Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconsideration of wind stress, wind waves, and turbulence in simulating wind-driven currents of shallow lakes in the Wave and Current Coupled Model (WCCM) version 1.0

Abstract. Wind stress, wind waves, and turbulence are essential variables and play a critical role in regulating a series of physical and biogeochemical processes in large shallow lakes. However, the parameterization of these variables and simulation of their interactions in large shallow lakes have not been strictly evaluated owing to a lack of field observations of lake hydrodynamic processes. To address this problem, two process-based field observations were conducted to record the development of summer and winter wind-driven currents in Lake Taihu, a large shallow lake in China. Using these observations and numerical experiments, a Wave and Current Coupled Model (WCCM) is developed by rebuilding the wind drag coefficient expression, introducing wave-induced radiation stress, and adopting a simple turbulence scheme to simulate wind-driven currents in Lake Taihu. The results show that the WCCM can accurately simulate the upwelling process driven by wind-driven currents during the field observations. A comparison with a reference model indicates a 42.9 % increase of the WCCM-simulated current speed, which is mainly attributed to the new wind drag coefficient expression. The WCCM-simulated current direction and field are also improved owing to the introduction of wave-induced radiation stress. The use of the simple turbulent scheme in the WCCM improves the efficiency of the upwelling process simulation. The WCCM thus provides a sound basis for simulating shallow lake ecosystems.
Walking in the cities without ground, how 3d complex network volumetrics improve analysis

Pedestrian route choice, wayfinding behaviour and movement pattern research rely on objective spatial configuration model and analysis. In 3D indoor and outdoor multi-level buildings and urban built environments (IO-ML-BE), spatial configuration analysis allows to quantify and control for route choice and wayfinding complexity/difficulty. Our contribution is to compare the interaction of the level of definition (LOD) of indoor and outdoor multi-level pedestrian network spatial models and complexity metric analyses. Most studies are indoor or outdoor and oversimplify multi-level vertical connections. Using a novel open data set of a large-scale 3D centreline pedestrian network which implement transport geography 2D data model principles in 3D, nine spatial models and twelve spatial complexity analyses of a large-scale 3D IO-ML-BE are empirically tested with observed pedestrian movement patterns (N = 17,307). Bivariate regression analyses show that the association with movement pattern increases steadily from R2 ≈ 0.29 to 0.56 (space syntax, 2.5D) and from R2 ≈ 0.54 to 0.72 (3D sDNA) as the 3D transport geography spatial model LOD and completeness increases. A multivariate stepwise regression analysis tests the bi-variate findings. A novel 3D hybrid angular-Euclidean analysis was tested for the objective description of 3D multi-level IO-ML-BE route choice and wayfinding complexity. The results suggest that pedestrian route choice, wayfinding and movement pattern analysis and prediction research in a multi-level IO-ML-BE should use high-definition 3D transport geography network spatial model and include interdependent outdoor and indoor spaces with detailed vertical transitions.
Design, static modeling and simulation of a 5-DOF precise piezoelectric positioner

This paper presents the design, the static modeling and the performances simulation of a five degrees of freedom precise positioner. Based on piezoelectric stack actuators, the positioner is able to perform high resolution x-y-z linear motions and angular motions about x and about y axes. After presenting the design, the static modeling is carried out in order to understand the functioning of the positioner. The simulation of the model is afterwards carried out to estimate the ranges of motions that it can perform. The positioner is very promising in various applications that require dexterity and high resolution displacement such as in images scanning with atomic force microscopes, in micromanipulation or microassembly, etc.
A digital background calibration technique for interstage gain nonlinearity in pipelined ADCs

This paper presents a digital background technique that intentionally exploits multiple dithers to calibrate conversion errors caused by interstage gain error and nonlinearity in high speed pipelined analog-to- digital converters (ADCs). Two independent, zero-mean pseudo-random signals are injected into the multiplying digital-to-analog converter (MDAC) alternately to estimate these errors. Least mean square (LMS) algorithms are adopted to quickly locate and track the calibration parameters. Simulation results are presented for a 800 MSps 12-bit pipelined ADC in a 40 nm CMOS technology , similar to that described by Murmann and Boser [1], Keane et al. [2] and Nan Sun [3] using low-gain amplifiers. With calibration, the signal-to-noise-distortion ratio ( SNDR ) and spurious-free dynamic range ( SFDR ) are improved from 32.74 dB and 43.61 dB to 70.54 dB and 89.8 dB, respectively. The proposed calibration technique has the advantages of simple implementation, arbitrary amplitude pseudo-random signals, and no restriction on the input signal of the ADC.
‘They Wouldn’t Mind Pushing People Off the Bus’: Exploring Power in Practice Theory through the Work of Simultaneous Interpreters

Based on a qualitative interview dataset, this article highlights the power relations in the work experiences of UK-based professional simultaneous interpreters, who provide valuable communication services to users but are constrained by the ‘invisible labour’ arrangements of their job. Adopting a practice theory approach, this study extends available theorisations of power as an effect manifested in performance, by articulating a view of power suffusing from the wider organisation of practices – meanings, competencies, and materialities – which governs social order. By making professional rewards conditional on collaborative engagement with other interpreters, the hiding of failure, and unobtrusive behaviours, the practice of interpreting translates power as the struggle to assert individual visibility. The study contributes to the sociological debate by offering an understanding of power shaped by the situated, practical order of everyday action.
Improving the Quality of Indihome Complaints Service Using Lean Service Method (Case Study of Customer Care Plasa Telkom Solo)

PT. Telkom Indonesia is a company engaged in the telecommunications sector. Nowadays, the necessity for internet networks has increased, notably since the COVID-19 pandemic. Thus, PT. Telkom Indonesia as the largest telecommunications company in Indonesia need to improve the quality of service, especially in the Indihome complaint service process. The Indihome service complaint process often causes many queues so that customers have to wait a long time to be served. This study uses the Lean Service method, by identifying 7 wastes in service companies and then reducing the amount of waste that occurs which causes inefficient and effective service processes. This study also uses VALSAT (Value Stream Analysis Tools) to identify waste in the service system flow. In the Indihome complaint service process, there are the most critical waste, namely the waste of delays and the waste of under-utilized resources. The proposed improvements for waste of delays and waste of under-utilized resources are maximizing the use of VIRSA (Virtual Plasa) machines, educating customers to use MyIndihome application, and conducting regular training for CSR employees. Through value stream mapping current state, it is known that the total time for customers to get service is 1709 seconds and through value stream mapping future state, it is known that the total time for customers to get service is 1468 seconds for each customer.
Applying the Optimal Injected Noise to Signal Estimation via Adaptive Stochastic Resonance

In signal estimation, an optimal estimator is frequently unachievable, because its closed form may not be analytically tractable or is too complex to implement. Alternatively, one can turn to suboptimal yet easily implementable estimators for practical signal estimation tasks. In this paper, a general noise-boosted estimator is designed and the adaptive stochastic resonance method is implemented to simultaneously exploit the beneficial role of the injected noise as well as the learning ability of the estimator parameter. Aiming to effectively improve the estimation performance, we use the kernel function method to find an approximate solution for the probability density function (PDF) of the optimal injected noise. During this process, the noise PDF and the estimator parameter establish a finite dimensional non-convex optimization space for maximizing the estimation performance, which is adaptively searched by the sequential quadratic programming algorithm at each iteration. Two representative signal estimation problems are explored, consisting in estimating a random signal from low-resolution observations, or a deterministic parameter in a heavy-tailed noisy environment. The obtained results demonstrate that this adaptive stochastic resonance method can improve the performance of the suboptimal estimators and bring it very close to that of the optimal estimator.
Evaluation of the Performance of CMIP6 Model Simulations for the Asian-Pacific Region: Perspectives from Multiple Dimensions

A comprehensive climate model assessment from multiple dimensions is critical for model selection to reduce uncertainties. Here, we evaluated the performance of seven models involved in the Coupled Model Intercomparison Project-6 (CMIP6) by comparing the simulated meteorological variables at the near-surface (sea ice cover and sea surface temperature) and pressure levels (air temperature, specific humidity, zonal wind, meridional wind, and geopotential height at 850 hPa, 500 hPa, and 200 hPa) to those using ERA5 reanalysis data for the 1995-2014 period from the perspectives of climatological and interannual variability. Then, a comprehensive rating index approach was applied to rank the models. The results show that the CMIP6 models could mostly reproduce the spatial variability of the climatology. However, there were also systematic biases. The sea ice cover and sea surface temperature exhibited noticeable biases of approximately -13.2% and 0.6 °C, respectively. Additionally, all models underestimated air temperature and geopotential height, while overestimating specific humidity in the middle troposphere and zonal and meridional wind speeds in the upper troposphere. Regarding interannual variability, the CMIP6 models performed well for the variables at a pressure level of 850 hPa and with sea ice cover. Taken together, all variables showed that NorESM2-MM exhibited good performance in terms of climatology, while MPI-ESM1-2-LR exhibited good interannual variability. Overall, in regard to the comprehensive rate index, MPI-ESM1-2-LR performed the best among the seven models. This study provides valuable scientific references for selecting the available CMIP6 models as lateral boundary conditions towards dynamical downscaling over Asian-Pacific area.
CUSTOMER LOYALTY AND PASSENGER SATISFACTION ON LION AIR’S LOW COST CARRIER

This study aims to determine the effect of ticket price and service quality on customer loyalty through passenger satisfaction as an intervening variable on the Low Cost Carrier (LCC ) of Lion Air airlines. Low Cost Carrier airlines which have relatively cheap ticket price, but due to the economic crisis in Indonesia, these air transportation services are relatively expensive compared to the previous year, which according to the Indonesian National Air Carrier Association, the increase reached almost 40-120% for each airline, because the increase that occurred made LCC airlines, especially Lion Air, experience a very drastic decrease in passengers by 35% in 2019, apart from ticket price increases, the quality of service provided by lion air airlines is also still not good so that passengers are not satisfied with Lion Air airlines. This research was conducted at Soekarno Hatta International Airport. The study was conducted using quantitative methods, with a sample of 100 respondents and data were taken using a questionnaire and processed using smart-PLS 3. The results of this study are from 7 proposed hypotheses, 6 of which are accepted and 1 of the hypothesis is rejected, for the rejected hypothesis is the effect of ticket price on the loyalty of Lion Air airline passengers.
Region-based Polarimetric Covariance Difference Matrix for PolSAR Ship Detection

To more effectively detect small ships, in this paper, a novel region-based polarimetric covariance difference matrix [RP] is put forward, which mainly consists of two stages. Briefly speaking, in the first stage, a new pixel representation way is proposed to depict the spatial characteristics of pixel, through which the difference information related to pixel’s local region is calculated as well. In the second stage, the global region difference information of pixel is computed. Finally, we construct [RP] via fusing these two different kinds of information together with a balance factor c. Meanwhile, considering the backscattering energy of ships is useful for ship detection, a new intensity-driven polarimetric notch filter (ID-PNFRP) is also derived from [RP]. Three different datasets are adopted to evaluate the effectiveness of [RP] and ID-PNFRP. Experimental results show that, 1) compared to the polarimetric covariance matrix [C] and the polarimetric covariance difference matrix [P], [RP] is more suitable for ship detection; 2) compared to the original GP-PNF (geometrical perturbation-polarimetric notch filter) and the total power detector SPAN, the proposed method ID-PNFRP can better detect small ships with greater FoM (figure of merit) and TCR (taget-to-clutter ratio) values.
A BVAR Analysis on Channels of Monetary Policy Transmission in Brazil

This article measures the responses of GDP and inflation to a positive shock of the variables that make up the channels of transmission of monetary policy. The results of impulse-response functions of the estimated Bayesian VAR (BVAR) were: an increase in the short-term interest rate (SELIC) leads to a long-term interest rate increasing and consequently a reduction in GDP. Free credit does not have a significant impact on Brazilian GDP, given the low free credit/GDP ratio (Bogdanski et al., 2000). A shock in inflation expectations result in a decreasing trajectory of GDP, a fact consistent with the Fisher effect (Mishkin, 2009); and a shock at SELIC reduces inflation in the first two months, there is no “price puzzle”. A credit shock does not cause significant pressures on inflation. The Inflation does not show a well-defined time path after a shock in asset prices. The decomposition of the variance of the forecast error, in turn, showed that: GDP, in the short term, has its forecast errors explained by its own shocks, 70% on average. However, in the medium term, their forecast errors are explained by their own shocks, around 35%, by inflation shocks, 34%, and by interest rate shocks, 20%. The other transmission channels do not have, in the short and medium terms, significant influence on GDP forecast errors, except the asset prices; and inflation forecast errors are explained, in the short term, mainly by their own shocks, 85% on average. In the medium term, inflation forecast errors are explained 68% by inflation itself, 6% by GDP and the others transmission channels participate individually, with approximately 6%. These results are robust when controlled for commodity prices.
Deep Spatio-Temporal Illuminant Estimation Under Time-Varying AC Lights

Artificial lights, which are powered by alternating current (AC), are ubiquitous nowadays. The intensity of these lights fluctuates dynamically depending on the AC power. In contrast to previous color constancy methods that exploited the spatial color information, we propose a novel deep learning-based color constancy method that exploits the temporal variations exhibited by AC-powered lights. Using a high-speed camera, we capture the intensity variations of AC lights. Then, we use these variations as an important cue for illuminant learning. We propose a network composed of spatial and temporal branches to train the model with both spatial and temporal features. The spatial branch learns the conventional spatial features from a single image, whereas the temporal branch learns the temporal features of AC-induced light intensity variations in a high-speed video. The proposed method calculates the temporal correlation between the high-speed frames to extract the effective temporal features. The calculations are done at a low computational cost and the output is fed into the temporal branch to help the model concentrate on illuminant-attentive regions. By learning both spatial and temporal features, the proposed method performs remarkably under a complex illuminant environment in a real world scenario in which color constancy is difficult to investigate. The experimental results demonstrate that the proposed method produces lower angular error than the previous state-of-the-art by 30%, and works exceptionally well under various illuminants, including complex ambient light environments.
Distinguishing Biological Trends from Adaptation

Models of evolution commonly decompose change into deterministic and stochastic components. Different models, however, produce different concepts of signal and noise. Excursion tests correct for two distinct types of noise, sampling error and phenotypic drift, resulting in two distinct types of signal or trend. A minimal trend is a signal of historical change after correcting for sampling error; a directed trend is a model dependent measure of confidence that selection has occurred (correcting for both sampling error and drift). The history of random walks and excursion tests in paleobiology highlights the conceptual middle ground between historical pattern and underlying processes. In paleobiology, both minimal and directed trends reflect a causally agnostic, trait-level product of evolutionary and environmental processes. Directed trends provide evidence for directional causes, but the identity and relative strength of those causes requires a deeper understanding. Thus, the magnitude of minimal and directed trends should not be interpreted as the strength of selection for a specified trait. They can be a useful stepping stone in that direction when paired with a map of the middle ground and agreement about how genetic, macroevolutionary, and environmental processes contribute to evolutionary change.
Position Error Calibrated Using Screen Coordinate System

GPS-based location tracking system is the optimum way to search where an object is in an outdoor environment. However, location tracking using signals transmitted by GPS satellites has a problem of not receiving proper signals under a building. This problem generates errors on location estimation. To modify position errors incurred by GPS signal loss, this study proposes a measure to minimize GPS-tracked position errors by organizing visual information to screen coordinate system. The proposed system organizes gathered imagery data into cells using a matrix equation for the perspective projection and screen partition formulas, and then tracks positions using GPS information received after inserting gathered GPS information to each cell. According to test results, an error range of about 3-5m existed in Google Earth when a person positioned at the bottom of a building tracked locations using GPS information received from missing GPS signals. When locations were tracked using screen coordinate system, errors remained below 30cm.
Hybrid equivalent source – 3D ray-launching simulation technique for deterministic estimation of radiated emissions of electrical appliances

Abstract In this work, a method for modeling the leaked radiofrequency radiation from electrical appliances is presented, with the aim of obtaining a model for a 3D ray-launching algorithm. The domestic microwave oven is the appliance under analysis, as it radiates a substantial amount of power and it is spread worldwide. The method uses numerical electromagnetic field simulations to obtain the exterior oven radiation. Due to the complexity of the metallic mesh of the oven door, a retrieval process has been implemented in order to accelerate the electromagnetic field simulation. This result is incorporated to a proprietary 3D ray-launching algorithm by obtaining equivalent radiation sources. Finally, the microwave oven leakage is obtained for the complete volume of an indoor scenario. The numerical results are then compared with experimental measurements, with good agreement. The proposed model is useful to predict accurately the leakage of the domestic microwave oven within a complete complex indoor scenario, aiding in further radioplanning considerations.
Experience in the use of a radio-oriented augmented reality navigation system for biopsy of a neoplasm of the lower jaw

Ctt JOurnal | VOLUME 10 | NUMBER 3-4 | OCTOBER-DECEMBER 2021 Anna V. Lysenko 1, Andrey I. Yaremenko 2, Vladimir M. Ivanov 3, Sergey V. Strelkov 3, Elizaveta A. Ivanova 2 1 Department of Maxillofacial Surgery, Research Institute of Dentistry and Maxillofacial Surgery, St. Petersburg, Russia 2 Department of Maxillofacial Surgery, Pavlov University, St. Petersburg, Russia 3 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia Experience in the use of a radio-oriented augmented reality navigation system for biopsy of a neoplasm of the lower jaw Cellular Therapy and Transplantation (CTT). Vol. 10, No. 3-4, 2021 doi: 10.18620/ctt-1866-8836-2021-10-3-4-78-83 Submitted: 06 December 2021, accepted: 17 December 2021
Calculation of atmospheric dispersion factor for accident release from coastal nuclear power

A model of calculating the probabilistic atmospheric dispersion factor for accident release from nuclear power plant (NPP),in which the effect of internal bound layer was taken into account,was proposed.The final accident probabilistic dispersion factor used to evaluate dose,the dose for each pathway and the individual effective dose at the bound of a coastal NPP (0.5? km from the coastline) were estimated.The measured parameters from field atmosphere dispersion experiment on site of a NPP were applied.The result showed that not only the value of accident probabilistic dispersion factor but also the value of individual effective dose predicted were 5.9 times higher than those derived by a traditional model.Hence,the effect of internal bound layer on the accident dispersion factor and dose must be taken into account for coastal NPP when the frequency occurring internal bound layer is too high to be neglected.