Topography Roughness Research Articles

Effect of oral irrigation device and its solution type on the surface roughness and topography of Bulk-fill composite resins.

BackgroundSurface roughness and topography of composite resin materials have a significant role in biofilm aggregation, periodontitis, and recurrent caries. The present study evaluated the effect of the Waterpik oral irrigation device (OID) with different solution [water/ chlorhexidine (CHX)] on the surface roughness and topography of microhybrid (x-tra fil) and nanohybrid (Tetric N-Ceram Bulk) bulk-fill composite resins. Material and MethodsDisk-shaped samples were prepared from each composite resin, measuring 5 mm in diameter and 3 mm in height, and assigned to three groups in terms of treatment (n=19): group A, control (storage in distilled water); group B, OID with water; group C, OID with 0.5% CHX. The samples were treated for eight weeks, simulating one-year use of OID. Profilometry and scanning electron microscopy (SEM) were used to evaluate and compare quantitatively surface roughness (Ra) and qualitative topography of composite resin surfaces before and after treatment. The data were analyzed with paired-samples, Wilcoxon, and generalized estimating equations tests (α=0.05). ResultsThe application of OID increased the Ra of composite resin compared to the control group (P<0.001). No significant difference was detected between the two solutions (water and CHX) (P=0.615). The effect of composite resin type and the cumulative effect of composite resin type and OID solution were not significant on the surface roughness changes of the samples (P=0.243 and P=0.464, respectively). ConclusionsOID with water and CHX solutions increased the surface roughness and topographic changes of microhybrid and nanohybrid bulk-fill composite resins. Key words:Composite resins, irrigation, mouthrinse, surface roughness, topography.

Morphological, structural, and optical properties of flexible Tin Oxide(II) thin film via thermal evaporation technique

Tin oxide compounds have been highly studied due to their important properties. Tin Oxide (II) SnO compound is considered an ideal p-type conductive material, with large p-type carrier mobility. It is getting a lot of attention in next-generation electronic applications. In this work, the SnO thin film was deposited on the polyethylene terephthalate (PET) substrate by the thermal evaporation method. The X-ray diffraction pattern revealed the amorphous structure of the SnO/PET thin film. The purity of the SnO/PET film was confirmed using the Raman spectrum. An atomic force microscope was carried out to investigate the topography (roughness and particle size) of the obtained SnO thin film. The optical band gap E_{{text{g}}}^{{{text{Opt}}}} for SnO/PET thin film in the absorption region was estimated using Tauc’s equation. The refractive index for the SnO/PET thin film was estimated at the normal dispersion range by a single oscillator model. The dielectric optical properties of the SnO/PET thin film were estimated. The calculated third-order nonlinear susceptibility χ(3) and nonlinear refractive index n(2) were in the order of ~ 10−10 and ~ 10−9esu, respectively, within the photon energy range (0.5 to 4 eV). The Sheik–Bahae model was used to determine the nonlinear absorption coefficient βc for SnO/PET thin film. Based on these detailed results, the high nonlinear optical parameters pave the way for the probability of using the SnO/PET in flexible optoelectronics devices.Graphical abstract

Implementation of Remote Sensing and GIS Techniques to Study the Flash Flood Risk at NEOM Mega-City, Saudi Arabia

Southern Red Sea flooding is common. Assessing flood-prone development risks helps decrease life and property threats. It tries to improve flood awareness and advocate property owner steps to lessen risk. DEMs and topography data were analyzed by RS and GIS. Fifth-through seventh-order rivers were studied. Morphometric analysis assessed the area’s flash flood danger. NEOM has 14 catchments. We determined each catchment’s area, perimeter, maximum length, total stream length, minimum and maximum elevations. It also uses remote sensing. It classifies Landsat 8 photos for land use and cover maps. Image categorization involves high-quality Landsat satellite images and secondary data, plus user experience and knowledge. This study used the wetness index, elevation, slope, stream power index, topographic roughness index, normalized difference vegetation index, sediment transport index, stream order, flow accumulation, and geological formation. Analytic hierarchy considered all earlier criteria (AHP). The geometric consistency index GCI (0.15) and the consistency ratio CR (4.3%) are calculated. The study showed five degrees of flooding risk for Wadi Zawhi and four for Wadi Surr, from very high to very low. 9.16% of Wadi Surr is vulnerable to very high flooding, 50% to high flooding, 40% to low flooding, and 0.3% to very low flooding. Wadi Zawhi’s flood risk is 0.23% high, moderate, low, or extremely low. They’re in Wadi Surr and Wadi Zawhi. Flood mapping helps prepare for emergencies. Flood-prone areas should prioritize resilience.

Using Remote Sensing and Machine Learning to Locate Groundwater Discharge to Salmon-Bearing Streams

We hypothesized topographic features alone could be used to locate groundwater discharge, but only where diagnostic topographic signatures could first be identified through the use of limited field observations and geologic data. We built a geodatabase from geologic and topographic data, with the geologic data only covering ~40% of the study area and topographic data derived from airborne LiDAR covering the entire study area. We identified two types of groundwater discharge: shallow hillslope groundwater discharge, commonly manifested as diffuse seeps, and aquifer-outcrop groundwater discharge, commonly manifested as springs. We developed multistep manual procedures that allowed us to accurately predict the locations of both types of groundwater discharge in 93% of cases, though only where geologic data were available. However, field verification suggested that both types of groundwater discharge could be identified by specific combinations of topographic variables alone. We then applied maximum entropy modeling, a machine learning technique, to predict the prevalence of both types of groundwater discharge using six topographic variables: profile curvature range, with a permutation importance of 43.2%, followed by distance to flowlines, elevation, topographic roughness index, flow-weighted slope, and planform curvature, with permutation importance of 20.8%, 18.5%, 15.2%, 1.8%, and 0.5%, respectively. The AUC values for the model were 0.95 for training data and 0.91 for testing data, indicating outstanding model performance.

Grinding performance oriented experimental evaluation on TiC-Steel cermet with vitrified bond cBN wheel

TiC-Steel cermet is widely used in aerospace and mining machinery owing to its excellent performance. However, the high wear resistance and the heterogeneity make its machining a challenging task. To investigate the grinding performance of TiC-Steel cermet, vitrified bond cBN wheel was customized to conduct dry grinding experiments. Grinding force was measured using a Kistler dynamometer; surface topography and 3D surface roughness parameters were measured by laser microscopy and scanning electron microscopy. Results indicate that plastic removal of steel phase, brittle fracture of ceramic phase, ceramic phase wear, ceramic phase debonding and microcracks are main removal modes of TiC-Steel cermet. 3D surface roughness parameters S a , S q , and S z consistently increase with increasing grinding depths from 25 μm to 125 μm and decrease with increasing spindle rotation speed. Effect of feed rate on the 3D surface roughness parameters is less than that of the grinding depth. The trend of the grinding force and surface topography is similar to that of 3D surface roughness parameters. Hence, the optimal processing parameters ( v w = 1–2 m/min, a p = 25 μm, n s = 5130 rpm) were used to obtain the best surface quality and the lowest grinding force (the minimum F N and F T of 9.2 N and 3.5 N, respectively). This study is devoted to broaden the research on the machinability of carbide-based cermets and promote utilization rate of cermets in industry.

Flood susceptibility mapping using extremely randomized trees for Assam 2020 floods

The year 2020 proved disastrous for the north eastern state of India, Assam. The state witnessed terrible floods in the midst of the pandemic. The current study aims to better understand the role played by various factors that contributed to the deluge. To this end, the current study undertakes a flood susceptibility mapping using a seldom employed decision tree based ensemble machine learning technique of extremely randomized trees (ERT). The model was trained and tested on a flood inventory superimposed with 14 flood influencing factors, namely slope, elevation, aspect, normalized difference vegetation index (NDVI), topographic wetness index (TWI), slope length, land use, geology, soil type, topographic roughness index (TRI), rainfall, distance from rivers, plan and profile curvature. The model was compared against other mapping techniques and produced an area under the receiver operating characteristic curve (AUC) of 0.901 outperforming others. The generated susceptibility map deduced the presence of low elevation, high rainfall and close proximity to rivers as major factors leading up to the disaster. It prophesizes a very high flood risk for approximately 18.32% of the study area concentrated in the northern and western part of the study region.

Surface Integrity and Friction Performance of Brass H62 Textured by One-Dimensional Ultrasonic Vibration-Assisted Turning.

The processing method, one-dimensional ultrasonic vibration-assisted turning (1D UVAT), is a potential and efficient way for fabricating a micro-textured surface. This paper aims at exploring the surface integrity and friction performance of brass H62 textured by the 1D UVAT. Four micro-textured surfaces with a specific distribution, size, and shape of dimples were fabricated by optimizing processing parameters, and the corresponding surface topography, subsurface microstructure, and surface roughness were observed and analyzed. A series of friction tests were carried out under oil-lubricating conditions to research the friction performance of micro-textured surfaces. The results show that the reason for the deviation between theoretical and experimental values of dimple depth was further revealed by observing the corresponding subsurface microstructure. The surface roughness of the micro-textured surfaces prepared is related to the number of micro-dimples per unit area and dimple size, which is greater than the surface generated by conventional turning. Compared with the polished surface and micro-grooved surface, the micro-textured surfaces have better friction performance with a lower frictional coefficient (COF) and wear degree. For the micro-textured surface fabricated by 1D UVAT, the number of micro-dimples per unit area has a great effect on the friction performance, and choosing a larger number is more conducive to improving the friction performance under the oil-lubricating condition. Consequently, this study proves that the proposed 1D UVAT can be a feasible candidate for preparing a micro-textured surface with better tribological property.

Artificial intelligence approaches for spatial prediction of landslides in mountainous regions of western India

The prediction of landslide is a complex task but preparing the landslide susceptibility map through artificial intelligence approaches can reduce life loss and damages resulting from landslides. The purpose of this study is to evaluate and compare the landslide susceptibility mapping (LSM) using six machine learning models, including random forest (RF), deep boost (DB), stochastic gradient boosting (SGB), rotation forest (RoF), boosted regression tree (BRT), and logit boost (LB) in the mountainous regions of western India. The landslide inventory map consisting of 184 landslide locations has been divided into two groups for training (70% data set) and validation (30% data set) purposes. Fourteen landslide triggering factors including slope, topographical roughness index, road density, topographical wetness index, elevation, slope length, drainage density, stream power index, geomorphology, rainfall, soil, lithology, lineament density, and normalized difference vegetation index have been considered using the boruta approach for the LSM. The results reveal that the RF model has the highest precision in terms of area under curve (0.88; 0.89), kappa (0.62; 0.50), accuracy (0.81; 0.77), and specificity (0.86; 0.86) both in the study region and secondary region, respectively. Hence, it can be concluded that the RF is an effective and promising technique as compared to DB, SGB, RoF, BRT, and LB for landslide susceptibility assessment in the research area as well as in regions having similar geo-environmental configuration.

Impact of Upward Oxygen Diffusion From the Oceanic Crust on the Magnetostratigraphy and Iron Biomineralization of East Pacific Ridge-Flank Sediments

Recent measurements of pore-water oxygen profiles in ridge flank sediments of the East Pacific Rise revealed an upward-directed diffusive oxygen flux from the hydrothermally active crust into the overlying sediment. This double-sided oxygenation from above and below results in a dual redox transition from an oxic sedimentary environment near the seabed through suboxic conditions at sediment mid-depth back to oxic conditions in the deeper basal sediment. The potential impact of this redox reversal on the paleo- and rock magnetic record was analyzed for three sediment cores from the Clarion-Clipperton-Zone (low-latitude eastern North Pacific). We found that the upward-directed crustal oxygen flux does not impede high quality reversal-based and relative paleointensity-refined magnetostratigraphic dating. Despite low and variable sedimentation rates of 0.1–0.8 cm/kyr, robust magnetostratigraphic core chronologies comprising the past 3.4 resp. 5.2 million years could be established. These age-models support previous findings of significant local sedimentation rate variations that are probably related to the bottom current interactions with the topographic roughness of the young ridge flanks. However, we observed some obvious paleomagnetic irregularities localized at the lower oxic/suboxic redox boundaries of the investigated sediments. When analyzing these apparently remagnetized sections in detail, we found no evidence of physical disturbance or chemical alteration. A sharp increase in single-domain magnetite concentration just below the present lower oxic/suboxic redox boundary suggests secondary magnetite biomineralization by microaerophilic magnetotactic bacteria living as a separate community in the lower, upward oxygenated part of the sediment column. We therefore postulate a two-phased post-depositional remanent magnetization of ridge flank sediments, first by a shallow and later by a deep-living community of magnetotactic bacteria. These findings are the first evidence of a second, deep population of probably inversely oriented magnetotactic bacteria residing in the inverse oxygen gradient zone of ridge flank sediments.

Enhancement of machinability and surface quality of Ti-6Al-4V by longitudinal ultrasonic vibration-assisted milling under dry conditions

Longitudinal ultrasonic vibration-assisted milling (LUVAM) was performed to improve the machinability and surface quality of titanium alloys Ti-6Al-4V under dry conditions. Effects of ultrasonic amplitude on the three-component cutting forces, cutting temperature, surface topography and 3D surface roughness (Sa and Sq) were investigated. The results show that, the cutting forces in both longitudinal and feed directions decrease with the increasing amplitude from 0 to 6 µm, as well as the average and maximum cutting temperature. Accordingly, the surface topography of Ti-6Al-4V becomes more uniform when ultrasonic amplitude reaches to 6 µm. Sa and Sq decrease by 35.1% and 34.0%, respectively, when the ultrasonic amplitude increases from 0 to 6 µm. The machinability and surface quality of Ti-6Al-4V are improved via this dry LUVAM, duo to the thermal-mechanical coupling resulted from large-amplitude ultrasonic vibration. The established approaches have potential applications in dry or near dry cutting of difficult-to-machine alloys with LUVAM.

Topographic Roughness on Forested Hillslopes: A Theoretical Approach for Quantifying Hillslope Sediment Flux From Tree Throw

AbstractWind‐driven tree throw is an observable and consequential process that suddenly moves soil downslope, inverts the soil column, and roughens the surface with pit‐mound topography. Quantifying fluxes due to tree throw is complicated by its stochastic nature and estimation requires averaging over a large area or long time. Here, we develop a theory that leads to a dimensionless metric directly measurable from high resolution topographic data. The theory explains the flux and topographic roughness as a function of tree throw production and decay rate by creep‐like processes. We then form a measurable dimensionless variable that is the ratio of fluxes due to tree throw versus creep‐like processes. Applying the theory to hillslopes in Southern Indiana, we find that tree throw accounts for 11%–18% of the hillslope sediment flux. The theoretical and observational findings provide important constraints on quantifying Critical Zone function from topographic parameters such as roughness.

The effects of controlled nanotopography, machined topography and their combination on molecular activities, bone formation and biomechanical stability during osseointegration

The initial cellular and molecular activities at the bone interface of implants with controlled nanoscale topography and microscale roughness have previously been reported. However, the effects of such surface modifications on the development of osseointegration have not yet been determined. This study investigated the molecular events and the histological and biomechanical development of the bone interface in implants with nanoscale topography, microscale roughness or a combination of both. Polished and machined titanium implants with and without controlled nanopatterning (75 nm protrusions) were produced using colloidal lithography and coated with a thin titanium layer to unify the chemistry. The implants were inserted in rat tibiae and subjected to removal torque (RTQ) measurements, molecular analyses and histological analyses after 6, 21 and 28 days. The results showed that nanotopography superimposed on microrough, machined, surfaces promoted an early increase in RTQ and hence produced greater implant stability at 6 and 21 days. Two-way MANOVA revealed that the increased RTQ was influenced by microscale roughness and the combination of nanoscale and microscale topographies. Furthermore, increased bone-implant contact (BIC) was observed with the combined nanopatterned machined surface, although MANOVA results implied that the increased BIC was mainly dependent on microscale roughness. At the molecular level, the nanotopography, per se, and in synergy with microscale roughness, downregulated the expression of the proinflammatory cytokine tumor necrosis factor alpha (TNF-α). In conclusion, controlled nanotopography superimposed on microrough machined implants promoted implant stability during osseointegration. Nanoscale-driven mechanisms may involve attenuation of the inflammatory response at the titanium implant site. Statement of SignificanceThe role of combined implant microscale and nanotopography features for osseointegration is incompletely understood. Using colloidal lithography technique, we created an ordered nanotopography pattern superimposed on screwshaped implants with microscale topography. The midterm and late molecular, bone-implant contact and removal torque responses were analysed in vivo. Nanotopography superimposed on microrough, machined, surfaces promoted the implant stability, influenced by microscale topography and the combination of nanoscale and microscale topographies. Increased bone-implant contact was mainly dependent on microscale roughness whereas the nanotopography, per se, and in synergy with microscale roughness, attenuated the proinflammatory tumor necrosis factor alpha (TNF-α) expression. It is concluded that microscale and nanopatterns provide individual as well as synergistic effects on molecular, morphological and biomechanical implant-tissue processes in vivo.

Fractal analysis of the martian landscape: A study of kilometre-scale topographic roughness

Natural and engineered surfaces can be modelled as fractal objects described by a non-integer dimension (i.e., their fractal dimension). This approach has been used extensively to characterize surface complexity in terms of rugosity or roughness. In this paper, the local fractal dimension is proposed as a means of mapping the spatial variability of the surface roughness of the Martian landscape. The local fractal dimension complements measures of topographic roughness proposed by other authors and provides new images of the Martian surface texture at the kilometric scale that can be used to interpret geological events, geological processes and geological formations. It can also assist in geological mapping and in the detection and prioritisation of sites that merit further exploration. Mars Orbiter Laser Altimeter data were used to characterize the kilometre-scale terrain roughness of Mars. The procedure is general and can also be applied to digital elevation models with higher resolution (for example, digital elevation models generated by stereo-pair HiRISE images) to assess roughness at the metric scale. Sixteen test sites were selected and used to illustrate the patterns of the spatial variability of landscape roughness (local fractal dimension maps) at the kilometric scale. The results show that the mean of the local fractal dimension ranges from 2.036 in Argyre Planitia to 2.403 at the North Pole. The results also show that the mean roughness values of the Martian landscapes are less than those of the Earth's continents. Basically, the roughness of the Martian terrain at the kilometric scale depends, inter alia, on the number of kilometric-scale landforms present on the terrain. It is thus logical that the local fractal dimension is higher on Earth, a geologically active planet, than on Mars. Only the North Pole test site (an area larger than the North polar ice cap) shows a roughness histogram similar to those of terrestrial sites. The abundance of information embedded in the spatial variability patterns in the roughness maps provides a significant resource for planetary geology research.

High-Potential Test for Quality Control of Separator Defects in Battery Cell Production

Lithium-ion batteries are a key technology for electromobility; thus, quality control in cell production is a central aspect for the success of electric vehicles. The detection of defects and poor insulation behavior of the separator is essential for high-quality batteries. Optical quality control methods in cell production are unable to detect small but still relevant defects in the separator layer, e.g., pinholes or particle contaminations. This gap can be closed by executing high-potential testing to analyze the insulation performance of the electrically insulating separator layer in a pouch cell. Here, we present an experimental study to identify different separator defects on dry cell stacks on the basis of electric voltage stress and mechanical pressure. In addition, finite element modeling (FEM) is used to generate physical insights into the partial discharge by examining the defect structures and the corresponding electric fields, including topographical electrode roughness, impurity particles, and voids in the separator. The test results show that hard discharges are associated with significant separator defects. Based on the study, a voltage of 350 to 450 V and a pressure of 0.3 to 0.6 N/mm2 are identified as optimum ranges for the test methodology, resulting in failure detection rates of up to 85%.

A blueprint of the topology and mechanics of the human ovary for next-generation bioengineering and diagnosis

Although the first dissection of the human ovary dates back to the 17th century, the biophysical characteristics of the ovarian cell microenvironment are still poorly understood. However, this information is vital to deciphering cellular processes such as proliferation, morphology and differentiation, as well as pathologies like tumor progression, as demonstrated in other biological tissues. Here, we provide the first readout of human ovarian fiber morphology, interstitial and perifollicular fiber orientation, pore geometry, topography and surface roughness, and elastic and viscoelastic properties. By determining differences between healthy prepubertal, reproductive-age, and menopausal ovarian tissue, we unravel and elucidate a unique biophysical phenotype of reproductive-age tissue, bridging biophysics and female fertility. While these data enable to design of more biomimetic scaffolds for the tissue-engineered ovary, our analysis pipeline is applicable for the characterization of other organs in physiological or pathological states to reveal their biophysical markers or design their bioinspired analogs.

The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa

The extreme variability in the topography, altitude and climatic conditions in the temperate Grassland Mountains of Southern Africa is associated with the complex mosaic of grassland communities with pockets of woodland patches. Understanding the relationships between plant communities and environmental parameters is essential in biodiversity conservation, especially for current and future climate change predictions. This article focused on the spatial distribution of woodland communities and their associated environmental drivers in the Golden Gate Highlands (GGHNP) National Park in South Africa. A generalized linear model (GLM) assuming a binomial distribution, was used to determine the optimal environmental variables influencing the spatial distribution of the woodland communities. The Coefficient of Variation (CV) was relatively higher for the topographic ruggedness index (68.78%), topographic roughness index (68.03), aspect (60.04%), coarse fragments (37.46%) and the topographic wetness index (31.33) whereas soil pH, bulk density, sandy and clay contents had relatively less variation (2.39%, 3.23%, 7.56% and 8.46% respectively). In determining the optimal number of environmental variables influencing the spatial distribution of woodland communities, roughness index, topographic wetness index, soil coarse fragments, soil organic carbon, soil cation exchange capacity and remote-sensing based vegetation condition index were significant (p 0.05) and positively correlated with the woodland communities. Soil nitrogen, clay content, soil pH, fire and elevation were also significant but negatively correlated with the woodland communities. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.81. This was indicative of a Parsimonious Model with explanatory predictive power for determination of optimal environmental variables in vegetation ecology.Conservation implications: The isolated woodland communities are sources of floristic diversity and important biogeographical links between larger forest areas in the wider Drakensberg region. They provide suitable habitats for a larger number of forest species and harbour some of the endemic tree species of South Africa. They also provide watershed protection and other important ecosystem services. Understanding the drivers influencing the spatial distribution and persistence of these woodland communities is therefore key to conservation planning in the area.

Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst Watershed

Due to numerous droughts in recent years, the amount of surface water in arid and semi-arid regions has decreased significantly, so reliance on groundwater to meet local and regional demands has increased. The Kabgian watershed is a karst watershed in southwestern Iran that provides a significant proportion of drinking and agriculture water supplies in the area. This study identified areas with karst groundwater potential using a combination of machine learning and statistical models, including entropy-SVM-LN, entropy-SVM-SG, and entropy-SVM-RBF. To do this, 384 karst springs were identified and mapped. Sixteen factors that are related to karst potential were identified from a review of the literature, and these were compiled for the study area. The 384 locations were randomly separated into two categories for training (269 location) and validation (115 location) datasets to be used in the modeling process. The ROC curve was used to evaluate the modeling results. The models used, in general, were good at determining the location of karst groundwater potential. The evaluation showed that the E-SVM-RBF model had an area under the curve of 0.92, indicating that it was most accurate estimator of groundwater potential among the ensemble models. Evaluation of the relative importance of each of the 16 factors revealed that land use, a vector ruggedness measure, curvature, and topography roughness index were the most important explainers of the presence of karst groundwater in the study area. It was also found that the factors affecting the presence of karst springs are significantly different from non-karst springs.

Grinding and polishing of the inner surface of monolithic simplified restorations made of zirconia polycrystals and lithium disilicate glass-ceramic: Effects on the load-bearing capacity under fatigue of the bonded restorations

This study evaluated the effect of grinding and polishing the inner surface of monolithic discs made of zirconia polycrystals (ZR) and lithium disilicate glass-ceramic (LD) on the load-bearing capacity under fatigue of the restorations bonded onto a dentin analogue material (epoxy resin). ZR and LD ceramic discs (10 mm in diameter, 1 mm in thickness) were produced and randomly allocated into 10 groups considering the internal adjustment approach: Ctrl – No adjustment; F – Grinding with fine diamond bur (46 μm); F + Pol – Grinding with fine diamond bur followed by polishing with 2 tips (finisher and polisher); FF – Grinding with extrafine diamond bur (30 μm); FF + Pol – Grinding with extrafine diamond bur followed by polishing. In addition, discs (10 mm in diameter, 2.5 mm in thickness) of fiber reinforced epoxy resin were produced. Afterwards, the intaglio surface of the ZR discs were air-abraded with 45 μm alumina particles for 10 s, the LD and resin epoxy discs were etched with hydrofluoric acid (5%/20 s and 10%/60 s, respectively), and the treated discs were primed as recommended. Each ceramic disc was luted onto the epoxy resin disc with resin cement. Then, the samples were tested under a step-stress fatigue test (20 Hz, 10,000 cycles/step, step-size of 100 N starting at 200 N, and proceeding until failure detection). Fractographic, topographic and surface roughness analysis were also performed. The adjustments (grinding with or without polishing) (ZR: 733–880 N; LD: 1040–1106 N) triggered a detrimental effect on the fatigue behavior in both ceramics compared with the absence of treatment (control group; ZR: 973 N; LD: 1406 N). The polishing step had no effect on fatigue findings. Thus, grinding the inner surface of the tested ceramics should be avoided wherever possible to prevent introducing damage and its detrimental effects on the fatigue behavior.

70 million years of seafloor spreading and magmatism in the South Atlantic

A basic tenet of seafloor spreading is the need to spatially accommodate the magnitude of lateral spreading. As new spreading proceeds and crust is transported away from the spreading axis, the space created is filled by both the magmatic accretion of new oceanic crust and the brittle stretching of that crust by extensional faults. The ratio between the magmatism and faulting, referred to as M, is dynamically related to the rate of spreading and the topographic roughness of the generated crust. Here we use a multichannel seismic dataset recently collected in the South Atlantic Ocean to examine how the relationships between spreading rate, M, and topographic roughness have changed over 70 million years of crustal ages all created at one spreading segment. We frequency filter the topographic profile of the top of the igneous crust to remove long wavelength signal and determine the best window length for analysis. We then use a moving window to quantify how M and the root mean square of topographic roughness vary across the age transect. Qualitatively and quantitatively, we find spreading rate and M are positively correlated while M and spreading rate are negatively correlated with the topographic roughness of the crust. We are able to expand the age and length scale of an analysis of M by an order of magnitude compared to previous studies. Our analysis also finds that the spreading center in the South Atlantic has likely alternated between an axial high and axial valley twice in the past.

Habitat suitability and connectivity implications for the conservation of the Persian leopard along the Iran-Iraq border.

Habitat fragmentation has major negative impacts on wildlife populations, and the connectivity could reduce these negative impacts. This study was conducted to assess habitat suitability and structural connectivity of the Persian leopard along the Iran–Iraq border (i.e., the Zagros Mountains) and compare the situation of identified core habitats and connectivity with existing conservation areas (CAs). An ensemble modeling approach resulting from five models was used to predict habitat suitability. To identify core habitats and corridors along the Iran–Iraq border, factorial least‐cost path analyses were applied. The results revealed that topographic roughness, distance to CAs, annual precipitation, vegetation/cropland density, and distance to rivers were the most influential variables for predicting the occurrence of the Persian leopard in the study area. By an estimated dispersal distance of 82 km (suggested by previous studies), three core habitats were identified (two cores in Iran and one core in Iraq). The largest cores were located in the south and the center of the study area, which had the highest connectivity priorities. The connectivity from these cores was maintained to the core within the Iraqi side. Only about one‐fifth of detected core habitats and relative corridors were protected by CAs in the study area. Detected core habitats and connectivity areas in this study could be an appropriate road map to accomplish the CAs network along the Iran–Iraq border regarding Persian leopard conservation. Establishing transboundary CAs, particularly in the core habitat located in the center of the study area, is strongly recommended to conserve existing large carnivores, including the Persian leopard.