A bibliometric-based evaluation on environmental research in the Arab world

The Arab world’s environment is among the most vulnerable and harsh ones across the globe. This entails much efforts to mitigate the potential environmental risks. Analysing contributions of Arab scholars in environmental research in terms of quantity and quality can bring up insights on their endeavours in this regard. Bibliometric techniques are proposed to conduct such this analysis over publications originated from Arab world in a leading environmental journal “Science of the Total Environment”. Research productivity is being used as quantitative indicator, while citation rates and Hirsch index (h-index) are being used as qualitative indicators. The research outputs were compared with those obtained from non-Arab Middle Eastern countries (Iran, Turkey and Israel). Worldwide research productivity was 17,258 documents, while that from Arab countries, Iran, Turkey and Israel were 215, 34, 83 and 87 documents, respectively. The h-index of Arab world research was 31, and total citations were 3616 with an average of 16.8. The highest share of publications was recorded by Saudi Arabia (53 documents; 24.7%). Egypt and Saudi Arabia had highest h-index with 15 for each one. American University of Beirut in Lebanon was the highest productive institution (16; 7.4%). The most collaborated country with Arab world was France (29; 13.5%). In the conclusion, the study reveals a clear gap in terms of research productivity between Arab countries and other Middle Eastern countries, precisely Israel and Turkey. More research efforts through optimizing investments in environmental research, developing regional experiences and fostering international collaboration are required to eliminate these lags.     

The probability distributions and fractal dimension of sunspot cycles associated with ENSO phenomena

Various methods have been used to secure the certainty of significant relations among the sunspot cycles and some of the terrestrial climate parameters such as temperature, rainfall, and ENSO. This study investigates the behavior of ENSO cycles and mean monthly sunspot cycles. Sunspot cycles range from 1755 to 2016 whereas, ENSO cycles range from 1866 to 2012. In this regard, the appropriateness of distributions is investigated with the help of Kolmogorov-Smirnov D, Anderson-Darling, and chi-square tests. It is found that most of the sunspot cycle follows generalized Pareto distribution whereas, generalized extreme value distribution was found appropriate for ENSO cycles. Probability distribution is used to analyze the behavior of each sunspot cycle and ENSO cycle separately. Probability distribution indicates the tail behavior of each cycle; tail explored correlation cycles. Furthermore, self-similar and self-affine fractal dimension methods are used to compute Hurst exponents to determine the persistency of the available data. Fractal dimension has an ability to study the complexity involved in sunspot and ENSO cycles. The fractal dimension and Hurst exponent describe persistency (smoothness) and complexity of data. Hurst exponent measures long-term behavior of time series, making it more helpful for forecasting. This is the measure of regularity or irregularity (chaos) of the time function in the form of their persistency or anti-persistency, respectively. Hurst exponents are computed using rescaled range analysis method and box counting methods. Both these methods are suitable for long-term forecasting. The results of this study confirm that during the period 1980–2000, ENSO cycles were very active. Simultaneously, ENSO was active for the periods 1982–1983, 1986–1987, 1991–1993, 1994–1995, and 1997–1998; these periods include two strongest periods of the century viz., 1982–1983 and 1997–1998. Sunspot cycles and ENSO cycles both were found to be persistent. Self-similar fractal dimensions exhibited a better persistency and a better correlation as compared to self-affine fractal dimension. This research is a part of a larger research project investigating the correlation of sunspot cycles and ENSO cycles, and the influence of ENSO cycles on variations of the local climatic parameters which in turn depends on solar activity changes.     

Suitability of AuRM2 as a Reference Material for Trace Element Microanalysis of Native Gold

Microanalysis of native gold specimens has been hampered by the lack of a suitable reference material (RM) known to be sufficiently homogeneous at the scale of microanalytical sampling. The suitability of gold reference material AuRM2 for microanalysis was assessed. This RM was created for bulk analysis of refined gold and was only certified for homogeneity at the bulk scale. However, it contains trace elements in appropriate mass fraction ranges for analysis of native gold. This study was not intended to provide alternative mass fractions from the original certified values, only to assess its suitability for microanalytical methods. Micro‐scale (~ 3.4 μg sample mass) heterogeneity was calculated from measurement repeatability of LA‐ICP‐MS analyses of AuRM2 by factoring in signal (represented by counting statistics) and instrument set‐up‐specific variability (determined using measurement variability of a reference material known to be homogeneous). Elements determined to be homogeneous or to have minor heterogeneity (< 10% calculated heterogeneity RSD) are Mg, Al, Ti, Fe, Ni, Cu, Zn, Se, Rh, Sn, Sb, Pt and Pb. Elements with moderate heterogeneity (10–20% heterogeneity RSD) are: Mn, As, Pd, Te and Bi. Correlation of element mass fractions indicates that micro‐scale inclusions of chalcophile‐rich phases along grain boundaries may be responsible for some of the chemical heterogeneity. However, the level of heterogeneity is statistically negligible compared with the ranges of chemical signatures observed in sample populations of native gold. Therefore, AuRM2 is shown to be sufficiently homogenous at a micro‐scale for use as a RM for microanalysis of native gold.