very rare. Thus, we are able to use methods for analysing forest structure which are suitable for both, unmapped and mapped data. The two data sets are unique in that all (approximately) 27,000 tree heights are available. Accordingly, it was possible to fit bimodal height distributions and bivariate mixed dbh/height distributions to almost all individual species that were represented by sufficiently large numbers. Methods of second order statistics (SOC), including marked point statistics as well as nearest neighbor statistics (NNS) based on nearest neighbourhood structure units are also presented, including bivariate mixtures of the NNS attributes “mingling” and “dominance”. Mark correlations were investigated for several marks, including diameters, heights and nearest neighbor statistics. Finally, we discuss the most important results and motivate the need for detailed assessments in large contiguous field plots. The literature on spatial statistics is often rather technical, and there is relatively little exchange between mathematicians developing the theory and ecologists who have interesting data from observational studies, such as presented in this contribution.

Bayesian and adaptive controls for a newsvendor facing exponential demand

The newsvendor problem is relatively easy to solve when the distribution of demand for newspapers is known. When the demand is unknown, the newsvendor faces a dual problem in the sense of Feldbaum (1960): to choose a decision variable that maximizes profit in the present period, and choose a large enough observation window to be able to view the process correctly so that consistent parameter estimation can occur. This is a difficult problem in general. In this paper, we treat a special case when the newsvendor faces exponential demand, independently and identically distributed with unknown mean.

Development of a high pressure chamber for research into diesel spray dynamics

An optically accessible pressure vessel and ancillary instrumentation for studies of diesel spray dynamics has been designed and built at the Australian Maritime College. The requirement for large observation windows and internal pressures up to 10 MPa necessitated the use of finite element analysis in conjunction with first principles analysis. Strain gauge testing confirmed the calculated maximum stresses in the observation windows. The chamber is a registered pressure vessel conforming to AS1210. A purpose-built injection system capable of fuel pressures up to 120 MPa and injection pulse durations up to 30 ms has been implemented. Laser-based instrumentation is synchronised with individual injection events to measure spray droplet velocities and sizes.

Old Program Director’s Course—Module 2—Teaching and evaluating for the six core competencies

In the free-space optical (FSO) links, atmospheric turbulence and pointing errors lead to scintillation in the received signal. Due to its ease of implementation, intensity modulation with direct detection (IM/DD) based on ON–OFF-keying(OOK) is a popular signaling scheme in these systems. For long-haul FSO links, avalanche photo diodes (APDs) are commonly used, which provide an internal gain in photo-detection, allowing larger transmission ranges, as compared with PIN photo-detector (PD) counterparts. Since optimal OOK detection at the receiver requires the knowledge of the instantaneous channel fading coefficient, channel estimation is an important task that can considerably impact the link performance. In this paper, we investigate the channel estimation issue when using an APD at the receiver. Here, optimal signal detection is quite more delicate than in the case of using a PIN PD. In fact, given that APD-based receivers are usually shot-noise limited, the receiver noise will have a different distribution depending on whether the transmitted bit is ‘0’ or ‘1’, and moreover, its statistics are further affected by the scintillation. To deal with this, we first consider minimum mean-square-error (MMSE), maximum a posteriori probability (MAP) and maximum likelihood (ML) channel estimation over an observation window encompassing several consecutive received OOK symbols. Due to the high computational complexity of these methods, in a second step, we propose an ML channel estimator based on the expectation–maximization (EM) algorithm which has a low implementation complexity, making it suitable for high data-rate FSO communications. Numerical results show that for a sufficiently large observation window, by using the proposed EM channel estimator, we can achieve bit error rate performance very close to that with perfect channel state information. We also derive the Cramer–Rao lower bound (CRLB) of MSE of estimation errors and show that for a large enough observation window, this CRLB can be adequately tight.

Suboptimal multiple-symbol differential detection of MPSK with diversity reception

Simon and Alouini (2001) have derived the structure of the optimal N-length differential detector for differentially encoded M-ary phase-shift keying signals, transmitted over a slow fading diversity channel. Even though there is no explicit phase estimation and compensation being performed at the receiver, it was demonstrated that as N increases, the error performance of this multiple-symbol differential detector approaches that of maximal-ratio combining (with differential encoding). Unfortunately, efficient implementation of this optimal receiver is not possible, and it exhibits a computational complexity exponential in N. The computational complexity can be reduced dramatically to N log N if the receiver first performs coherent combining of the received multichannel baseband signals, followed by single-channel multiple-symbol differential detection (MSDD). A coherent combiner is introduced that is capable of cophasing the multichannel signals without violating the fundamental nature of differential detection, i.e. to avoid explicit phase estimation. The proposed suboptimal coherent combining MSDD (CC-MSDD) receiver essentially consists of two differential detectors: one operating across diversity branches, and one operating across time. Owing to the dramatic reduction in complexity, a very large observation window is used with the CC-MSDD. With window size N=64, the asymptotic performance of the CC-MSDD is only 0.5 dB away from maximal-ratio combining with differential encoding. This translates into a 1.5 dB gain in power efficiency over conventional equal gain combining for a second-order diversity system. The authors also investigate suboptimal receivers which perform selection combining, followed by single-channel MSDD. Although these selection combining MSDD receivers provide less than satisfactory performance in stand-alone mode, they are promising candidates for the initial detector in blind, iterative coherent detectors that operate on the principle of decision feedback.

Desenvolvimento de um dispositivo de baixo custo para medidas por quimiluminescência

A simple and low cost device (ca. US$ 150) that comprises two photodiodes fixed in lab-made Perspex flow cell is proposed for chemiluminescence measurements. The characteristics of the device (large observation window and reduced thickness) allow maximizing the amount of the emitted radiation detected. A sensitivity improvement of ca. 50 % was observed by employing two photodiodes for signal measurements. The performance of the device was assessed by the oxidation of luminol by hydrogen peroxide, yielding a linear response within the range of 2.50 to 500 µmol L-1 H2O2. The detection limit was estimated as 0.8 µmol L-1 hydrogen peroxide which is comparable with those obtained by using equipments based on photomultipliers.