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Background/aim: Santander, the capital of Cantabria, Spain (172,000 inhabitants) is 7 km from an industrial emission source (IES) of Mn located in a 10,000 inhabitants town (Maliaño) (annual air Mn arithmetic mean = 231.8 ng/m3 ; reference WHO guideline = 150 ng/m3 ). Our objective was to compare the motor function of adult healthy volunteers living in both places. Methods: Cross-sectional study analyzing 130 consecutive participants. Exposure to Mn was assessed in terms of source distance from the IES, by Personal Environmental Monitors (PEMs) carried for 24 h by participants consisting of a portable impactor connected to a personal pump, and by biomarkers (blood, hair and fingernails). The impactor allowed the separation of fine (PM2.5) and coarse (PM10-2.5) particles and for each particle size in-vitro bioaccessibility tests with biologically active fluids were performed to separate the soluble (bio accessible) from the insoluble (non-bioaccessible) fraction. Mean Differences (MDs) adjusted for age, sex, and study level, were obtained for motor function tests results. Results: Regarding Grooved Pegboard, overall mean time to complete the test was 59.31 and 65.27 seconds (Standard Deviation = 10.11 and 11.69) for dominant and nondominant hands respectively. Statistically significant higher times (indicating worse function) were observed when living near the IES in both hands but MDs of only 1.22 and 2.05 seconds were obtained after adjusting for the predefined confounders (p = 0.373 and 0.221 respectively). Regarding Mn levels in their PEMs (in both bioaccessible and non-bioaccessible coarse&fine fractions) higher times were computed in participants with higher levels for the bioaccessible-fine fraction, with a MD that diminished but still yielded statistical significance after controlling for confounding: adjusted MD = 3.01 more seconds; 95%CI (0.44-5.38), p = 0.022. Poorer results were also observed for fingernails levels. Regarding Finger Tapping Test, no statistically significant differences were found with the exception of Mn fingernails levels. Conclusions: Our results suggest poorer motor function as assessed by Grooved Pegboard test in relation to "proximity to IES", "bioaccessible-fine fraction as determined by PEMs and "Mn fingernails levels". However, our findings were affected by confounding, and only the adjusted MD for the Mn bioaccessible-fine fraction remained of sufficient magnitude to maintain statistical significance. This work was supported by the Spanish Ministry of Science, Innovation and Universities through the CTM2017-82636-R Project. This funding source was not involved in the study design; data collection, analysis, or interpretation; the writing of the article; or the decision to submit for publication. Bohdana Markiv also thanks this Ministry for the PhD grant awarded, PRE2018-085152.

Decision-makers often collect and aggregate experts’ point predictions about continuous outcomes, such as stock returns or product sales. In this article, we model experts as Bayesian agents and show that means, including the (weighted) arithmetic mean, trimmed means, median, geometric mean, and essentially all other measures of central tendency, do not use all information in the predictions. Intuitively, they assume idiosyncratic differences to arise from error instead of private information and hence do not update the prior with all available information. Updating means in terms of unused information improves their expected accuracy but depends on the experts’ prior and information structure that cannot be estimated based on a single prediction per expert. In many applications, however, experts consider multiple stocks, products, or other related items at the same time. For such contexts, we introduce ANOVA updating – an unsupervised technique that updates means based on experts’ predictions of multiple outcomes from a common population. The technique is illustrated on several real-world datasets.

We propose a particle-based distributed PHD filter for tracking the states of an unknown, time-varying number of targets. To reduce communication, the local PHD filters at neighboring sensors communicate Gaussian mixture (GM) parameters. In contrast to most existing distributed PHD filters, our filter employs an “arithmetic average” fusion. For particles–GM conversion, we use a method that avoids particle clustering and enables a significance-based pruning of the GM components. For GM–particles conversion, we develop an importance sampling based method that enables a parallelization of filtering and dissemination/fusion operations. The resulting distributed PHD filtering framework is able to integrate both particle-based and GM-based local PHD filters. Simulations demonstrate the excellent performance and small communication and computation requirements of our filter.

The measurement of technical efficiency is a topic of great interest. Since the beginning, many researchers have developed new approaches to gauge technical efficiency, mainly in the non-parametric area of Data Envelopment Analysis (DEA). However, the first measures in DEA, the well-known radial models, only accounted for radial inefficiency, which motivated the introduction in the literature of the so-called Global Efficiency Measures (GEMs); non-oriented and non-radial in nature. Two famous GEMs are the Russell Graph Measure and the Enhanced Russell Graph Measure, also known as the Slacks-Based Measure. These approaches aggregate input and output specific efficiencies through the arithmetic mean, which may not be the most appropriate aggregator function when input and output efficiency ratios are considered, as will be shown. In this paper, in contrast, we propose aggregating input and output specific inefficiencies by applying the geometric average, which will allow us to define new multiplicative versions of the Russell Graph Measures. We also prove some theoretical results and introduce an iterative algorithm, based upon Second Order Cone Programming, to solve the new models. Finally, the implementation of the introduced approaches is empirically illustrated through a data set taken from the literature.

The effect of particle size distribution on the hydrodynamics of dilute-phase pneumatic conveying system was analyzed using computational particle fluid dynamics (CPFD) simulation. The influence of a simulation parameter, i.e., correction factor of drag coefficient (k), on the hydrodynamics of pneumatic conveying system was determined via CPFD simulation. When results of simulation were compared with experimental data of previous studies, the average error of pressure drop per length predicted by the CPFD approach with the correction factor was below 4.4%. Saltation velocity and the pressure drop per unit length declined as the drag force coefficient increased. Simulation results also revealed that the pressure drop per length and the saltation velocity were decreased when the fine powder fraction in the particle size distribution was increased, although the width of particle size distribution was widened, and the standard deviation was increased. Finally, the Relative Standard Deviation (RSD) of pressure drop per length was measured and compared with median diameter (d50), Sauter mean diameter, geometric mean diameter, and arithmetic mean diameter. The RSD of the Sauter mean diameter was 5.8%, approximately twice less than the RSD value of d50 commonly used in pneumatic conveying.

As people desire contact with the natural environment and comfortable living, modern buildings are increasingly incorporating the design of courtyard spaces. Hence, it is of interest to investigate the fungal air quality of courtyard spaces. This study aimed to investigate seasonal patterns of airborne fungal concentration, particlesize distribution, and taxonomic composition by using air microbial samplers and combining culture and molecular techniques. The results indicated that fungal concentration varied between seasons, peaking in autumn (825 ± 260 CFU/m3) and being the lowest in winter (617 ± 197 CFU/m3). Spearman's correlation analysis showed that fungal concentrations were positively correlated with relative humidity and wind speed. The relative humidity and wind speed supported fungal dispersion, whereas temperature negatively affected fungal dispersion in a multiple linear regression model. The fungal concentrations corresponding to “not excellent” in the Air Quality Index (AQI: >50) were higher than those corresponding to “excellent” (AQI: 0–50). The airborne fungal particle sizes in the range 1.1–3.3 μm (>58%) were predominant in all four seasons. In all four seasons, the airborne fungi had count median diameters ranging from 1.60 μm to 1.80 μm, allowing the fungi to penetrate the terminal bronchi. Verticillium (75.9%) and Cladosporium (27.4%) were the most abundant fungal genera in spring and summer, respectively. Flammulina was predominant in autumn and winter, accounting for 35.2% and 31.3%, respectively. Moreover, 14 fungal genera that contained allergenic or pathogenic species were identified in all four seasons. The highest mean average daily dose rates of airborne fungi was found in autumn. These findings will provide information for creating a more reasonable, comfortable, and healthier courtyard space air environment.

The distribution of data presented in many electrophysiological studies is presumed to be normal without any convincing evidence. To test this presumption, the cell membrane capacitance and magnitude of inward rectifier potassium currents were recorded by the whole-cell patch clamp technique in rat atrial myocytes. Statistical analysis of the data showed that these variables were not distributed normally. Instead, a positively skewed distribution appeared to be a better approximation of the real data distribution. Consequently, the arithmetic mean, used inappropriately in such data, may substantially overestimate the true mean value characterizing the central tendency of the data. Moreover, a large standard deviation describing the variance of positively skewed data allowed 95% confidence interval to include unrealistic negative values. We therefore conclude that the normality of the electrophysiological data should be tested in every experiment and, if rejected, the positively skewed data should be more accurately characterized by the median and interpercentile range or, if justified (namely in the case of log-normal and gamma data distribution), by the geometric mean and the geometric standard deviation.

Atmospheric nitrogen dioxide (NO2), which has adverse effects on human health, has significantly changed due to rapid economic growth in Northeast Asia. Trends in tropospheric NO2 vertical column densities (VCDs) can be an indicator of the effectiveness of national environmental policies to reduce NO2 emissions. A number of studies have focused on long-terms trends in NO2 VCDs, mostly relying on arithmetic means obtained from various satellite sensors. The results of such studies may provide limited insights due to the skewed measurement distributions. To analyze these whole data, this study used the lowest 5th, 25th, 50th, 75th, and 95th percentiles (hereinafter referred to as B05, Q1, MED, Q3, and T95, respectively), as well as the arithmetic means, of NO2 VCDs over Northeast Asia (Northeast China, Southeast China, Republic of Korea, and Japan) retrieved from the Ozone Monitoring Instrument (OMI) from 2005 to 2018. This paper presents in priority the trends for the means, B05 (background concentrations), and T95 (high concentrations) in tropospheric NO2. All three categories showed a reversal in their trends from positive to negative at about 2011. However, the absolute results from 2005 to 2018 show the following differences: the mean and T95 decreased (NE China: −0.04 and −0.34, SE China: −0.05 and −0.32, Korea: −0.02 and −0.16, and Japan: −0.01 and −0.24 × 1015 molecules cm−2 yr−1, respectively) while B05 increased (NE China: +0.07, SE China: +0.06, Korea: +0.03 × 1015 molecules cm−2 yr−1), except in Japan (−0.01 × 1015 molecules cm−2 yr−1). We ascribe this discrepancy to a significant increase in the background concentrations (B05) of tropospheric NO2 until 2011 due to intensive industrial activities in Northeast Asia. High concentration (T95) emissions, on the other hand, have substantially decreased since 2011 partly due to strict environmental regulations in the region. These findings require further elaboration in the future using diurnal variations of tropospheric NO2 VCDs from the Geostationary Environment Monitoring Spectrometer (GEMS), as well as the consideration of socioeconomic factors (e.g., economic growth/recession, environmental regulations, etc.).

The paper by Z. Kurac, 2019 deals with a new property, the so-called transfer-stability, characterizing the arithmetic mean. With this property, it is possible to define special forms of arithmetic mean on finite chains. The idempotence property was required for this definition. In this paper, we neglect this necessity and deal only with transfer-stable aggregation functions. Thanks to this fact, it is possible to define these aggregation functions on any finite lattice (hereinafter “lattice”) and not only on finite chains. Transfer-stable aggregation functions can be defined on any finite lattice. Nevertheless, there is a subclass of finite lattices, the so-called transfer-stable lattices, where the behavior of the transfer-stable aggregation functions is simply described because the transfer-stability classes are linearly ordered. Therefore, the main goal of this paper is characterization of these transfer-stable lattices. The second half of the paper deals with some useful properties associated with the lattice of all k-ary transfer-stable aggregation functions.

Survey designs should be efficient as marine survey programs are usually expensive and time-consuming; however, surveys have rarely been evaluated for multiple species. In the present study, we evaluated multispecies fisheries surveys with respect to three influential factors, i.e., sampling methods, estimation methods and sample size. A joint species distribution model (JSDM) developed in north Yellow Sea, China was used as the operating model to simulate the spatial distribution of multiple species simultaneously. We examined the precision of multispecies abundance estimation using diverse sampling methods [random sampling (RDS), systematic sampling (SYS), stratified random sampling (SRS), generalized random-tessellation stratified sampling (GRT) and spatial coverage sampling (SPC)], estimation methods [arithmetic mean (Arm), universal kriging (Ukr), multivariate distribution model (Mvd), and boral model (Brm)], and a range of sample sizes (from 30 to 300). The results showed significant differences in estimation among sampling methods, where GRT and SYS yielded less relative absolute bias (RAB) over all and RDS showed the least precision. Regarding estimation methods, Mvd and Arm showed the best performances and Brm yielded the least precision. Significant interactions existed between sampling and estimation methods. Arm worked best with GRT, likewise Mvd with SYS and Ukr with SPC. SPC and Mvd showed the best performances for a small sample size (N = 30), and all sampling and estimation methods provided similar results for a large sample size (N = 300). Generally, doubling sample size resulted in a decrease of RAB by 0.097 on average, a rate depending on species, sampling and estimation methods. This study contributed to an integrative framework for evaluating designs of multispecies fisheries surveys. Keywords: Multispecies survey, Boral, Sampling methods, Estimation methods, Sample size

The radon concentrations in soil air were measured before and after a rainfall. 226Ra concentration, porosity, moisture content and temperature in soil were measured at Kyungpook National University in Daegu. As the results of measurement and analysis, the arithmetic mean of measured 222Rn concentration increased from 12100 ± 500 Bq/m3 to 16200 ± 600 Bq/m3 after the rainfall. And the measured 226Ra concentration was 61.4 ± 5.7 Bq/kg and the measured porosity was 0.5 in soil. The estimated values of 226Ra concentration and porosity using diffusion model of 222Rn in soil were 60.3 Bq/kg and 0.509, respectively. The estimated values were similar to the measured values. 222Rn concentration in soil increased with depth and moisture content. The estimations were obtained through fitting based on the diffusion model of 222Rn using the measurement values. The measured depth profiles of 222Rn were similar to the calculated depth profiles of 222Rn in soil. We hope that the results of this study will be useful for environmental radiation analysis. Keywords: Radon, Soil, Rainfall, Diffusion model

Surface roughness plays an important role in macro and micro-scale granular behaviors; however, there is currently lack of a unified approach to quantify the roughness of closed outlines and surfaces, which can consider the overall morphological characteristics of particles. This paper proposes approaches that are suitable for roughness evaluation of 2D general-shape closed outlines and 3D general-shape closed surfaces. For 2D closed outlines, the roughness is evaluated by comparing the real outline with the benchmark outline reconstructed based on the Fourier analyses. For 3D closed surfaces, the roughness is calculated by comparing the real surface against the benchmark surface reconstructed by the spherical harmonic analyses. The local deviation as well as the overall roughness of 2D closed outlines, and 3D closed surfaces, can be evaluated via the approach. After analyzing the roughness of two types of particles with different morphological characteristics by the proposed approaches, it is found that the 2D arithmetic average roughness and the 2D root mean square roughness are well correlated, and so are their 3D counterparts. Nevertheless, values of the 2D and 3D indices are not well correlated for each type of particles, and the particles with different texture can be more clearly distinguished from each other based on the 3D roughness parameters than on the 2D counterparts.

Let G be a finite, connected graph. The eccentricity of a vertex v of G is the distance from v to a vertex farthest from v . The average eccentricity of G is the arithmetic mean of the eccentricities of the vertices of G . It was shown that the average eccentricity of a graph of order n and minimum degree δ cannot exceed avec ( G ) ≤ 9 n 4 ( δ + 1 ) + 15 4 , and that this bound is best possible apart from a small additive constant. In this paper we show that for triangle-free graphs this bound can be improved to avec ( G ) ≤ 3 ⌈ n 2 δ ⌉ + 5 . We also show that for graphs not containing a 4-cycle as a subgraph, the bound can be improved to avec ( G ) ≤ 15 4 ⌈ n δ 2 − 2 ⌊ δ 2 ⌋ + 1 ⌉ + 11 2 . We construct graphs to show that the bound for triangle-free graphs is sharp apart from a small additive constant. We also show that the bound for C 4 -free graphs is close to being best possible by constructing for every value of δ for which δ + 1 is a prime power, an infinite sequence of C 4 -free graphs with average eccentricity at least 15 4 n δ 2 + 3 δ + 2 − 5 2 .

Preliminary values of whole organism concentration ratio (CRwo-soil) were derived for terrestrial vertebrates of an Australian tropical savanna environment. Wildlife groups included bird, bat, ground-dwelling mammal and reptile. Sample data for some of the wildlife groups (bird and bat in particular) were limited. The bird and bat CRwo-soil values were generally lower than the ground-dwelling mammal and reptile CRwo-soil values based on the available data. Arithmetic mean CRwo-soil values for two species of native marsupial and two species of non-native placental were not significantly different (p

For a given graph G = (V, E), the degree mean rate of an edge uv ∈ E is a half of the quotient between the geometric and arithmetic means of its end-vertex degrees d(u) and d(v). In this note, we derive tight bounds for the Randić index of G in terms of its maximum and minimum degree mean rates over its edges. As a consequence, we prove the known conjecture that the average distance is bounded above by the Randić index for graphs with order n large enough, when the minimum degree δ is greater than (approximately) ∆1/3 , where ∆ is the maximum degree. As a by-product, this proves that almost all random (Erdös-Rényi) graphs satisfy the conjecture. This research is partially supported by the project 017SGR1087 of the Agency for the Management of University and Research Grants (AGAUR) of the Government of Catalonia. This research has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement No 734922.

According to [5] , the arithmetic mean is a function characterized by four features: it is non-decreasing, idempotent, symmetric and additive. The first three of them can be naturally converted to the theory of posets but the last one generally can not. Due to this problem, we will replace it with another suitable property, which is called transfer-stability. However, we do not get the exact arithmetic mean but some approximation. These functions will be called transfer-stable means. The first aim of the paper is to show that transfer-stable means on a finite chain form a lattice which is isomorphic to the direct power of a finite chain. The second goal is to create a generating set of transfer-stable means, i.e., means that can generate all other transfer-stable means of the same arity by classical composition of functions. The last goal deals with question of how to generate all transfer-stable means of any arity by binary transfer-stable means only. For this problem we define special transfer-stable means composition.

Monitoring the Sustainable Development Goals (SDGs) is an important challenge and strategic opportunity for stakeholders and beneficiaries involved with Agenda 2030 at all levels. To monitor progress across a diverse set of goals with multiple targets and indicators and to track overall progress, Jeffrey Sachs and associates have developed the SDG Index. Although their index is robust and permits comparisons across countries, it neglects the ‘balanced’ and ‘integrated’ nature of the SDGs (set out in Transforming Our World), and exhibits well-known problems associated with the use of an arithmetic mean (which assumes perfect substitution between dimensions). To overcome these difficulties, this paper introduces an adjusted ‘Integrated Sustainable Development Index’ (I-SDI) that can take account of trade-offs and synergies between goals and targets as well as across the economic, social and environmental spheres of sustainable development. This is accomplished by introducing a new aggregation method based on the Multidimensional Synthesis of Indicators (MSI) approach. This approach overcomes well-known problems associated with replacing the arithmetic mean with the geometric mean (a difficulty encountered by the post-2010 HDI). Specifically, it makes an allowance for the heterogeneity of dimensions, while avoiding the tendency of the geometric mean to collapse to zero. In this paper, the I-SDI scores and rankings are compared with those generated by the SDG Index and the geometric mean. Moreover, to capture the heterogeneity within goals, the I-SDI2 is introduced (which applies the MSI method within as well as between goals). By taking account of heterogeneity within and between goals as well as across the economic, social and environmental dimensions of sustainable development, and by capturing synergies and trade-offs among indicators, our study reveals crucial differences in I-SDI scores and rankings that illustrate the value of a more flexible and integrated measure for guiding policymakers and monitor overall progress.

The continuous development in network technologies causes a considerable hike in number of attacks and intrusions. Identification of these threats has become a critical part of security. To fulfill this task, the Intrusion Detection Systems (IDS) were created. Unfortunately, these tools have curse of dimensionality which tends to increase time complexity and decrease resource utilization. As a consequence, it is desirable that important features of network traffic must be analyzed. To obtain these features, previous work has employed a variant of Linear Discriminant Analysis (LDA) called Median Nearest Neighbors-LDA (Median NN-LDA). This approach finds the relevant features by working with network connections that are near to the median of every class. However, Median NN-LDA has an important drawback. It employs the class arithmetic mean vectors in the within and between scatter matrices formulation. As the arithmetic mean is sensitive to outliers, the approach will not produce optimal results. To deal with that, this paper introduces a new robust Median NN-LDA based on the generalized mean. Many experiments on KDDcup99 and NSL-KDD indicate the superiority of the approach over many LDA variants.

In this study were investigated the effects of different moisture levels (4.8, 9.5, 13, 16.7 and 20%, w.b.) during the storage at 10 °C for three months on some mineral compositions and morpho-physiological properties as dimensional (length, width, thickness, arithmetic mean diameter, geometric mean diameter, surface area and volume, sphericity), gravimetric (thousand grain weight, bulk and true densities) and the seed (colour measurement and electrical conductivity) of de-hulled einkorn wheat seeds. Mineral composition of wheat seeds changed with increasing moisture level. In particular, decreases in mineral composition were observed above 16.7% moisture level. Dimensional properties showed increases depending on increased moisture level. It was found that thousand grain weight and true density values increased with increase in moisture level. However, bulk density values were found to decrease with increase in moisture level. The seed colour properties as L*, a*, b*, Chroma, hue angle and Browning index did not change statistically at the end of three months storage with increase at moisture level. The results showed that mineral compositions and functional properties of seeds at moisture level of 9.5% is more suitable than other moisture levels. As a result, high moisture levels during storage can cause degradation of seed quality.

A new method is proposed to determine the original in-depth distribution of composition directly by the deconvolution of measured depth profiling data using the MRI (Mixing-Roughness-Information) depth resolution function. To overcome the ill-conditioned problem that is often experienced in the deconvolution procedure, the regularization method and the TV-Tikhonov algorithm are employed. The method is applied for the case that the original depth-concentration distribution is either a smooth function or a square wave function and the corresponding arithmetic mean errors are determined accordingly. The noise effects from “measured” data on the deconvoluted profile are also quantitatively evaluated.

We use a broad-range set of inflation models and pseudo out-of-sample forecasts to assess their predictive ability among 14 emerging market economies (EMEs) at different horizons (1–12 quarters ahead) with quarterly data over the period 1980Q1-2016Q4. We find, in general, that a simple arithmetic average of the current and three previous observations (the RW-AO model) consistently outperforms its standard competitors—based on the root mean squared prediction error (RMSPE) and on the accuracy in predicting the direction of change. These include conventional models based on domestic factors, existing open-economy Phillips curve-based specifications, factor-augmented models, and time-varying parameter models. Often, the RMSPE and directional accuracy gains of the RW-AO model are shown to be statistically significant. Our results are robust to forecast combinations, intercept corrections, alternative transformations of the target variable, different lag structures, and additional tests of (conditional) predictability. We argue that the RW-AO model is successful among EMEs because it is a straightforward method to downweight later data, which is a useful strategy when there are unknown structural breaks and model misspecification.

This paper discusses the variability of the modelled Vertical Total Electron Content (VTEC) and performance of the latest versions of the International Reference Ionosphere (IRI) model in the estimation of TEC over the mid-latitude regions in the recent high solar activity (2013–2015) years. This is conducted by comparing the pattern of the variations of the VTEC obtained from five ground based Global Positioning System (GPS) receivers installed at different mid-latitude regions and the latest versions of the IRI model (IRI 2007, IRI 2012 and IRI 2016). It has been observed that the measured (GPS-derived) and modelled (IRI 2007, IRI 2012 and IRI 2016) monthly and seasonal diurnal variability of VTEC show the lowest values at around 10:00 UT (04:00 LT) and the highest values at around 20:00 UT (14:00 LT). Moreover, both the measured and modelled VTEC variations generally follow the pattern of the variation of the solar activity, showing enhancement in shifting from 2013 to 2014, and drop again in 2015, with some exceptional months. In the years 2013–2015, the highest measured and modelled seasonal arithmetic mean VTEC values are observed in the March equinox in 2014; while, the lowest measured and modelled VTEC values are observed in the December solstice and June solstice, respectively in 2015. It has also been shown that the IRI 2016 VTEC values are generally larger than those of the IRI 2007 and IRI 2012 VTEC values and tend to respond to variation of the GPS VTEC values better than others, especially in the equinoctial and June solstice months. Moreover, when compared to the IRI 2007 and IRI 2012 versions, the smallest root-mean-square deviations are observed in using the IRI 2016 version, showing that the IRI 2016 version is generally better in capturing the VTEC values with some exceptional months (especially in the December solstice months). Hence, in the December solstice months, the IRI 2007 and IRI 2012 versions are generally better in estimating the VTEC variations as compared to the IRI 2016 version. Moreover, the root-mean-square deviations obtained (either due to overestimations or underestimations) in the IRI 2007 and IRI 2012 versions are very close to each other, proving that the two versions show similar performance in TEC estimation.

The temperature variation in China is closely related to the dynamics of global climate change. In order to reveal its possible connections with global climate during the Holocene, we present a nationwide temperature reconstruction in China for the past 12,000 years, based on multiple proxies with three statistical methods, including empirical orthogonal function, composite-plus-scale, and simple arithmetic average. Our reconstruction shows that the late 20th-century temperature in China is the highest at least over the past millennium. Although the low temperature in the period of 10,000–12,000 yr BP was mainly related to the North Atlantic cool conditions, the reconstructed China's temperature followed solar forcing variations more closely than climatic influence from the North Atlantic. The Asian Monsoon was also closely connected to temperature change in China over the Holocene.

The geometric Bonferroni mean (GeoBM), which was designed as a primitive attempt to extend the Bonferroni mean (BM), has enriched the family of BM-type aggregation functions in a variety of decision-making contexts to model homogeneous relations among certain attributes. Although it is difficult to dispute the versatility of GeoBM-based information fusion techniques, a key disadvantage of existing GeoBM developments is that they provide no specification regarding how the GeoBM should be designed, constructed, and applied, which has led to the existence of disparate GeoBM definitions and non-unified and unsound generalizations. This has resulted in some confusion within the GeoBM field and has thus presented significant barriers to researchers hoping to apply the latest developments in their specific areas of interest. In this study, we propose a novel GeoBM construction based on the generalized BM (GenBM) by selecting suitable components of the GenBM to provide a decomposable descriptive formulation that is easy to understand and interpret. A modified GeoBM (MGeoBM) is also proposed to enhance the capacity for modeling real-life situations. Furthermore, we demonstrate that the concept of generating the GeoBM from the GenBM can be readily adopted in a generalized extended BM (EBM) framework to construct an extended GeoBM (EGeoBM) that can model heterogeneous relations among certain attributes. The proposed calibrated EBM is an accurate update to the standard EBM, as can be seen on noting that independent attributes can be modeled by the arithmetic mean rather than by the power mean. Several natural extensions of the EGeoBM, e.g., the extended MGeoBM (EMGeoBM) and its weighted form, together with their degenerate forms under various assumptions, are discussed and finally applied to a linguistic 2-tuple environment. Comparisons among several existing linguistic 2-tuple aggregation functions demonstrate that the proposed EMGeoBM performs more robustly than the EBM, providing relatively stable alternative rankings.

While the aerosol optical depth (AOD) product from the Visible Infrared Imaging Suite (VIIRS) instrument has proven effective for estimating regional ground-level particle concentrations with aerodynamic diameters less than 2.5 μm (PM2.5), its performance at larger spatial scales remains unclear. Despite the wide application of statistical models in building ground-level PM2.5 satellite remote sensing retrieval models, a limited number of studies have considered the spatiotemporal heterogeneities for model structures. Taking China as the study area, we used the VIIRS AOD, together with multi-source auxiliary variables, to develop a spatially structured adaptive two-stage model to estimate ground-level PM2.5 concentrations at a 6-km spatial resolution. To this end, we first defined and calculated a dual distance from the ground-level PM2.5 monitoring data. We then applied the unweighted pair-group method with arithmetic means on dual distances and obtained 13 spatial clusters. Subsequently, we combined the time fixed effects regression (TEFR) model and geographically weighted regression (GWR) model to develop the spatially structured adaptive two-stage model. For each spatial cluster, we examined all possible combinations of auxiliary variables and determined the best model structure according to multiple statistical test results. Finally, we obtained the PM2.5 estimates through regression mapping. At least seven model-fitting data records per day made a good threshold that could best overcome the model overfitting induced by the second-stage GWR model at the minimum price of losing samples. The overall model fitting and ten-fold cross validation (CV) R2 were 0.82 and 0.60, respectively, under that threshold. Model performances among different spatial clusters differed to a certain extent. High-CV R2 values always exceeded 0.6 while low-CV R2 values less than 0.5 also existed. Both the size of the model-fitting data records and the extent of urban-industrial characteristics of spatial clusters accounted for these differences. The PM2.5 estimates agreed well with the PM2.5 observations with correlation coefficients all exceeding 0.5 at the monthly, seasonal, and annual scales. East of Hu’s line and north of the Yangtze River were characterized by high PM2.5 concentrations. This study contributes to the understanding of how well VIIRS AOD can retrieve ground-level PM2.5 concentrations at the national scale and strategies for building ground-level PM2.5 satellite remote sensing retrieval models.

Framboids, microscopic sub-spheroidal aggregates of pyrite microcrystals, are found in sediments of all ages and framboid size-frequency distributions are widely used to determine the oxygenation states of paleo-waters. Sedimentary framboid populations display unimodal log-normal size distributions as a consequence of the multiplicative central limit theorem in probability theory. The application of additive statistics to framboid populations and their consequent characterization in terms of arithmetic means and standard deviations is wrong because it predicts a subset of framboids with negative diameters. A meta–analysis of 377 sets of measurements of the diameters of 48,063 pyrite framboids from 104 sediment and sedimentary rock locations shows that the geometric mean diameter of sedimentary framboids is 6.2 μm and the geometric standard deviation is 1.5. Ninety-five percent of all sedimentary framboids have geometric mean diameters between 2.9 and 13.9 μm. The geometric mean diameter of modern syngenetic framboids formed within euxinic water columns is 4.7 μm and that of diagenetic framboids formed within sediments is 6.7 μm. The estimated measurement error is ±10%. Framboid mean diameters can be used to help discriminate the oxygenation state of paleo-waters. A minimum number of 30 measurements is required and ideally ≥100 measurements are recommended. The conflicting evidence reported in the literature for the application of framboid size-frequency measurements results mainly from the intrinsic nature of statistical analyses: there is always a finite chance that a particular framboid size-frequency distribution is a result of either syngenetic or diagenetic processes. Including the systematic stereological error in framboid size measurements, the geometric mean size range for syngenetic framboids is 2.9–10.9 μm and that for diagenetic framboids 3.1–20.9 μm. This suggests a significant overlap in geometric mean diameters of framboids from euxinic and non-euxinic environments between ~3 and ~11 μm. Geometric mean framboid diameters within this size range are not robust proxies for paleo-water oxygenation conditions. The origin of the smaller sizes of syngenetic compared with diagenetic framboids appears to be related to the limited time available for framboid crystal growth within the water column. The statistical uncertainty in assigning particular framboid size-frequency distributions to defined oxygenation conditions results mainly from (a) some diagenetic framboids forming over a limited time, thereby also producing smaller framboids and (b) mixtures of syngenetic and diagenetic framboid populations through unavoidable time-averaging of samples. The absence of any significant differences in the sizes of modern and ancient framboids indicates that framboids do not continue to grow over extended time periods: once formed they remain the same over geologic time periods and only change through infilling, overgrowth and recrystallization. The result is that ancient framboids may sample the contemporary paleoenvironment in the sedimentary system in which they are found.

The gridding process applied to satellite-retrieved cloud properties results in the loss of certain information. In this study, we analyzed the error associated with using gridded cloud optical depth (τ) in calculating radiative forcing from the perspective of the distribution pattern of τ. Utilizing the simulated results from SBDART (Santa Babara DISORT Atmospheric Radiative Transfer), we calculated this error in ideal probability distribution functions (PDFs) of τ while keeping the average τ constant, and then used the τ retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) pixel-level observations to simulate real case studies. The results from both the ideal experiments and real case studies indicate that there is a large dependence of the error caused by gridding process on the PDF of τ. The greatest relative error occurs in the cases when τ fits a two-point or uniform distribution, reaching 10–20%, while this error is below 5% when τ follows a binomial distribution. From the analysis of MODIS pixel-level data from June 2016, we found that the PDFs of τ within one grid point (1° × 1°) could not be simply described by a normal distribution. Although using the logarithmic mean of τ controls the error effectively, the error can still be up to 4%. Our study suggests that using gridded data (especially the arithmetic mean) to calculate radiative forcing may result in uncertainty to a certain extent, which depends strongly on the distribution pattern of cloud properties within the grid point. The PDF of cloud properties should be comprehensively considered in the gridding process in the future.

Peanut products were the target of the largest food recall in United States history from 2008 to 2009, with more than 3,200 products implicated, economic losses estimated at $1 billion, and more than 700 reported illnesses and 9 deaths. Predictive modeling tools such as quantitative microbial risk assessment can be used to aid processors in making risk management decisions that may reduce the chances of foodborne illness, but published risk assessment for peanuts is not currently available. A quantitative microbial risk assessment was performed to quantify salmonellosis risk from consumption of peanuts in the United States. Prevalence and concentration data for Salmonella on raw, shelled peanuts were used in combination with probability distributions of simulated log reductions achieved during production steps before consumption. Data for time-temperature combinations used in each step were obtained from published literature, industry surveys, or expert opinion, and survival data were obtained from the literature. A beta-Poisson dose-response model was used to predict probability of illness from ingestion of Salmonella cells. The model predicted 14.2 (arithmetic mean) or 0.0123 (geometric mean) illnesses per year. Sensitivity analysis showed that thermal inactivation log reductions applied had the biggest impact on predicted salmonellosis risk, followed by consumer storage time, Salmonella starting concentration, Salmonella starting prevalence, and number of originally contaminated 25-g servings per originally positive 375-g sample. Scenario analysis showed that increasing log reduction variability increased mean salmonellosis risk. Removing the effect of storage on Salmonella survival increased the arithmetic and geometric means to 153 and 0.598 illnesses per year, respectively. This study indicated that the risk of salmonellosis from consumption of peanuts can be lowered by reducing field contamination, control of storage steps, and monitoring of appropriate critical limits in peanut roasting.

Simultaneously measured luminosity and magnetic field induced by the return strokes in typical upward and downward flashes occurring on the 600 m-tall Canton Tower were presented. The correlation between peak relative luminosity and peak relative magnetic field induced by return strokes were examined for 4 upward and 4 downward flashes. All the flashes contained 3 or more return strokes and all the return strokes in a same flash followed the same path. Luminosity of the lightning channel close to the top of the Canton Tower exhibited characteristics of pronounced initial peak with 20–90% rise time of about 5.2 μs (arithmetic mean value, based on 43 samples) for subsequent strokes, which was inferred to be related to the secondary (typically largest) peak current at the top of the Canton Tower. The magnetic field induced by subsequent strokes exhibited characteristics of pronounced initial peak with 20–90% rise time of about 1.2 μs (arithmetic mean value, based on 47 samples). The initial peak magnetic field was modified to proportionally represent the largest peak current at the top of the Canton Tower. Roughly linear and quadratic relation between the initial peak luminosity and modified peak magnetic field were found for subsequent strokes in both upward and downward flashes. The quadratic relation fit the data slightly better than the linear relation. The ratio of peaks of luminosity to magnetic field of the downward first stroke were considerably larger than those of the subsequent strokes, the possible reasons were also discussed.

Background Increased public awareness of PFAS contamination in Australia has resulted in serum biomonitoring efforts in individuals in potentially affected communities. However, population-based reference values for assessing whether individual results exceed the typical range in the Australian general population are not currently available. Objective Estimate population upper bound reference values based on updated serum PFAS concentrations in pooled samples from southeast Queensland, Australia and population variation observed in the US National Health and Nutrition Examination Survey (NHANES) datasets. Methods We calculated ratios of 95th percentile to arithmetic mean (P95:AM ratios) using data from the NHANES 2013–14 and 2015–16 cycle samples for frequently detected PFASs: PFOA, linear and branched PFOS, perfluorononanoate (PFNA), perfluorodecanoate (PFDA), and perfluorohexanesulfonate (PFHxS). We estimated Australian age-specific means for PFAS using pooled serum samples collected in 2014–15 and 2016–17. We used the P95:AM ratios to estimate 95th percentile concentrations in the Australian population based on the results of the 2016–17 pooled samples. Results and conclusions P95:AM ratios for each PFAS were similar across NHANES cycle and age group, so overall compound-specific ratios were estimated for PFOA (2.1), PFNA (2.4), PFDA (2.7), PFHxS (2.7), and linear (2.4) and summed PFOS (2.3). Australian mean PFAS concentrations continued previously reported declining trends. The estimated P95 values can be used as preliminary substitutes for more rigorous population reference values to identify samples with clearly elevated serum PFAS concentrations in Australian biomonitoring efforts. Given uncertainties and variability inherent in this evaluation, the estimated P95 values should be interpreted with caution. Mean and estimated P95 serum PFAS concentrations in Australia should continue to be monitored to document declining trends in population serum concentrations.

This paper mainly discusses the improvement of performance of the International Reference Ionosphere (IRI) model in estimating the variation of the Vertical Total Electron Content (VTEC) over the mid latitude American regions during the relatively low (2008–2010) and relatively high (2012) solar activity years. This has been conducted employing the VTEC values obtained from the dual frequency ground based Global Positioning System (GPS) receivers located at Mineral Area Community College, MACC (37.85°N, 269.52°W) and Mississippi County Airport, MAIR (36.85°N, 270.64°W), and the latest versions of the IRI online model (IRI 2007, IRI 2012 and IRI 2016). The study mainly focuses to compare the trend of variability of the monthly and seasonal modeled VTEC values (IRI 2007 VTEC, IRI 2012 VTEC and IRI 2016 VTEC) with the corresponding measured VTEC values (GPS VTEC). The overall results show that the IRI VTEC values (almost in all versions of the model) are generally smaller than the GPS VTEC except after about 15:00 UT (09:00 LT) in the December solstice when the Sun shifts to the high solar activity. On the contrary, overestimations of the VTEC values by the model are observed in traversing from the low solar activity (2008) to high solar activity (2012) phase, especially after about 15:00 UT (09::00 LT) with the IRI 2016 version showing the highest. In general, the IRI 2007 and IRI 2012 versions show similar monthly and seasonal underestimations or overestimations showing that the two versions have almost similar performance. The IRI 2016 version is generally better in capturing both the diurnal and arithmetic mean GPS VTEC values with some exceptional months and seasons as compared to those of the IRI 2007 and IRI 2012 versions.

This paper discusses the monthly and seasonal variation of the total electron content (TEC) and the improvement of performance of the IRI model in estimating TEC over Ethiopia during the solar maximum (2013–2016) phase employing as reference the GPS derived TEC data inferred from four GPS receivers installed in different regions of Ethiopia; Assosa (geog 10.05°N, 34.55°E, Geom. 7.01°N), Ambo (8.97°N, 37.86°E, Geom. 5.42°N), Nazret (8.57°N, 39.29°E, Geom. 4.81°N) and Arba Minch (6.06°N, 37.56°E, Geom. 2.62°N). The results reveal that, in the years 2013–2016, the highest peak GPS-derived diurnal VTEC is observed in the March equinox in 2015 over Arba Minch station. Moreover, both the arithmetic mean GPS-derived and modelled VTEC values, generally, show maximum and minimum values in the equinoctial and June solstice months, respectively in 2014–2015. However, in 2013, the minimum and maximum arithmetic mean GPS-derived values are observed in the March equinox and December solstice, respectively. The results also show that, even though overestimation of the modelled VTEC has been observed on most of the hours, all versions of the model are generally good to estimate both the monthly and seasonal diurnal hourly VTEC values, especially in the early morning hours (00:00–03:00 UT or 03:00–06:00 LT). However, it has also been shown that the IRI 2007 and IRI 2012 versions generally perform best in matching the diurnal GPS derived TEC values as compared to that of the IRI 2016 version. In addition, the IRI 2012 version with IRI2001 option for the topside electron density shows the highest overestimation of the VTEC as compared to the other options. None of the versions of the IRI model are proved to be able to capture the effects of geomagnetic storms.

With almost a decade of operational experience from an amine-based post combustion carbon capture plant in Norway, Technology Centre Mongstad has under multiple occasions and operating scenarios monitored the work environment exposure risk for such facilities. Primary focus has been on concentrations of Nitrosodimethylamine in the work environmental atmosphere. This paper presents some findings from work environmental gas sapling collected between 2012 and 2020, where Thermosorb-N filters, impingers and PTR-MS were used for sampling. The main objective has been to investigate work environment exposure risk in a CO2 capture plant. The findings show that the median outdoor background concentration during the different test campaigns have been 0.2 ng/m3(Arithmetic Mean 5.8 ng/m3, range

Statistics Finland has relatively long experience in constructing indices of prices of old flats using the hedonic approach where regression analysis and classification of flats (i.e. stratification) are combined. Practically this means: First the price model is based on the fixed effect model applied for separate regions and second the quality adjustment is performed within each regional cell in a classification (i.e. inside stratums) using so called Oaxaca decomposition. The hedonic price index is computed by aggregating regional cell level (i.e. stratum level) quality adjusted prices using the logarithmic Laspeyres formula. In this study we develop hedonic price index for new flats. In outline, we use similar methods as in case of old flats, but we develop Oaxaca decomposition in the cell or stratum level for unweighted and weighted arithmetic and geometric means – these are our first new results for hedonic methods. For that we develop new theorems for price aggregation from observed prices into stratum aggregates by logarithmic mean. New theorems of price aggregation are performed to semilogarithmic price models. Our price aggregation form observation level into strata leads to three new decomposition average prices – decompositions for unweighted arithmetic average prices and weighted arithmetic and geometric average prices. The stratum level Oaxaca decomposition for different price aggregates, that is, quality adjusted price changes and quality corrections, are aggregated using several basic (i.e. Laspeyres, Paasche, log-Laspeyres, log-Paasche,…) and excellent index number formulas (i.e. Tornqvist, Fisher, Mongomery-Vartia,…). The price aggregation is performed separately for weighted and unweighted arithmetic and geometric average prices. The construction strategy of index series in this study is based on the base strategy. By this strategy index series are free of chain error (or drift). Our test data is a high-quality register data on all free-market transactions of dwellings in new blocks of flats and terraced houses. Data includes statistical unit specific information of unit prices, quantities, values and of some unit specific quality characteristics form 2010/I to 2018/IV being quarter data. The quarter data includes about 2000 – 3000 observation per a quarter.

Analytic Hierarchy process (AHP) is an effective approach for dealing with Multi Criteria Decision Problem (MCDM). This paper investigates AHP in Intuitionistic Fuzzy environment. Here comparative judgments are taken in the form of Triangular Intuitionistic fuzzy number (TIFN). The elements of the comparison matrices are transformed into Interval valued Intuitionistic Fuzzy number by using Nearest Weighted Intuitionistic Interval Approximation (NWIIA) which is introduced in this paper. Then, the transformed matrix is changed in to a crisp matrix by using score function. Priority values are calculated by Arithmetic mean method. This process is applied to the supplier selection problem from the paper in the literature with the same data. It is found that this method yields the same result as that of the paper more easily.

In the practical application of node positioning in the Internet of Things (IOT), the distribution of beacon nodes is generally non-uniform, so there is a certain error in positioning accuracy. In order to make the positioning more accurate, The MMSDV-Hop localization algorithm which improved DV-Hop localization algorithm is proposed in this paper. At first, this algorithm needs to determine the valid beacon nodes in a local range by selecting threshold value, and after using minimization criterion of mean-square error and correcting to obtain the final average hop distance. The dynamic weight is added with the hop number and the number of valid nodes as weights to determine the distance between the unknown nodes and the beacon nodes. A Weighted centroid localization algorithm and a weighted least square method are used to obtain an estimated position separately and the final position is determined by the arithmetic mean value of the two estimated positions. The Matlab simulation experiment shows that compared with the DV-Hop localization algorithm, the improved MMSDV-Hop localization algorithm has increased significantly in the positioning accuracy.

With commercialization of deep learning (DL) models, daily precision dietary record based on images from smartphones becomes possible. This study took advantage of DL techniques on visual recognition tasks and proposed a suite of big-data-driven DL models regressing from food images to their nutrient estimation. We established and publicized the first food image database from the Chinese market, named ChinaMartFood-109. It contained 10,921 images with 23 nutrient contents, covering 18 main food groups. Inception V3 was optimized using other state-of-the-art deep convolutional neural networks, achieving up to 78 % and 94 % for top-1 and top-5 accuracy, respectively. Besides, this research compared three nutrient estimation algorithms and achieved the best regression coefficient ( R 2 ) by normalization + AM compared with arithmetic mean and harmonic mean, validating applicability in practice as well as theory. These encouraging results provide further evidence supporting artificial intelligence in the field of food analysis.

239Pu and 237Np are long-lived radionuclides that emit alpha rays, and once released into the environment, they are present there for a long period of time. Therefore,239Pu and 237Np are important radionuclides in the safety assessment related to geological disposal of radioactive waste because of the possibility of long-term exposure to humans. Mobilities of these radionuclides in the environment are of particular interest; therefore, in this study, we have made the first-time determination of the soil-soil solution distribution coefficient (Kd, L/kg) using global fallout 239Pu and 237Np in soil. The Kd values were determined by extracting these radionuclides from 23 soil samples using a laboratory batch method. The desorption Kd values of 239Pu were found to vary from 3.2 × 103 to 1.4 × 105 L/kg, and their geometric mean (GM) and arithmetic mean (AM) were 2.3 × 104 L/kg and 3.2 × 104 L/kg, respectively. The desorption Kd values of 237Np ranged from 8.9 × 102 to 2.1 × 104 L/kg, and their GM and AM were 4.1 × 103 L/kg and 6.4 × 103 L/kg, respectively. A comparison between the obtained Kd values of 239Pu and 237Np indicated that the former were about 6-fold higher than the latter in Japanese paddy field soils. Pearson's correlation analysis suggested that the main factors contributing to the sorption and desorption of Pu isotopes in Japanese paddy soils were related to the amounts of Fe and Mn oxides, while the sorption and desorption of 237Np in them would be controlled by an ion-exchange reaction, and/or complex-formation with organic matter, especially in Fluvisols.

Fibre print-through on the surfaces of composites emerges as a consequence of the heterogeneous mix of matrix and reinforcing fibres and is one of the obvious surface imperfections that differentiates them from conventional materials. Visible surfaces in the body shell of vehicles demand high Class A requirements without any surface imperfections. Currently, fibre print-through on glossy painted surfaces is evaluated subjectively by human auditors. An overreliance on subjective human evaluation has arisen due to a lack of methods and parameters for characterising this phenomenon. To understand which characteristics are responsible for human perception and to determine suitable parameters for the evaluation of print-through effects, the subjective perception of 25 participants measured by multidimensional scaling is correlated to a fitted parameter regarding fibre print-through and conventional parameters such as long- or shortwave, or the arithmetic mean R a . The comparison of various characteristics of fibre print-through to coated aluminium enables a limiting value to be set based on perception.

In this study, a techno-economic analysis of the capacity of Morocco to produce hydrogen from solar energy has been conducted. For this reason, a Photovoltaic-electrolyze system was selected and the electricity and hydrogen production were simulated for 76 sites scattered all over the country. The Global Horizontal Irradiation (GHI) data used for the simulation were extracted from the CAMS-Rad satellite database and meteorological stations at ground level. Before simulations, the accuracy of the GHI values from the satellite dataset has been checked, and their uncertainties was calculated against accurate data measured in-situ. After that, the simulated values of the hydrogen mass were interpolated using a GIS software to create a Hydrogen production map of Morocco. Finally, an economical investigation of electricity and hydrogen production costs has been conducted by calculating the L C O E and L C O H 2 . Results show that the satellite dataset has a mean average deviation of 6.8% which is a very acceptable error rang. Also, it was found that Morocco have a high potential for hydrogen production, with a daily annual production that varies between 6489 and 8308 Tons/km 2 . Moreover, the cost of electricity and hydrogen production in the country are in the range of 0.077–0.099 $/kWh and 5.79–4.64 $/Kg respectively. The findings of this study are with high importance as they provide an overall perspective of the country potential of hydrogen production for policy makers and investors, and it was motivated by the lack of information on the subject in the literature since it's, at the best of our knowledge, the first study assessing the hydrogen production from solar for the whole country.

Chi-square statistics of the uncertainty weighted mean, which is a linear estimator, is widely used in data analysis of inter-laboratory comparison. However, the chi-square statistics of other linear estimators is not investigated. In this study, a modified chi-square statistics, which comprises the linear estimator, is proposed under the condition that comparison results are Gaussian distributed with a common mean. The proposed statistics is analyzed through Monte Carlo simulation by combining the weights of linear estimator into a multi-dimension vector. Simulation results show that the proposed statistics is (n−1)th-order chi-square distributed when the weights vector of linear estimator is located in a particular subspace, which is influenced by the uncertainties of participants. Furthermore, this chi-square statistics of arithmetic mean is applied to the common mean and random effects models as examples. For the common mean model, the statistics can be applied to the hypothesis testing of arithmetic mean; for the random effects model, the statistics can be applied to the variance estimation of random effects.

The promulgation and implementation of the Air Pollution Prevention and Control Action Plan (APPCAP) have greatly accelerated air quality improvements in China. In this study, these improvements were assessed and analyzed using arithmetic mean and percentile methods. Air quality status and trends were illustrated meticulously. Air pollution risks remaining since the implementation of the APPCAP were also identified. In addition, a complex network correlation model was created and used to demarcate highly inter-correlated regions within China, which were identified using long-term PM2.5 concentration data. The results indicate that the annual mean PM2.5 concentration decreased by more than 30% throughout the country since the implementation of the APPCAP. However, more than 1 billion people were still exposed to polluted air containing PM2.5 concentrations exceeding the WHO Interim Target-1 (WHO IT-1). Cities with populations of more than 10 million were generally among the most polluted regions in China, while PM2.5 concentrations in locations with populations of less than 1 million met WHO IT-1 standards. Moreover, PM2.5 network correlation analysis defined 7 key Joint Prevention and Control of Atmospheric Pollution (JPCAP) regions with strong synchronicity in PM2.5 mass concentrations; these results suggest that JPCAP could be implemented separately with in each of these demarcated regions. The atmospheric pollution control concepts and methods proposed herein are also broadly applicable for the implementation of JPCAP policies in other regions worldwide.

Monitoring of concentrations of radon (222Rn) and gamma level in underground uranium mines is essential to minimise the radiation exposure of miners within the prescribed limits stipulated by regulatory agencies. This paper presents the quantitative assessment of concentrations of 222Rn and gamma radiation level at the different working places being operated at various depths of Narwapahar mine. Equilibrium Equivalent Radon (EER) concentration was found to be in the range varying from 60 to 850 Bq m−3 with a geometric mean of 289 Bq m−3 and geometric standard deviation of 1.94. The average value of EER in the mine was estimated to be about 29% of action level of 1000 Bq m−3 recommended by International Atomic Energy Agency (IAEA). Gamma radiation was found to be in the range of 0.73–6.15 µGy/h with arithmetic mean of 2.52 µGy/h and standard deviation of 1.49 µGy/h. Its average was calculated to be 31% of the derived regulatory limit of 8 µGy/h for 8 h working period in the mine. Furthermore, comparisons of EER and gamma radiation at various working places reveal that concentrations of EER are poorly correlated with grade of uranium ore whereas gamma radiation levels depend on it. The total annual radiation exposure of miners to radon and its daughters and gamma radiation in Narwapahar mine was evaluated to be 4.06 mSv/y, which was about of 20% of the prescribed limit of 20 mSv/y recommended by International Commission on Radiological Protection (ICRP). Thus it may be concluded that working condition of Narwapahar mine is considered as safe due to good ventilation condition of the mine and other control measures.

There is always more than one method can be employed to reconstruct a traffic accident and then more than one result can be obtained. How to describe these different results becomes an issue. Two solutions were given, the first is to fuse different results to one result, while the other is to rank different results according to their credibility. Methods based on the Ordered Weighted Averaging (OWA) operator and Uncertain Ordered Weighted Averaging (UOWA) operator were proposed to fuse different certain results and different interval results to one result, respectively. And methods based on the Combination Weight Arithmetic Average (CWAA) and OWA operators were proposed to rank different certain or interval results. Finally, a true vehicle-motorcycle accident was given to demonstrate these proposed methods, results showed that all methods work well in practice. If the calculation uncertainty was not considered, the fused result 64.56km/h and a ranked vector can be obtained; if the calculation uncertainty was considered, the fused result [62.13, 68.13]km/h and a ranked interval number set can be obtained. Because that all final results were obtained by employing widely used mature operators, they deserve to be trusted. The research provides more reliable choices to describe different results obtained from different methods in accident reconstruction.

Surface roughening is often applied to various devices, such as orthopedic and dental implants , in order to promote bone-implant attachment (osseointegration). In this study, we investigate the influence of pure waterjet peening on a generated random metallic surface. The deformation of the substrate, the height distributions, material ratio curves of deformed surfaces, and 12 area roughness parameters were analyzed for different impact velocities, ranging from 100 m/s to 700 m/s, and different initial arithmetic mean heights ( Sa), ranging from 0.62 μm to 1.88 μm. As the impact velocity increases, the height distribution becomes wider. The dispersion parameters Sa and Sq, extreme parameter Sz, and asymmetry parameter Ssk all reach their higher values at a higher impact velocity . The root mean square height Sq relates to surface energy where both cell adhesion and protein adsorption can be enhanced by a higher surface energy. The negative skewness Ssk surface obtained from the waterjet peening process corresponds to improved load bearing surface since most peaks can be worn away quickly, thereby providing a good contact condition for the implant and surrounding tissues. The material ratio curves obtained at different impact velocities demonstrate that higher impact velocity results in higher values of valley depth ( Svk), which indicates a larger available surface area for cell adhesion, proliferation/differentiation. It is recommended that when describing the roughness in the context of cell adhesion research, the roughness parameters Sq, Ssk, Svk be reported as a minimum set.

Metafrontier-based methodologies have gained in popularity to assess the technology gaps of Decision Making Units (DMUs). One important indicator in this context is the technology gap ratio at the group level. Indeed, in metafrontier contexts, DMUs are partitioned into groups, capturing the heterogeneity present between DMUs. To date, no aggregation scheme has been suggested for this task. In practice, the arithmetic average is used. In this paper, we propose an alternative aggregation procedure, based on economic optimisation behaviour, given by the model, and easy to use and to interpret in practice. We apply our method to the case of 10 European sectors during the period 1995–2015. It represents a unique opportunity to apply the metafrontier methodology, and in particular, our aggregation scheme to sectors over a long period. Our findings reveal important patterns useful for policy-makers.

In [Characterizations of the differential uniformity of vectorial functions by the Walsh transform, IEEE Transactions on Information Theory 2017], the author has characterized differentially δ-uniform functions by equalities satisfied by their Walsh transforms. This generalizes the characterization of APN functions by the fourth moment of the Walsh transform. We study two notions which are related: (1) the componentwise APNness (CAPNness) of ( n , n ) -functions, which is a stronger version of APNness, related to the characterization by the fourth moment, in which the arithmetic mean of W F 4 ( u , v ) when u ranges over F 2 n and v is fixed nonzero in F 2 n equals 2 2 n + 1 (2) the componentwise Walsh uniformity (CWU) of ( n , m ) -functions ( m = n , resp. m = n − 1 ), which is a stronger version of APNness (resp. of differential 4-uniformity) related to one of the new characterizations, in which the arithmetic mean of W F 2 ( u 1 , v 1 ) W F 2 ( u 2 , v 2 ) W F 2 ( u 1 + u 2 , v 1 + v 2 ) when u 1 , u 2 range independently over F 2 n and v 1 , v 2 are fixed nonzero and distinct in F 2 m , equals 2 3 n . Concerning the first notion, it is known from Berger, Canteaut, Charpin and Laigle-Chapuy that any plateaued function is CAPN if and only if it is AB and that APN power permutations are CAPN. We prove that CAPN functions can exist only if n is odd; this solves an eleven year old open problem by these authors. Concerning the second notion, we show that any crooked function (and in particular any quadratic APN function) is CWU, but we observe also that other APN functions like Kasami functions and the inverse of one of the Gold APN permutations are CWU for n ≤ 11 . We show that the CWUness of APN power permutations is equivalent to a property of Δ F = { F ( x ) + F ( x + 1 ) + 1 ; x ∈ F 2 n } . This new property, that we call cyclic-additive difference set property, is more complex than the cyclic difference set property (proved in the case of Kasami APN functions by Dillon and Dobbertin). We prove it in the case of the inverse of Gold function. In the case of Kasami functions, we observe that the cyclic-additive property is also true for n ≤ 10 even and we leave the proof of the CWUness and the cyclic-additive property as open problems.

Petrophysical cutoff of net reservoir plays a very important role in reservoir characterization for the evaluation of hydrocarbons in place and the estimation of ultimate hydrocarbon recovery. There have been many approaches to quantify cutoffs, yet each of these approaches yields a different reservoir model with some amount of uncertainties due to lack of enough data, insufficiency of knowledge and the heterogeneous nature of petroleum reservoirs. Conventionally, net reservoirs cut-offs are evaluated by applying static petrophysical well-logs without consideration of dynamic performance, which results in a crisp classification of reservoir or non-reservoir zones. This paper takes Q oilfield in Albert Basin of Uganda as an example, provides a new structured quantitative approach which integrates all core, petrophysical interpretation, modular dynamics test data, reservoir fluid data and development wells pattern together to determine a reasonable net reservoir cutoffs. Three dependent variables including oil initially in place (OIIP), total oil production (FOPT) and total water production (FWPT) were selected to test the sensitivity with two independent variables, i.e. volume of clay (Vclay) and porosity. Then experiment design and response surface method were used in constructing the proxy models that are related to the dependent variable. After running 5000 realizations, probability density function (PDF) was utilized to locate P50 value on the cumulative probability curve. Finally, the cutoffs of Vclay and porosity were determined by the arithmetic mean of corresponding P50 value. The case study clearly illustrates how all available data from a reservoir should be integrated for appropriate determination of the net reservoir cutoffs.

One of the important elements of municipal solid waste management (MSWM) system is waste storage service. Residents deal with the system in this stage and the efficiency of waste collection element, the most expensive element of waste management system, relies on the performance of storage service. In this study, the performance of two different models including minimize facilities (MF) and maximize capacitated coverage (MCC) was investigated to find optimal locations for storage stations in Alandasht district located in Mashhad- Iran. Four effective factors including total service coverage, residential engagement, surplus container capacity devoted to each station and the ratio of the standard deviation to the arithmetic mean of solid waste allocated to each station were considered to compare these models. The MF model provided the highest service coverage by proposing 26 stations covering 98.56 percent of total residences. According to 26 stations proposed with MF model, MCC was run with 26, 27, 25 and 24 stations. MCC-27 provided the maximum attendance of residents with 54.47 percent. However, the most economical container distribution to the stations proposed with MCC-24 by presenting the minimum ratio of surplus devoted capacity to total demand, 33.74 percent. Finally, MCC-25 provided better distribution of residents to the storage stations, i.e., the minimum ratio of the standard deviation to the average solid waste devoted to stations, 22.13 percent. service area (SA) analysis applied to MF, MCC-25 and MCC-24 showed more than 60 percent of residences are located between 0 and 100 m walking distance for these analyses.

Polar polycyclic aromatic hydrocarbons (PAHs) derivatives like nitrated and oxygenated PAHs have higher toxic potentials than the parent one, and are receiving growing interests. In this study, we investigated household air pollution and personal exposure to nitro- and oxy-PAHs during a winter period in rural Shanxi, northern China. The overall arithmetic means of 24-h average indoor nitro-PAHs and oxy-PAHs were 10.2 ± 3.6 and 76.8 ± 51.8 ng/m3, respectively, that were much higher than the 7.98 ± 4.30 and 54.7 ± 45.4 ng/m3 in the outdoor air. Nearly 90% of particulate PAHs derivatives were enriched in fine PM2.5 and even finer PM1.0 fraction. Daily inhalation exposure to nitro- and oxy-PAHs for the rural population were 8.41 ± 3.08 and 68.5 ± 79.7 ng/m3, respectively. Residents burning briquette for cooking were found to have lower household air pollution and exposure levels compared with those burning wood. The calculated time-weighted average concentration overestimated, though correlated positively, the daily inhalation exposure compared to the that from personal carried samplers.