Faulting patterns in the Lower Yarmouk Gorge potentially influence groundwater flow paths

Recent studies investigating groundwater parameters, e.g., heads, chemical composition, and heat transfer, argued that groundwater flow paths in the Lower Yarmouk Gorge (LYG) area are controlled by geological features such as faults or dikes. However, the nature of such features, as well as their exact locations, were so far unknown. In the present paper, we propose a new fault pattern in the LYG area by compiling and revising geological and geophysical data from the study area, including borehole information, geological map cross sections, and seismic data from the southern Golan Heights and northern Ajloun mountains. The presented pattern is composed of strike–slip and thrust faults, which are associated with the Dead Sea transform system and with the Kinnarot pull-apart basin. Compressional and tensional structures developed in different places, forming a series of fault blocks probably causing a non-uniform spatial hydraulic connection between them. This study provides a coarse fault-block model and improved structural constraints that serve as fundamental input for future hydrogeological modeling which is a suggested solution for an enigmatic hydrological situation concerning three riparian states (Syria, Jordan, and Israel) in a water-scarce region. In areas of water scarcity and transboundary water resources, transient 3-D flow simulations of the resource are the most appropriate solution to understand reservoir behavior. This is an important tool for the development of management strategies. However, those models must be based on realistic geometry, including structural features. The study at the LYG is intended to show the importance of such kinds of structural investigations for providing the necessary database in geologically stressed areas without sufficient data. Furthermore, during the hydrogeological investigation, a mismatch with results of pull-apart basin rim fault evolution studies was discovered. We argue that this mismatch may result from the settings at the eastern rim of the basin as the en-echelon changes from pull-apart basins (Dead Sea, Kinnarot, Hula) to a push-up ridge (Hermon)

Transient simulations of large-scale hydrogeological processes causing temperature and salinity anomalies in the Tiberias Basin

Hot and salty waters occur in the surroundings of the Lake Tiberias. Transient numerical simulations of thermally-driven flow without salinity effects show that mixed convection can explain the upsurge of thermal waters through permeable faults and the high temperature gradient in the Lower Yarmouk Gorge (LYG). It turns out that by including salinity effects, the flow patterns differ from those of a purely thermal regime because heavy brines dampen upward buoyant flow and convective cells. Accordingly, the fault permeability had to be increased to restore a good fit with the measured temperatures. This further supports the hypothesis that the high temperature gradient in the LYG is likely due to fractures or faults in that area. The thermohaline simulations also suggest that the derivatives of relic seawater brines are the major source of salinity. Deep brines leaching salt diapirs cannot reach the surface. However, the presence of local shallower salt bodies below the lake can potentially contribute to the salinity of the western spring and well waters, though in very small amount. This is in agreement with geochemical data according to which the major source of the brines of the Tiberias Basin represents seawater evaporation brines. Besides being of importance for understanding the hydrogeological processes that salinize Lake Tiberias, the presented simulations provide a real-case example illustrating large-scale fluid patterns due to only one source of buoyancy (heat) and those that are additionally coupled to salinity

Sources of Salinization of Groundwater in the Lower Yarmouk Gorge, East of the River Jordan

In the Lower Yarmouk Gorge the chemical composition of regional, fresh to brackish, mostly thermal groundwater reveals a zonation in respect to salinization and geochemical evolution, which is seemingly controlled by the Lower Yarmouk fault (LYF) but does not strictly follow the morphological Yarmouk Gorge. South of LYF, the artesian Mukeihbeh well field region produces in its central segment groundwaters, an almost pure basaltic-rock type with a low contribution (<0.3 vol-%) of Tertiary brine, hosted in deep Cretaceous and Jurassic formations. Further distal, the contribution of limestone water increases, originating from the Ajloun Mountains in the South. North of the LYF, the Mezar wells, the springs of Hammat Gader and Ain Himma produce dominantly limestone water, which contains 0.14-3 vol-% of the Tertiary brine, and hence possesses variable salinity. The total dissolved equivalents, TDE, of solutes gained by water/rock interaction (WRI) and mixing with brine, TDEWRI+brine, amount to 10-70% of total salinity in the region comprising the Mukheibeh field, Ain Himma and Mezar 3 well; 55-70% in the springs of Hammat Gader; and 80-90% in wells Mezar 1 and 2. The type of salinization indicates that the Lower Yarmouk fault seemingly acts as the divide between the Ajloun and the Golan Heights-dominated groundwaters

Essentially biased: why people are fatalistic about genes

We propose that people are genetic essentialists—that is, they tend to think of genetic attributions as being immutable, of a specific etiology, natural, and dividing people into homogenous and discrete groups. Although there are rare conditions where genes operate in these kinds of deterministic ways, people overgeneralize from these to the far more common conditions where genes are not at all deterministic. These essentialist biases are associated with some harmful outcomes such as racism, sexism, pessimism in the face of illnesses, political polarization, and support for eugenics, while at the same time they are linked with increased tolerance and sympathy for gay rights, mental illness, and less severe judgments of responsibility for crime. We will also discuss how these essentialist biases connect with the burgeoning direct-to-consumer genomics industry and various kinds of genetic engineering. Overall, these biases appear rather resistant to efforts to reduce them, although genetics literacy predicts weaker essentialist tendencies

Using Support Vector Machine (SVM) with GPS Ionospheric TEC Estimations to Potentially Predict Earthquake Events

There are significant controversies surrounding the detection of precursors that may precede earthquakes. Natural hazard signatures associated with strong earthquakes can appear in the lithosphere, troposphere, and ionosphere, where current remote sensing technologies have become valuable tools for detecting and measuring early warning signals of stress build-up deep in the Earth’s crust (presumably associated with earthquake events). Here, we propose implementing a machine learning support vector machine (SVM) technique, applied with GPS ionospheric total electron content (TEC) pre-processed time series estimations, to evaluate potential precursors caused by earthquakes and manifested as disturbances in the TEC data. After filtering and screening our data for solar or geomagnetic influences at different time scales, our results indicate that for large earthquakes (>Mw 6), true negative predictions can be achieved with 85.7% accuracy, and true positive predictions with an accuracy of 80%. We tested our method with different skill scores, such as accuracy (0.83), precision (0.85), recall (0.8), the Heidke skill score (0.66), and true skill statistics (0.66)

Using Support Vector Machine (SVM) with GPS Ionospheric TEC Estimations to Potentially Predict Earthquake Events

There are significant controversies surrounding the detection of precursors that may precede earthquakes. Natural hazard signatures associated with strong earthquakes can appear in the lithosphere, troposphere, and ionosphere, where current remote sensing technologies have become valuable tools for detecting and measuring early warning signals of stress build-up deep in the Earth&rsquo;s crust (presumably associated with earthquake events). Here, we propose implementing a machine learning support vector machine (SVM) technique, applied with GPS ionospheric total electron content (TEC) pre-processed time series estimations, to evaluate potential precursors caused by earthquakes and manifested as disturbances in the TEC data. After filtering and screening our data for solar or geomagnetic influences at different time scales, our results indicate that for large earthquakes (&gt;Mw 6), true negative predictions can be achieved with 85.7% accuracy, and true positive predictions with an accuracy of 80%. We tested our method with different skill scores, such as accuracy (0.83), precision (0.85), recall (0.8), the Heidke skill score (0.66), and true skill statistics (0.66)

Ecogeographic Conditions Dramatically Affect <i>Trans</i>-Resveratrol and Other Major Phenolics’ Levels in Wine at a Semi-Arid Area

Grapevines are susceptible and responsive to their surrounding environment. Factors such as climate region and terroir are known to affect polyphenolic compounds in wine and therefore, its quality. The uniqueness of the terroir in Israel is the variety of soil types and the climatic conditions, ranging from Mediterranean to arid climates. Thus, understanding the effects of climate on grapevine performance in Israel may be a test case for the effect of climate change on grapevine at other areas in the future. First, we present a preliminary survey (2012–2014) in different climate zones and terroirs, which showed that trans-resveratrol concentrations in Merlot and Shiraz were high, while those of Cabernet Sauvignon were significantly lower. A further comprehensive countrywide survey (2016) of Merlot wines from 62 vineyards (53 wineries) compared several phenolic compounds’ concentrations between five areas of different climate and terroir. Results show a connection between trans-resveratrol concentrations, variety, and terroir properties. Furthermore, we show that trans-resveratrol concentrations are strongly correlated to humidity levels at springtime, precipitation, and soil permeability. This work can be considered a glimpse into the possible alterations of wine composition in currently moderate-climate wine-growing areas

Ancient trash mounds unravel urban collapse a century before the end of Byzantine hegemony in the southern Levant.

The historic event of the Late Antique Little Ice Age (LALIA) was recently identified in dozens of natural and geological climate proxies of the northern hemisphere. Although this climatic downturn was proposed as a major cause for pandemic and extensive societal upheavals in the sixth-seventh centuries CE, archaeological evidence for the magnitude of societal response to this event is sparse. This study uses ancient trash mounds as a type of proxy for identifying societal crisis in the urban domain, and employs multidisciplinary investigations to establish the terminal date of organized trash collection and high-level municipal functioning on a city-wide scale. Survey, excavation, sediment analysis, and geographic information system assessment of mound volume were conducted on a series of mounds surrounding the Byzantine urban settlement of Elusa in the Negev Desert. These reveal the massive collection and dumping of domestic and construction waste over time on the city edges. Carbon dating of charred seeds and charcoal fragments combined with ceramic analysis establish the end date of orchestrated trash removal near the mid-sixth century, coinciding closely with the beginning of the LALIA event and outbreak of the Justinian Plague in the year 541. This evidence for societal decline during the sixth century ties with other arguments for urban dysfunction across the Byzantine Levant at this time. We demonstrate the utility of trash mounds as sensitive proxies of social response and unravel the time-space dynamics of urban collapse, suggesting diminished resilience to rapid climate change in the frontier Negev region of the empire

Mean Platelet Volume as a Predictor of Coronary Artery Disease Severity and its Association With Coronary Artery Calcification

Coronary calcium score (CCS) is a highly sensitive marker for estimating coronary artery calcification (CAC) and detecting coronary artery disease (CAD). Mean platelet volume (MPV (is a platelet indicator that represent platelet stimulation and production. The aim of the current study was to examine the association between MPV values and CAC. We examined 290 patients who underwent coronary computerized tomography (CT) exam between the years 2017 and 2020 in a tertiary care medical center. Only patients evaluated for chest pain were included. The Multi-Ethnic Study of Atherosclerosis (MESA) CAC calculator was used to categorize patients CCS by age, gender, and ethnicity to CAC severity percentiles (<50, 50-74, 75-89, ≥90). Thereafter, the association between CAC percentile and MPV on admission was evaluated. Out of 290 patients, 251 (87%) met the inclusion and exclusion criteria. There was a strong association between higher MPV and higher CAC percentile ( P  = .009). The 90th CAC percentile was associated with the highest prevalence of diabetes mellitus (DM), hypertension, dyslipidemia, and statin therapy ( P  = .002, .003, .001, and .001, respectively). In a multivariate analysis (including age, gender, DM, hypertension, statin therapy, and low-density lipoprotein level) MPV was found to be an independent predictor of CAC percentile (OR 1.55-2.65, P  < .001). Higher MPV was found to be an independent predictor for CAC severity. These findings could further help clinicians detect patients at risk for CAD using a simple and routine blood test