Percent Area Coverage Research Articles

Microstructural Characterisation of Adsorbent Ash with Potentially Toxic Elements in a Mortar

Abstract Potentially toxic elements (PTEs) in ecosystems and construction materials pose a significant environmental concern. Various qualitative and quantitative techniques are employed to analyse PTEs in a sample. This study explores an innovative approach that incorporates PTE (Cd, Zn, Cu, Pb) adsorbent ash, specifically adsorbed paper ash (APA) and adsorbed mulch ash (AMA), into mortar composites. This approach offers several advantages, including reduced reliance on waste landfills, energy recovery during the ashing process, and immobilisation of PTEs within a cement matrix. This study evaluated the elemental and microstructural characteristics of mortar composites incorporated with adsorbed ash by using a scanning electron microscope (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS), followed by analysing the elemental maps with ImageJ software version 1.8.0. Parallel experiments were conducted to measure the leaching of mortar composites. The total elemental content of PTEs in the leachate solutions was quantified using an inductively coupled plasma-optical emission spectrometer (ICP-OES). The differences in adsorption capacity and leaching of PTEs observed between paper and mulch can be ascribed to their distinct affinities, which are influenced by the recorded pH levels. The examined elemental mapping revealed a consistent distribution across the APA and AMA mortar matrix structures, with greater intensity than the blank mortar sample. Furthermore, there is a reverse correlation between the order of percentage area coverage of the immobilised elements and the order of leaching, indicating that the PTEs were successfully immobilised. The percentage of PTE area coverage within AMA mortar composites followed the subsequent order: Pb > Cd > Zn > Cu, constituting 32.1 %, 28.6 %, 13.8 %, and 12.4 %, respectively. This order was also observed in the blank mortar composite, with percentages of 12.5 %, 8.6 %, 4.5 %, and 4.2 %, respectively. In the case of the APA mortar composite, the percentage of area coverage followed a different sequence: Cd > Pb > Zn > Cu, representing 27.7 %, 26.6 %, 14.5 %, and 14.1 %, respectively. The results also demonstrated notable improvements in the microstructure of the mortar when AMA and APA are incorporated, which is attributed to the ash additives’ micro-filling capacity. The findings contribute to advancing environmentally sound construction practices, with implications for sustainable waste management and pollution mitigation.

Correlations between [18F]flutemetamol PET and region‐matched postmortem integrated density measures of cyano‐flutemetamol signal in Aβ plaques

AbstractBackgroundThe binding substrates of [18F]flutemetamol and [11C]PiB PET consist of fibrillar amyloid‐β (Aβ) aggregates in morphologically and structurally distinct diffuse plaques (DP) and cored plaques (CP) which are present at different proportions across brain regions in Alzheimer’s disease (AD). To account for this heterogeneity, an unbiased quantitative measure integrating plaque size and density of amyloid‐β (Aβ) fibrils in plaques could help avoid false positive results, improve imaging‐to‐autopsy correlations, and further advance our understanding of pathological substrates for binding of amyloid PET tracers.MethodSixteen subjects underwent [18F]flutemetamol PET imaging in the pivotal Phase III end‐of‐life study (Study GE067‐007 and GE067‐026) and later came to autopsy (mean imaging‐to‐autopsy interval was 111 ± 87.6 days). [18F]flutemetamol SUVRpons values in four neocortical regions were correlated with region‐matched postmortem measures of cyano‐flutemetamol labeling of all plaques, as well as CP and DP separately, using percent area coverage, mean grayscale intensity of fluorescence, or a combination of the two measures referred to as integrated density.ResultIn the analysis of all cyano‐flutemetamol‐labeled plaques, [18F]flutemetamol SUVRpons values were more closely associated with integrated density measures than percent area coverage and mean grayscale values. Similarly, when CP and DP were analyzed separately, the integrated density values showed the closest association with neocortical region‐matched [18F]flutemetamol SUVRpons values. When area coverage of CP and DP were each expressed as a fraction of total plaque area coverage with or without integrating fluorescence intensity values, [18F]flutemetamol SUVRpons values within each region of interest were associated with the DP, but not the CP, area coverage measure.ConclusionThe association of antemortem [18F]flutemetamol PET and region‐matched postmortem integrated density measurements of cyano‐flutemetamol labeled plaques further supports the hypothesis that amyloid PET signal is influenced both by plaque size and Aβ fibril density within DP and CP. Further elucidating the relative contributions of each plaque type to the retention of amyloid PET radioligands could influence how a positive amyloid PET signal is interpreted in relation to postmortem pathology data.

Correlations between [18F]flutemetamol PET and region‐matched postmortem integrated density measures of cyano‐flutemetamol signal in Aβ plaques

AbstractBackgroundThe binding substrates of [18F]flutemetamol and [11C]PiB PET consist of fibrillar amyloid‐ß (Aß) aggregates in morphologically and structurally distinct diffuse plaques (DP) and cored plaques (CP) which are present at different proportions across brain regions in Alzheimer’s disease (AD). To account for this heterogeneity, an unbiased quantitative measure integrating plaque size and density of amyloid‐ß (Aß) fibrils in plaques could help avoid false positive results, improve imaging‐to‐autopsy correlations, and further advance our understanding of pathological substrates for binding of amyloid PET tracers.MethodSixteen subjects underwent [18F]flutemetamol PET imaging in the pivotal Phase III end‐of‐life study (Study GE067‐007 and GE067‐026) and later came to autopsy (mean imaging‐to‐autopsy interval was 111 ± 87.6 days). [18F]flutemetamol SUVRpons values in four neocortical regions were correlated with region‐matched postmortem measures of cyano‐flutemetamol labeling of all plaques, as well as CP and DP separately, using percent area coverage, mean grayscale intensity of fluorescence, or a combination of the two measures referred to as integrated density.ResultIn the analysis of all cyano‐flutemetamol‐labeled plaques, [18F]flutemetamol SUVRpons values were more closely associated with integrated density measures than percent area coverage and mean grayscale values. Similarly, when CP and DP were analyzed separately, the integrated density values showed the closest association with neocortical region‐matched [18F]flutemetamol SUVRpons values. When area coverage of CP and DP were each expressed as a fraction of total plaque area coverage with or without integrating fluorescence intensity values, [18F]flutemetamol SUVRpons values within each region of interest were associated with the DP, but not the CP, area coverage measure.ConclusionThe association of antemortem [18F]flutemetamol PET and region‐matched postmortem integrated density measurements of cyano‐flutemetamol labeled plaques further supports the hypothesis that amyloid PET signal is influenced both by plaque size and Aß fibril density within DP and CP. Further elucidating the relative contributions of each plaque type to the retention of amyloid PET radioligands could influence how a positive amyloid PET signal is interpreted in relation to postmortem pathology data.

Drought prediction: Insights from the fusion of LSTM and multi-source factors

In the context of current global climate change, accurate drought prediction is crucial for water resources management and agricultural production. Although traditional drought forecasting methods largely rely on historical climatic data, these methods cannot fully consider the long-term effects of factors, such as climate change, and the evaluation of prediction results is limited. Therefore, this study proposed a drought prediction and evaluation framework based on Long Short-Term Memory (LSTM), integrating multi-source factors to significantly enhance the accuracy and reliability of drought prediction models. This framework applied two distinct forecasting schemes. The first scheme utilized ten diverse factors, including precipitation, evaporation, bare soil percentage area coverage, percentage crop cover, leaf area index, runoff, surface runoff, soil moisture, temperature, and total vegetated percentage cover, to predict future precipitation and evaporation, which was then used to calculate the Standardized Precipitation-Evaporation Index (SPEI) to evaluate drought characteristics. The second scheme directly used these ten factors and historical SPEI to predict future SPEI, further assessing future drought characteristics. By comparing the drought prediction results of the two schemes in terms of data statistics, drought characteristics, and spatial patterns, it was found that the LSTM model significantly improved accuracy when handling high-dimensional complex data and predicting key factors such as precipitation, evaporation, temperature, and soil moisture. The first scheme was more accurate when predicting severe and extreme droughts, whereas the second scheme was more sensitive to predicting moderate and mild droughts and exhibited higher stability and regularity in predicting the spatial variability of drought. In summary, LSTM has made significant improvements in the accuracy, stability, and reliability of drought prediction, providing stronger support for practical applications, such as agriculture and water resources management, and offering a new research tool for further climate change research.

Impacts of climate and land use/cover change on mini-hydropower generation in River Kyambura watershed in South Western part of Uganda

Abstract This study explored the combined impacts of climate and land-use change on mini-hydropower generation in the Kyambura watershed. The soil and water assessment tool (SWAT) was used as a hydrological model whereas the statistical downscaling model (SDSM) was used to downscale meteorological data for the Kyambura watershed for the year 2050. The results show that there will be an increase in urban land by 11.89%, barren land by 25.78%, water by 0.49% and a reduction in percentage area coverage of vegetation by 38.17% by the year 2050. A 10.6 and 17.7% increase is anticipated in average annual hydropower generated by the year 2050. There is, therefore, a need to develop governing policies to regulate management practices to preserve the integrity of the watersheds and ensure the reliability of power production.

Identification of Phytochemical Constituents in Phyllanthus acidus L. Leaf through Gas Chromatography-Mass Spectroscopy as Biostimulant

The Phyllanthus acidus L. belongs to the family phyllanthaceae and possess a wide range of secondary metabolites and phytochemicals in leaves. To siphon off the use of synthetic chemicals in crop production, an alternative like utilizing the natural bio-stimulants could play a crucial role in promoting crop growth and development. The major goal of this study was to employ gas chromatography-mass spectrometry to examine the bioactive compounds present in phyllanthus leaf and to identify and characterize them utilizing dichloromethane as extraction solvent. According to GC-MS analysis, dichloromethane extraction of phyllanthus leaf yielded, 25 phytoconstituents in which ethyl oleate contributed the area percentage of 53.68%, hexadecanoic acid, ethyl ester by 17.47%, octadecanoic acid, ethyl ester by 4.56%, squalene by 1.93% and cyclodecasiloxane, eicosamethyl- by 1.80% were having the largest area coverage percentage. Since most of the phytoconstituents are growth stimulants, it is suggested that phyllanthus leaf extracts be produced on a commercial scale as an exogenous biostimulant for plant growth and development.

Detection of fusarium head blight in wheat under field conditions using a hyperspectral camera and machine learning

Fusarium head blight (FHB) is among the most devastating fungal diseases in cereal crops, reducing yield, and affecting human and livestock health through the production of mycotoxin. Despite application of fungicides, complete eradication of disease is virtually impossible in the field. There is a need for a disease detection technology during late growing stage for estimation of yield affected with FHB and for potential selective harvesting. Most published studies have focused on FHB detection during the milk growth stage using hyperspectral cameras. This preliminary study attempted to fill the knowledge gap by detecting FHB at the ripening stage. A spectral library of healthy and infected ears was collected with a hyperspectral camera in the visible and near-infrared region, over the canopy of eight different wheat varieties. The ears were segmented from the background using a simple linear iterative clustering (SLIC) superpixel algorithm on the normalized difference vegetation index (NDVI) images. Three different machine learning methods, namely, support vector machine (SVM), artificial neural network (ANN), and logistic regression (LR), were utilized for classification. To visualize the FHB distribution in the hypercube, the best performing model was applied for predicting the infected ears in the canopy images. The percentage area coverage of FHB for each hypercube was estimated. Results showed that the SVM algorithm produced the best classification accuracy (CA) of 95.6 % in the test set, followed successively by ANN and LR with CA values of 82.9 and 82.5 %, respectively. Interestingly, the preliminary study shows significant differences in spectral reflectance according to the variety of different resistance levels. The study also proves the feasibility of FHB detection using the developed prediction model during late growth stage with the potential of yield loss estimation before harvest.

SPATIAL RELATIONSHIP BETWEEN LAND-USE LAND COVER WITH SOIL EROSION IN THE NARMADA BASIN USING SENTINEL 2 IMAGE: ASSESSING THE PERFORMANCE OF RF MACHINE LEARNING CLASSIFIER

In the past decades, increasing demand for cultivable soil, deforestation and land conversion in the region has led to severe soil and natural resources exhaustion. The grade and rate of the soil and land-use land-capacity connection has been determined using soil parameter data together with geographic information systems, utilizing machine learning methods (random forest).The analysis shows high and substantial land coverage over Grass Land area with 52,330.59 sq. km/54.5 percent, with an Urban growth of 19,255.36 sq.km/20.0 percent, 12,400.51 sq.km/12.9 percent for Agriculture, Forest land with 8,828.67 sq.km/9.2 percent, 1,970.382 sq.km/2.0 percent for water and the smallest land cover among the classes was cropland with 1,337.51 sq.km/1.4 percent area coverage. Random forest algorithms show that soil erosion for the whole Upper catchment was lower compared to the bottom catchment region and high soil erosion in line with the land conversation of natural vegetation. This analysis includes extra significant information and differences between kinds of land use soil erosion with a major and very severe area 38.337.55 sq.km/39.9 percent; the severely eroded soil covers 29.346.59 sq.km/30.5 percent; the modest soil erosion area (15.372.16 sq.km/16.00 percent); the lowest or slightest soil erosion zone was 13066.73 sq.km/13.6 percent. To strengthen the status and use of the collected resources as a result of sustainable land use activities that benefit local rural life, inclusive and viable land use is needed immediately. The area where very severe soil erosion and the land cover has been correlated to determine the relationship with the existing land covers in the area, decreases of soil erosion indicates the change in the land uses. The correlation between the LULC and the soil erosion was 0.53, with an RMSE of 0.033 and a p-value of 0.000063.

Association Between Oct-Based Microangiography Perfusion Indices and Diabetic Retinopathy Severity in Patients with Diabetes in Pakistan

Objective: To assess the relationship between capillary perfusion of retinal vessels and severity of diabetic retinopathy with the help of Optical Coherence Tomography angiography.
 Study Design: Cross-sectional study.
 Place and Duration of Study: Armed Forces Institute of Ophthalmology, Rawalpindi Pakistan, from Feb 2020 to Apr 2021.
 Methodology: Seventy-three eyes of 37 subjects suffering from diabetes had their imaging done with Rtvue Avanti OCT angio system. Socio-demographic and clinical data was gathered. Subjects were divided into three groups depending upon the severity of diabetes. The perfusion index (PI) was taken as percent area coverage by retinal vessels with the flow.
 Results: Out of a total of 73 eyes, 31 (42.5%) had none to mild Non-Proliferative Diabetic Retinopathy, 19 (26%) with moderate to severe Non-Proliferative Diabetic Retinopathy and 23 (31.5%) with Proliferative Diabetic Retinopathy. The mean age of the participants was 58.09 ± 10.32 years, with best corrected visual acuity as 0.35 ± 0.35 and Blood Sugar Random as 200.46 ± 70.71. BCVA showed a significant positive correlation with Perfusion Index (p=0.026). No significant association/relationship was found between the severity of diabetic retinopathy and perfusion index in this data (p=0.26).
 Conclusion: No statistically significant relationship was found between Perfusion Index (PI) and severity of diabetic retinopathy.

An Energy-Efficient Routing Scheduling Based on Fuzzy Ranking Scheme for Internet of Things

Internet of Things (IoT) is a wireless network of various battery-powered sensing units. Due to the limited battery capacity, the nonaccessible/abandoned nodes demand more energy to be reached or reintegrated to keep the network connected. When a specific tree topology for routing, called destination-oriented directed acyclic graphs (DODAGs), is used, isolated nodes spend maximum energy on the assigned task during data transformation from the sensor field to the DODAG root. The nodes closer to the DODAG root need to rely on faraway nodes and resource-burden-constrained nodes to lead to the quick energy drain. It brings an idea of IoT network nodes in which an extra amount of energy provide to the longer time alive nodes. This article proposes an ARFOR-adaptive ranking fuzzy-based energy-efficient opportunistic routing protocol for sustainable IoT applications. The proposed protocol consists of a parent node (PN) that acts as a head node in a cluster to aggregate the packets to DODAG root; and a volunteer node (VN) acts as a forwarder to transfer the packets to PN with threshold energy limits to increase network lifetime during the transmission cycle. The proposed VN selection is based on fuzzy parameters, such as Canberra distance, residual energy, and threshold. The simulation outcomes depict that the ARFOR fairly justifies the network timeline requirement with maximum percentage area coverage. The percentage gain in terms of network lifetime is comparatively significant for a lower number of VN.

Integrated spatial planning for biodiversity conservation and food production

Integrated spatial planning for biodiversity conservation and food production

A quantitative analysis of overspray in Aerosol Jet® printing

As Aerosol Jet® (AJ) printing is becoming more attractive to additive manufacturing, printed electronics, among other applications, reducing or minimizing the amount of ink droplets landing in unintended regions—known as the overspray—has been elevated on the agenda for print quality control and improvement. Many AJ users had discussed the overspray issue associated with AJ printing, while the metrology for quantified evaluation of overspray is still lacking. In this work, the likely physical mechanism for inducing overspray is analyzed along with a set of computational fluid dynamics (CFD) simulations. We then present a 2D image processing method for quantitatively evaluating the severity of overspray in terms of its percent area coverage versus a normalized distance from printed line edge. Our results show that the amount of overspray of AJ printing seems to scale with the printed line width (LW), and usually to become negligible (e.g. percent area coverage of overspray < 1%) beyond 30%–40% of LW from line edges. The overspray is shown to often decrease by increasing the jet velocity and sheath-to-mist ratio. Without loss of generality and for concise illustration, herewith we use only one representative ink to print test samples for the quantitative overspray analysis. The results have been found to bear a resemblance to AJ printed features with many other inks.

A Study on Pesticide Sprayer Powered by Solar Energy Appropriate for Small Farms

The study was conducted on a knapsacksprayer powered by a DC motor through a 12 V lead acid battery charged from a solar panel (photovoltaic) directed to sun rays. The system was installed and tested in the western desert on a small-scale farm at Frafra Oasis (New val-ley). This study aimed to evaluate and develop a knapsack sprayer powered by a solar energy for overcoming operator fatigue and shortage of traditional energy in Egypt’s western desert. The experiments were conducted during the period which starts in August 2019 till Febru-ary 2020. The main parts of the system consist of photovoltaic (PV) or solar cells, charger controller, rechargeable battery, and DC motor speed control with dimmer and pump which was attached with a tank 20 liters capacity for sucking and pressurizing the liquid to the boom of the sprayer through a flexible hose. The main results of experiments were as fol-lows: The time for recharging the battery com-pletely was found 330 minutes (5.5 hours) to charge completely from 10.55 V – 13.85 V, with current intensity 1.67 Ampere. The bat-tery discharge time was varied due to drop the battery voltage from 13.85 – 10.55 Volts. De-pending on the motor speed, which is the time for discharging the battery was found 4 – 9 hours, when motor pulled 0.85 - 1.85 Amps at 2000 - 3400 rpm and this time at deferent speed is enough to spray area 3 - 6.82 fed/day day work = 6 hours with application rate 67 - 104.7 l/fed. The number of droplets and the area coverage percentage ranges from 30 – 146.33 drops and 13.96 – 27.97% for one cm2 of simulator targets at a speed ranging from 2000 – 3400 rpm, respectively.

Coverage Aware Scheduling Strategies for 3D Wireless Video Sensor Nodes to Enhance Network Lifetime

High-density wireless video sensor nodes (VSNs) having limited battery power are deployed randomly in the disaster-hit area for capturing visual data, but its local processing and transmission consume high energy. High deployment density of those VSNs results in a larger overlap in the coverage area across VSNs that can be utilized to cover the sensing region of some VSNs and shut off such VSNs to decrease energy consumption and increase network lifetime without losing much area coverage. Two advanced approaches (APP_5 and APP_6) with realistic 3D rectangular pyramid camera coverage of VSN monitoring 2D target area is proposed in this paper. These approaches reduce the number of active VSNs in the target area and energy consumption maintaining the overall coverage area above some threshold value ensuring network connectivity. The approaches are compared with the three state-of-the-art approaches EX_1, EX_2 and EX_3 in the same simulation setup. Observed that for 150 deployed VSNs over the target area of size $75\times 75$ square meters, APP_5 and APP_6 reduce energy consumption by 6.98% and 18.6% respectively from the existing approach EX_3 (producing a better result among three existing approaches in terms of energy consumption). Reducing the number of active VSNs helps decrease energy consumption at the expense of reduced area coverage. For the same node density, both APP_5 and APP_6 lose a little amount of area coverage (i.e. 0.93% and 0.95%) than the existing approach EX_2 (producing a better result among three existing approaches in terms of percentage of area coverage). Additionally, both the proposed approaches (having the same communication overhead) establish superiority by 3.19%/7.83%/4.25% from EX_1/EX_2/(EX_3) in terms of communication overhead for 100 deployed VSNs on the same target area. Finally, APP_6 substantiates superiority in terms of reduced energy consumption (11.97%) than APP_5 losing a very little percentage (0.02%) of area coverage for 150 deployed VSNs.

Environmental dust repelling from hydrophobic and hydrophilic surfaces under vibrational excitation

Mitigation of environmental dust from surfaces becomes one of the challenges for maintaining the optical characteristics of surfaces. Dust repelling from hydrophobic and hydrophilic surfaces under vibrational excitation is investigated and the percentage of dust repelled from surfaces is evaluated. The characteristics of the dust particles are examined and dust adhesion on surfaces under molecular forces (van der Walls) is explored. High speed recording system is utilized to monitor dust repelling from the surfaces. The dust residues, which are not repelled from the sample surfaces, are analyzed and the percentage of area coverage of the dust repelled from the surfaces is assessed. The repelling height of the dust is predicted analytically, and the findings are compared with the experimental data. Findings revealed that the analytical predictions of dust repelling height are in good agreement with the experimental data. Due to none-stoichiometric elemental compositions in the dust compounds, ionic forces are created while forming the cluster-like structures because of particle adhesion. The vibrational excitation repels dust from sample surfaces in the form of cluster-like structures. Dust repelled from hydrophobic surface results in a larger clean area on the hydrophobic surface (80% of total surface area) than that of the hydrophilic surface (20% of total surface area).

Post-mortem analyses of PiB and flutemetamol in diffuse and cored amyloid-\u03b2 plaques in Alzheimer\u2019s disease

Specificity and sensitivity of positron emission tomography (PET) radiopharmaceuticals targeting fibrillar amyloid-β (Aβ) deposits is high for detection of neuritic Aβ plaques, a mature form of Aβ deposits which often have dense Aβ core (i.e., cored plaques). However, imaging-to-autopsy validation studies of amyloid PET radioligands have identified several false positive cases all of which had mainly diffuse Aβ plaques (i.e., plaques without neuritic pathology or dense amyloid core), and high amyloid PET signal was reported in the striatum where diffuse plaques predominate in Alzheimer’s disease (AD). Relative contributions of different plaque types to amyloid PET signal is unclear, particularly in neocortical areas where they are intermixed in AD. In vitro binding assay and autoradiography were performed using [3H]flutemetamol and [3H]Pittsburgh Compound-B (PiB) in frozen brain homogenates from 30 autopsy cases including sporadic AD and non-AD controls with a range of brain Aβ burden and plaque density. Fixed tissue sections of frontal cortex and caudate from 10 of the AD cases were processed for microscopy using fluorescent derivatives of flutemetamol (cyano-flutemetamol) and PiB (cyano-PiB) and compared to Aβ immunohistochemistry and pan-amyloid (X-34) histology. Using epifluorescence microscopy, percent area coverage and fluorescence output values of cyano-PiB- and cyano-flutemetamol-labeled plaques in two-dimensional microscopic fields were then calculated and combined to obtain integrated density measurements. Using confocal microscopy, we analysed total fluorescence output of the entire three-dimensional volume of individual cored plaques and diffuse plaques labeled with cyano-flutemetamol or cyano-PiB. [3H]Flutemetamol and [3H]PiB binding values in tissue homogenates correlated strongly and their binding pattern in tissue sections, as seen on autoradiograms, overlapped the pattern of Aβ-immunoreactive plaques on directly adjacent sections. Cyano-flutemetamol and cyano-PiB fluorescence was prominent in cored plaques and less so in diffuse plaques. Across brain regions and cases, percent area coverage of cyano-flutemetamol-labeled plaques correlated strongly with cyano-PiB-labeled and Aβ-immunoreactive plaques. For both ligands, plaque burden, calculated as percent area coverage of all Aβ plaque types, was similar in frontal cortex and caudate regions, while integrated density values were significantly greater in frontal cortex, which contained both cored plaques and diffuse plaques, compared to the caudate, which contained only diffuse plaques. Three-dimensional analysis of individual plaques labeled with either ligand showed that total fluorescence output of a single cored plaque was equivalent to total fluorescence output of approximately three diffuse plaques of similar volume. Our results indicate that [18F]flutemetamol and [11C]PiB PET signal is influenced by both diffuse plaques and cored plaques, and therefore is likely a function of plaque size and density of Aβ fibrils in plaques. Brain areas with large volumes/frequencies of diffuse plaques could yield [18F]flutemetamol and [11C]PiB PET retention levels comparable to brain regions with a lower volume/frequency of cored plaques.

Lagged Compound Occurrence of Droughts and Pluvials Globally Over the Past Seven Decades

AbstractThe drought‐pluvial seesaw—defined as the phenomenon of pluvials (wet spells) following droughts (dry spells)—magnifies the impact of individual pluvial and drought events yet has not been systematically evaluated, especially at the global scale. We apply an event coincidence analysis to explore the aggregated seesaw behavior based on land surface model simulations for the past seven decades (1950–2016). We find that globally, about 5.9% and 7.6% of the land surface have experienced statistically significant (p&lt;0.10) drought‐pluvial seesaw behavior during the boreal spring‐summer and fall‐winter, with an average 11.1% and 11.4% of all droughts being followed by pluvials in the following season, respectively. Although this global frequency pattern is modest and coherent changes cannot be detected at the subcontinental scale, local hot spots of drought‐pluvial seesaw have become more frequent than either droughts or pluvials alone in the last three decades, albeit with a small percentage of area coverage.

Electrochemical Decoration of Additively Manufactured Graphene Macroelectrodes with MoO2 Nanowires: An Approach to Demonstrate the Surface Morphology

Additive manufacturing (AM) provides a unique platform for the rapid design and fabrication of complex structures. Printed structures can be used as is or as templates to be decorated with electrochemical deposited nanomaterials, which may be utilised as electrocatalytic sensing platforms. Novel methods are required to determine the electrochemical deposited morphology present on the electrode surfaces. Additively manufactured graphene macroelectrodes (AM-GMs) were fabricated using a commercially available feedstock and molybdenum (di)oxide (MoO2) was successfully electrochemically deposited onto the electrode surface. The electrochemically deposited MoO2 was analysed using scanning electron microscopy (SEM), optical interferometry, Raman spectroscopy and multifractal analysis (MFA). Although the electrochemical deposition of MoO2 nanowires were clearly visible using SEM, MFA enabled quantification of the MoO2 nanowires, deposited at a variety of time points (20 – 300 s). MFA was utilised to generate quantitative data, derived from ƒ(α) curves, to determine the area of the electrochemical deposited MoO2 nanowires, including coverage, density, dispersion and clustering. The AM-GMs which were subjected to 300 s (maximum time period) of MoO2 electrodeposition demonstrated the greatest percentage area coverage (20.14 %). The use of such mathematical systems offers an inexpensive method to characterise the parameters of electrochemically-deposited materials.

Epidermal growth factor treatment of female mice that express APOE4 at an age of advanced pathology mitigates behavioral and cerebrovascular dysfunction

APOE4 is a major genetic risk factor for Alzheimer's disease and high amyloid-β (Aβ) levels in the brain are a pathological hallmark of the disease. However, the contribution of specific APOE-modulated Aβ-dependent and Aβ-independent functions to cognitive decline remain unclear. Increasing evidence supports a role of APOE in modulating cerebrovascular function, however whether ameliorating this dysfunction can improve behavioral function is still under debate. We have previously demonstrated that systemic epidermal growth factor (EGF) treatment, which is important for vascular function, at early stages of pathology (treatment from 6 to 8 months) is beneficial for recognition and spatial memory and cerebrovascular function in female mice that express APOE4. These data raise the important question of whether EGF can improve APOE4-associated cerebrovascular and behavioral dysfunction when treatment is initiated at an age of advanced pathology. Positive findings would support the development of therapies that target cerebrovascular dysfunction associated with APOE4 in aging and AD in individuals with advanced cognitive impairment. Therefore, in this study female mice that express APOE4 in the absence (E4FAD- mice) or presence (E4FAD+ mice) of Aβ overproduction were treated from 8 to 10 months of age systemically with EGF. EGF treatment mitigated behavioral dysfunction in recognition memory and spatial learning and improved hippocampal neuronal function in both E4FAD+ and E4FAD- mice, suggesting that EGF treatment improves Aβ-independent APOE4-associated deficits. The beneficial effects of EGF treatment on behavior occurred in tandem with improved markers of cerebrovascular function, including lower levels of fibrinogen, lower permeability when assessed by MRI and higher percent area coverage of laminin and CD31 in the hippocampus. These data suggest a mechanistic link among EGF signaling, cerebrovascular function and APOE4-associated behavioral deficits in mice with advanced AD-relevant pathology.

Evaluating the quality of WAAS availability control algorithm under geomagnetic storm conditions

Introduction: The Wide Area Augmentation System (WAAS) is vulnerable to false alarms about the violation of the required navigation parameter availability under geomagnetic disturbances. As a consequence, the system operation efficiency might decrease because of a mismatch between the output of the control system and the actual quality of the navigation-time support. Purpose: Comparative analysis of the actual quality of navigation-and-time support for GPS users and the output information of the system for monitoring the availability of the required WAAS navigation parameters under a moderate magnetic storm and with technical failures during the operation of separate segments of GPS and WAAS systems. Results: Location errors were calculated for 82 reference stations in the USA equipped with GPS navigation receivers. The calculations used the geometric ranges of visible navigation satellites and the corresponding real values of the ionospheric range-measurement error determined by the method of two-frequency measurements. Based on the same data and through the use of the conventional standard WAAS availability control algorithm, the user protection levels were calculated in the horizontal and vertical planes. The results of these calculations are presented as a time graph of WAAS operating area coverage percentage, which was compared with the respective graphs presented in the official WAAS work reports. It is established that there are cases of significant discrepancy between the forecasts about the availability of the required navigation parameters according to the WAAS data and the real quality of positioning in the operating area of this system. There are discrepancies in the results of calculations of protection levels in the horizontal and vertical planes obtained from official reports on the operation of the system and in calculations based on the geometric range and real ionospheric range-measurement error. Practical relevance: Recommendations are proposed in order to reconsider the development of a navigation parameter availability control for wide-area augmentation systems, splitting the calculation into “locally dependent” and “globally dependent” components of differential corrections of range-measurement errors. It will reduce the likelihood of false alarms or dangerous inconsistencies in information within the system.