Developing an Embedded Model for Test suite prioritization process to optimize consistency rules for inconsistencies detection and model changes

Software form typically contains a lot of contradiction and uniformity checkers help engineers find them. Even if engineers are willing to tolerate inconsistencies, they are better off knowing about their existence to avoid follow-on errors and unnecessary rework. However, current approaches do not detect or track inconsistencies fast enough. This paper presents an automated approach for detecting and tracking inconsistencies in real time (while the model changes). Engineers only need to define consistency rules-in any language-and our approach automatically identifies how model changes affect these consistency rules. It does this by observing the behavior of consistency rules to understand how they affect the model. The approach is quick, correct, scalable, fully automated, and easy to use as it does not require any special skills from the engineers using it. We use this model to define generic prioritization criteria that are applicable to GUI, Web applications and Embedded Model. We evolve the model and use it to develop a unified theory. Within the context of this model, we develop and empirically evaluate several prioritization criteria and apply them to four stand-alone GUI and three Web-based applications, their existing test suites and mainly embedded systems. In this model we only run our data collection and test suite prioritization process on seven programs and their existing test suites. An experiment that would be more readily generalized would include multiple programs of different sizes and from different domains. We may conduct additional empirical studies with larger EDS to address this threat each test case has a uniform cost of running (processor time) monitoring (human time); these assumptions may not hold in practice. Second, we assume that each fault contributes uniformly to the overall cost, which again may not hold in practice

NEW INSIGHT INTO THE MIDDLE EOCENE CALCAREOUS NANNOPLANKTON BIOSTRATIGRAPHY AND PALEOENVIRONMENT FROM FAYOUM AND BENI SUEF AREAS, EGYPT

The present study deals with calcareous nannoplankton paleoenvironmental and biostratigraphic implications as well as the genesis and the stratigraphic significance of an event bed recognized from the middle Eocene Beni Suef Formation in the sections of Gebel Na’alun (Fayoum area) and Gebel Homret Shaibun (Beni Suef area), Egypt. Calcareous nannoplankton biostratigraphy indicates that the Beni Suef Formation in the two areas is synchronous, covering an interval that may be correlated with the calcareous nannoplankton Zone NP17. Paleoenvironmental implications from calcareous nannoplankton suggests deposition of sediments in the Beni Suef Formation under relatively stable, temperate and mesotrophic conditions, with a short interval of eutrophication in the basal part of the Homret Shaibun section

A record of spontaneous subduction initiation in the Izu–Bonin–Mariana arc

The initiation of tectonic plate subduction into the mantle is poorly understood. If subduction is induced by the push of a distant mid-ocean ridge or subducted slab pull, we expect compression and uplift of the overriding plate. In contrast, spontaneous subduction initiation, driven by subsidence of dense lithosphere along faults adjacent to buoyant lithosphere, would result in extension and magmatism. The rock record of subduction initiation is typically obscured by younger deposits, so evaluating these possibilities has proved elusive. Here we analyse the geochemical characteristics of igneous basement rocks and overlying sediments, sampled from the Amami Sankaku Basin in the northwest Philippine Sea. The uppermost basement rocks are areally widespread and supplied via dykes. They are similar in composition and age—as constrained by the biostratigraphy of the overlying sediments—to the 52–48-million-year-old basalts in the adjacent Izu–Bonin–Mariana fore-arc. The geochemical characteristics of the basement lavas indicate that a component of subducted lithosphere was involved in their genesis, and the lavas were derived from mantle source rocks that were more melt-depleted than those tapped at mid-ocean ridges. We propose that the basement lavas formed during the inception of Izu–Bonin–Mariana subduction in a mode consistent with the spontaneous initiation of subduction

Calibration of the depth invariant algorithm to monitor the tidal action of Rabigh City at the Red Sea Coast, Saudi Arabia

Rabigh is a thriving coastal city located at the eastern bank of the Red Sea, Saudi Arabia. The city has suffered from shoreline destruction because of the invasive tidal action powered principally by the wind speed and direction over shallow waters. This study was carried out to calibrate the water column depth in the vicinity of Rabigh. Optical and microwave remote sensing data from the European Space Agency were collected over 2 years (2017–2018) along with the analog daily monitoring of tidal data collected from the marine station of Rabigh. Depth invariant index (DII) was implemented utilizing the optical data, while the Wind Field Estimation algorithm was implemented utilizing the microwave data. The findings of the current research emphasis on the oscillation behavior of the depth invariant mean values and the mean astronomical tides resulted in R2 of 0.75 and 0.79, respectively. Robust linear regression was established between the astronomical tide and the mean values of the normalized DII (R2 = 0.81). The findings also indicated that January had the strongest wind speed solidly correlated with the depth invariant values (R2 = 0.92). Therefore, decision-makers can depend on remote sensing data as an efficient tool to monitor natural phenomena and also to regulate human activities in fragile ecosystems

Major Factors Controlling the Elemental Composition of Al-Kharrar Lagoon Bottom Sediments, Rabigh, Saudi Arabia

Bottom sediments of Al-Kharrar Lagoon, Rabigh area, Saudi Arabia were analyzed for mineralogical (26 samples) and major oxides, minor, and trace elements (46 samples). The prime objective is to document the controlling factors of the mineralogical and chemical composition of the lagoon bottom sediments. Hierarchical cluster (HCA) and the principal component (PCA) analyses are used to disclose the degree of similarities among elements to distinguish them into statistically significant groups. Results clarified the interplay of terrestrial sediment influx through the temporarily active Wadi Rabigh, hydrological regime and the autochthonous biogenic sedimentation, and to a lesser extent rare anthropogenic influence that impacted the lagoon sediments. The spatial distribution of minerals shows a southward increase in the siliciclastic-related minerals (quartz, clay minerals, k-feldspars, and plagioclase along with traces of amphiboles), whereas carbonate minerals (high Mg-calcite and aragonite) dominate the northern sector of the lagoon in areas far from the influence of detrital influx. The concentrations levels of oxides, minor, and trace elements display spatial variability. Three main distinctive elemental groups were delineated appraising the analysis of the elemental interrelationships and associated statistical analysis. The first group includes the positively correlated SiO2, TiO2, Al2O3, Fe2O3, MnO, MgO, K2O, Na2O, V, Cr, Ni, Zn, Rb, and Ba, which are concentrated in the southern sector of the lagoon. The second group is the carbonate-related elements (CaO and Sr) that dominate the northern sector. The distribution patterns of P2O5 and Cu varied highly across the lagoon. Enrichment factors revealed moderate levels of Cu in some sites supporting the anthropogenic source. The results showed the hospitable bottom ecological status of the lagoon despite local anthropogenic stressors such as an influx of flood water that contain a mixture of lithogenic and dissolved Cu from local farming

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

Depositional setting and cementation pattern of al-mejarma beachrocks, Saudi Arabia: A proxy for the late quaternary red sea coastal evolution

This study utilizes lithofacies characteristics, petrographic, XRD, and stable isotope data of Al-Mejarma beachrocks, Red Sea, Saudi Arabia, to interpret its depositional setting, origin of cement, and coastal evolution. The beachrock is 1.15 m thick, medium to very coarse-grained sandstone with scattered granules. It shows massive to graded bedding, horizontal, ripple, and shore parallel to slightly oblique planar cross-laminations, with a remarkable absence of bioturbation. It was deposited by shore-parallel longshore currents in a relatively high-energy beach environment. The framework comprises quartz, feldspars, and lithic fragments admixed with biogenic remains of algae, mollusca, foraminifera, corals, and echinoids. They are cemented by high magnesium calcite in the form of isopachous rims and pore-filling blades, and rarely, as a meniscus bridge. The mean values of δ18OVPDB and δ13CVPDB are 0.44‰ and 3.65‰, respectively, suggesting a seawater origin for the cement. The framework composition, facies geometry, and association with back-barrier lagoon impose a deposition as a shoreface-beach barrier through two stages corresponding to the middle and late Holocene. The first stage attests landward migrating sediment accumulation and rapid marine cementation. The sediments stored offshore during the early and middle Holocene humid periods migrated landward from offshore and alongshore by onshore waves and longshore drift during the middle and late Holocene sea-level highstand. They were cemented to form beachrock and subsequently emerged as the late Holocene sea-level fell

Identification of natural antiviral drug candidates against Tilapia Lake Virus: Computational drug design approaches.

Tilapia Lake Virus (TiLV) is a disease that affects tilapia fish, causing a high rate of sudden death at any stage in their life cycle. Unfortunately, there are currently no effective antiviral drugs or vaccines to prevent or control the progression of this disease. Researchers have discovered that the CRM1 protein plays a critical function in the development and spreading of animal viruses. By inhibiting CRM1, the virus's spread in commercial fish farms can be suppressed. With this in mind, this study intended to identify potential antiviral drugs from two different tropical mangrove plants from tropical regions: Heritiera fomes and Ceriops candolleana. To identify promising compounds that target the CRM1 protein, a computer-aided drug discovery approach is employed containing molecular docking, ADME (absorption, distribution, metabolism and excretion) analysis, toxicity assessment as well as molecular dynamics (MD) simulation. To estimate binding affinities of all phytochemicals, molecular docking is used and the top three candidate compounds with the highest docking scores were selected, which are CID107876 (-8.3 Kcal/mol), CID12795736 (-8.2 Kcal/mol), and CID12303662 (-7.9 Kcal/mol). We also evaluated the ADME and toxicity properties of these compounds. Finally, MD simulation was conducted to analyze the stability of the protein-ligand complex structures and confirm the suitability of these compounds. The computational study demonstrated that the phytochemicals found in H. fomes and C. candolleana could potentially serve as important inhibitors of TiLV, offering practical utility. However, further in vivo investigations are necessary to investigate and potentially confirm the effectiveness of these compounds as antiviral drugs against the virus TiLV