In this paper, the results of an experimental investigation for a Y-shaped engine inlet are presented. The experiment is performed at subsonic flow conditions. The main focus is given to time-dependent total pressures measured at the aerodynamic interface plane. Distinctive frequencies carrying high energy contents of the fluctuating total pressures are given and the relation between time-dependent and time-average performance parameters is presented. The cross-correlation coefficients of the high frequency probe readings distributed through the aerodynamic interface plane are also investigated.

In order to minimize the risk of infection during the Covid-19 pandemic, peopleare recommended to keep interpersonal distance (e.g., 1 m, 2 m, 6 feet), washtheir hands frequently, limit social contacts and sometimes to wear a face mask.We investigated how people judge the protective effect of interpersonal distanceagainst the Corona virus. The REM model, based on earlier empirical studies,describes how a person’s virus exposure decreases with the square of thedistance to another person emitting a virus in a face to face situation. In acomparison with model predictions, most participants underestimated theprotective effect of moving further away from another person. Correspondingly,most participants were not aware of how much their exposure would increase ifthey moved closer to the other person. Spectral analysis of judgments showedthat a linear ratio model with the independent variable = (initialdistance)/(distance to which a person moves) was the most frequently usedjudgment rule. It leads to insensitivity to change in exposure compared with theREM model. The present study indicated a need for information about the effectsof keeping interpersonal distance and about the importance of virus carryingaerosols in environments with insufficient air ventilation. Longer conversationsemitting aerosols in a closed environment may lead to ambient concentrations ofaerosols in the air that no distance can compensate for. The results of thestudy are important for risk communications in countries where people do notwear a mask and when authorities consider removal of a recommendation or arequirement to wear a face mask.

We used correlation and spectral analyses to investigate the cognitive structures and processes producing biased judgments. We used 5 different sets of driving problems to exemplify problems that trigger biases, specifically: (1) underestimation of the impact of occasional slow speeds on mean speed judgments, (2) overestimation of braking capacity after a speed increase, (3) the time saving bias (overestimation of the time saved by increasing a high speed further, and underestimation of time saved when increasing a low speed), (4) underestimation of increase of fatal accident risk when speed is increased, and (5) underestimation of the increase of stopping distance when speed is increased. The results verified the predicted biases. A correlation analysis found no strong links between biases; only accident risk and stopping distance biases were correlated significantly. Spectral analysis of judgments was used to identify different decision rules. Most participants were consistent in their use of a single rule within a problem set with the same bias. The participants used difference, average, weighed average and ratio rules, all producing biased judgments. Among the rules, difference rules were used most frequently across the different biases. We found no personal consistency in the rules used across problem sets. The complexity of rules varied across problem sets for most participants.

We consider the spectral analysis of several examples of bilateral birth–death processes and compute explicitly the spectral matrix and the corresponding orthogonal polynomials. We also use the spectral representation to study some probabilistic properties of the processes, such as recurrence, the invariant distribution (if it exists), and the probability current.

Block-structured Markov chains model a large variety of queueing problems and have many important applications in various areas. Stability properties have been well investigated for these Markov chains. In this paper we will present transient properties for two specific types of block-structured Markov chains, including M/G/1 type and GI/M/1 type. Necessary and sufficient conditions in terms of system parameters are obtained for geometric transience and algebraic transience. Possible extensions of the results to continuous-time Markov chains are also included.

Leafy spurge (Euphorbia esula L.) and purple loosestrife (Lythrum salicaria L.) are invasive weeds that displace native vegetation. Herbicides are often applied to these weeds during flowering, so it would be ideal to identify them early in the season, possibly by the leaves. This paper evaluates the spectral separability of the inflorescences and leaves of these plants from surrounding vegetation. Leafy spurge, purple loosestrife, and surrounding vegetation were collected from sites in southeastern North Dakota and subjected to spectral analysis. Partial least-squares discriminant analysis (PLS-DA) was used to separate the spectral signatures of these weeds in the visible and near-infrared wavelengths. Using PLS-DA, the weeds were discriminated from their surroundings with R2 values of 0.86 to 0.92. Analysis of the data indicated that the bands contributing the most to each model were in the red and red-edge spectral regions. Identifying these weeds by the leaves allows them to be mapped earlier in the season, providing more time for herbicide application planning. The spectral signatures identified in this proof of concept study are the first step before using ultra–high resolution aerial imagery to classify and identify leafy spurge and purple loosestrife.

The lithostratigraphic characteristics of the iconic Blue Lias Formation of southern Britain are influenced by sedimentation rates and stratigraphic gaps. Evidence for regular sedimentary cycles is reassessed using logs of magnetic susceptibility from four sites as an inverse proxy for carbonate content. Standard spectral analysis, including allowing for false discovery rates, demonstrates several scales of regular cyclicity in depth. Bayesian probability spectra provide independent confirmation of at least one scale of regular cyclicity at all sites. The frequency ratios between the different scales of cyclicity are consistent with astronomical forcing of climate at the periods of the short eccentricity, obliquity and precession cycles. Using local tuned time scales, 62 ammonite biohorizons have minimum durations of 0.7 to 276 ka, with 94% of them <41 ka. The duration of the Hettangian Stage is ≥2.9 Ma according to data from the West Somerset and Devon/Dorset coasts individually, increasing to ≥3.7 Ma when combined with data from Glamorgan and Warwickshire. A composite time scale, constructed using the tuned time scales plus correlated biohorizon limits treated as time lines, allows for the integration of local stratigraphic gaps. This approach yields an improved duration for the Hettangian Stage of ≥4.1 Ma, a figure that is about twice that suggested in recent time scales.

Using remotely sensed land-cover data in 1994 and 2014, and cross-sectional survey data in 2014, this study examines the association between land use and cover change and agricultural productivity in northern Ghana. We document a significant expansion of crop land and settlements (productive use) at the expense of natural vegetation cover. Land areas converted from natural cover to productive use have higher maize yield (0.17 tons per hectare) and harvest value (1,021 Ghanaian Cedi) compared with those converted from bare soil to productive cover. Moreover, areas that were covered by shrubs or savannah in 1994 were more productive in 2014 relative to bare soils in 1994. Although our data do not allow us to establish causality, the evidence suggests the importance of past land-cover conditions in affecting current agricultural performance, especially in resource-stricken settings where conservation and restoration practices are not as common.

The purpose of this study was to clarify the association between hand, foot, and mouth disease (HFMD) epidemics and meteorological conditions. We used HFMD surveillance data of all 47 prefectures in Japan from January 2000 to December 2015. Spectral analysis was performed using the maximum entropy method (MEM) for temperature-, relative humidity-, and total rainfall-dependent incidence data. Using MEM-estimated periods, long-term oscillatory trends were calculated using the least squares fitting (LSF) method. The temperature and relative humidity thresholds of HFMD data were estimated from the LSF curves. The average temperature data indicated a lower threshold at 12 °C and a higher threshold at 30 °C for risk of HFMD infection. Maximum and minimum temperature data indicated a lower threshold at 6 °C and a higher threshold at 35 °C, suggesting a need for HFMD control measures at temperatures between 6 and 35 °C. Based on our findings, we recommend the use of maximum and minimum temperatures rather than the average temperature, to estimate the temperature threshold of HFMD infections. The results obtained might aid in the prediction of epidemics and preparation for the effect of climatic changes on HFMD epidemiology.

In this paper we seek to characterize the robustness of the ENSO/soybean price relationship and to determine whether it has practical economic content. If such a meaningful relationship exists, the implications could be profound for commodity traders and for public sector investments in climate forecasting capabilities. Also, the validity of economic evaluations of climate impacts and climate forecasts based on ENSO-price independence would come into question. Our findings suggest a relationship between interannual climate and soybean prices, although we are not able to attribute the relationship to ENSO or to say that ENSO is economically important.

Disease detection and control is thus one of the main objectives of vineyard research in France. Monitoring diseases manually is fastidious and time consuming, so current research aims to develop an automatic detection of vineyard diseases. This project explored the use of a high-resolution multi-spectral camera embedded on a UAV (Unmanned Aerial Vehicle) to identify the infected zones in a field. In-field spectrometry studies were performed to identify the best spectral bands for the sensor design. The best models were found to be the function of the grapevine variety considered and the 520-600-650-690-730-750-800 nm bands were found to be the most efficient for all types of grapevines, with an overall classification accuracy of more than 94%.

Tick-borne encephalitis (TBE) is peculiar due to its unstable dynamics with profound inter-annual fluctuations in case numbers – a phenomenon not well understood to date. Possible reasons – apart from variable human contact with TBE foci – include external factors, e.g. climatic forcing, autonomous oscillations of the disease system itself, or a combined action of both. Spectral analysis of TBE data from six regions of central Europe (CE) revealed that the ostensibly chaotic dynamics can be explained in terms of four superposed (quasi-)periodical oscillations: a quasi-biennial, triennial, pentennial, and a decadal cycle. These oscillations exhibit a high degree of regularity and synchrony across CE. Nevertheless, some amplitude and phase variations are responsible for regional differences in incidence patterns. In addition, periodic changes occur in the degree of synchrony in the regions: marked in-phase periods alternate with rather off-phase periods. Such a feature in the disease dynamics implies that it arises as basically diverging self-oscillations of local disease systems which, at intervals, receive synchronizing impulses, such as periodic variations in food availability for key hosts driven by external factors. This makes the disease dynamics synchronized over a large area during peaks in the synchronization signal, shifting to asynchrony in the time in between.

We investigated the seasonality of age-specific tuberculosis (TB) in Japan. To allow the development of TB control strategies for different age groups we used a time-series analysis, including a spectral analysis and least squares method, to analyse the monthly age-specific numbers of newly registered cases of all forms of active TB in Japan from January 1998 to December 2013. The time-series data are reported in 10-year age groups: 0–9, 10–19, …, 70–79, and ⩾80 years. We defined the contribution ratio of the 1-year cycle, Q1, as the contribution of the amplitude of a 1-year cycle to the whole amplitude of the time-series data. The Q1 values in the age groups corresponding to adolescence and middle life (10–39 years) and old age (⩾70 years) were high. The peaks in the active TB epidemics for the ⩾70 years age group occurred in August and September, 1–2 months behind the peaks for the 10–39 years age group (June and July). An active TB epidemic might be attributable to travel by public transport and irregular employment in the 10–39 years age group and immune system suppression by low winter temperatures in the ⩾70 years age group.

Atomic force microscopy (AFM) and laser scanning microscopy (LSM) measurements on a series of specially designed roughness artifacts were performed and the results characterized by spectral analysis. As demonstrated by comparisons, both AFM and LSM can image the complex structures with high resolution and fidelity. When the surface autocorrelation length increases from 200 to 500 nm, the cumulative power spectral density spectra of the design, AFM and LSM data reach a better agreement with each other. The critical wavelength of AFM characterization is smaller than that of LSM, and the gap between the measured and designed critical wavelengths is reduced with an increase in the surface autocorrelation length. Topography measurements of surfaces with a near zero or negatively skewed height distribution were determined to be accurate. However, obvious discrepancies were found for surfaces with a positive skewness owing to more severe dilations of either the solid tip of the AFM or the laser tip of the LSM. Further surface parameter evaluation and template matching analysis verified that the main distortions in AFM measurements are tip dilations while those in LSM are generally larger and more complex.

This paper falls within the context of diagnosis of rotating machines in speed variableregime. Based on simulation signals, this work has the purpose to find relevant indicatorsfor the diagnosis of gear transmissions in a variable regime. Two indicators are proposed;the first indicator is the RMS value applied to the vibration signal divided by itscorresponding instantaneous frequency. The second is the normalised gear frequency byaveraging speed. The gear frequency and averaging speed are estimated from thespectrogram. To test the proposed indicators simulate signals have been used. Thesesignals are the results of a dynamic modelling of the gears transmission and arecalculated by using the Newmark integration diagram. This dynamic modelling takes intoaccount the eccentricity defect.