Research of the origin of a particular Tunisian group using a physical marker and Alu insertion polymorphisms

The aim of this study was to show how, in some particular circumstances, a physical marker can be used along with molecular markers in the research of an ancient people movement. A set of five Alu insertions was analysed in 42 subjects from a particular Tunisian group (El Hamma) that has, unlike most of the Tunisian population, a very dark skin, similar to that of sub-Saharans, and in 114 Tunisian subjects (Gabes sample) from the same governorate, but outside the group. Our results showed that the El Hamma group is genetically midway between sub-Saharan populations and North Africans, whereas the Gabes sample is clustered among North Africans. In addition, The A25 Alu insertion, considered characteristic to sub-Saharan Africans, was present in the El Hamma group at a relatively high frequency. This frequency was similar to that found in sub-Saharans from Nigeria, but significantly different from those found in the Gabes sample and in other North African populations. Our molecular results, consistent with the skin color status, suggest a sub-Saharan origin of this particular Tunisian group

Genetic differentiation of Yemeni people according to rhesus and Gm polymorphisms

For introducing Yemeni population in synthesis of genetic relationships of human populations, analysis of rhesus and Gm polymorphisms have been carried out for a population sample of 210 Yemenites. Rhesus haplotype frequencies were compared to those estimated in an original sample of 171 Tunisians and to available data for other populations. Gm haplotype frequencies were introduced in a wide synthesis of genetic relationships for 67 populations from Africa, Europe, the Near East and India. The genetic profile of Yemeni people would be close to that of a highly diversified ancestral population. The first inhabitants of North Africa, the Berbers and Yemenites have very likely a common origin and were not subject to important genetic drift after their geographic differentiation. While, the divergence between Yemenites and their neighbours of sub-Saharan Africa would have occurred with a founder effect and a long isolation. An important parallelism is observed for the Gm system between genetic and linguistic differentiations

Monitoring of mangrove forests vegetation based on optical versus microwave data: A case study western coast of Saudi Arabia

Normalized difference vegetation index (NDVI) is one of the parameters of vegetation that can be studied by remote sensing of land surface with Sentinel-2 (S-2) satellite image. The NDVI is a nondimensional index that depicts the difference in plant cover reflectivity between visible and near-infrared light and can be used to measure the density of green on a piece of land. On the other hand, the dual-pol radar vegetation index (DpRVI) is one of the indices studied using multispectral synthetic aperture radar (SAR) images. Researchers have identified that SAR images are highly sensitive to identify the buildup of biomass from leaf vegetative growth to the flowering stage. Vegetation biophysical characteristics such as the leaf area index (LAI), vegetation water content, and biomass are frequently used as essential system parameters in remote sensing data assimilation for agricultural production models. In the current study, we have used LAI as a system parameter. The findings of the study revealed that the optical data (NDVI) showed a high correlation (up to 0.712) with LAI and a low root-mean-square error (0.0296) compared to microwave data with 0.4523 root-mean-square error. The NDVI, LAI, and DpRVI mean values all decreased between 2019 and 2020. While the DpRVI continued to decline between 2020 and 2021, the NDVI and LAI saw an increase over the same period, which was likely caused by an increase in the study area’s average annual rainfall and the cautious stance of the Red Global (RSG) project on sustainability

Sulfur Speciation of Crude Oils by Partial Least Squares Regression Modeling of Their Infrared Spectra

Research has been carried out to determine the feasibility of partial least-squares regression (PLS) modeling of infrared (IR) spectra of crude oils as a tool for fast sulfur speciation. The study is a continuation of a previously developed method to predict long and short residue properties of crude oils from IR and near-infrared (NIR) spectra. Retention data of two-dimensional gas chromatography (GC GC) of 47 crude oil samples have been used as input for modeling the corresponding IR spectra. A total of 10 different PLS prediction models have been built: 1 for the total sulfur content and 9 for the sulfur compound classes (1) sulfides, thiols, disulfides, and thiophenes, (2) aryl-sulfides, (3) benzothiophenes, (4) naphthenic-benzothiophenes, (5) dibenzothiophenes, (6) naphthenic-dibenzothiophenes, (7) benzonaphthothiophenes, (8) naphthenic-benzo-naphthothiophenes, and (9) dinaphthothiophenes. Research was carried out on a set of 47 IR spectra of which 28 were selected for calibration by means of a principal component analysis. The remaining 19 spectra were used as a test set to validate the PLS regression models. The results confirm the conclusion from previous studies that PLS modeling of IR spectra to predict the total sulfur concentration of a crude oil is a valuable alternative for the commonly applied physicochemical ASTM method D2622. Besides, the concentration of dibenzothiophenes and three different benzothiophene classes can be predicted with reasonable accuracy. The corresponding models offer a valuable tool for quick on-site screening on these compounds, which are potentially harmful for production plants. The models for the remaining sulfur compound classes are insufficiently accurate to be used as a method for detailed sulfur speciation of crude oils

Irrigation system performance in relation with groundwater assessment from collective to catchment scale

The performance of on demand irrigation system located in Merguellil Valley (Tunisia) have been analysed from both agronomic and engineering point of view. A full set of mitigation options, including technical alternatives and management strategies have been formulated examined and evaluated through a stockholder driven participatory approach that embraces both water managers, farmers and researchers