An Efficient Adaptive and Steep-Convergent Sidelobes Simultaneous Reduction Algorithm for Massive Linear Arrays

Antenna arrays have become an essential part of most wireless communications systems. In this paper, the unwanted sidelobes in the symmetric linear array power pattern are reduced efficiently by utilizing a faster simultaneous sidelobes processing algorithm, which generates nulling sub-beams that are adapted to control and maintain steep convergence toward lower sidelobe levels. The proposed algorithm is performed using adaptive damping and heuristic factors which result in learning curve perturbations during the first few loops of the reduction process and is followed by a very steep convergence profile towards deep sidelobe levels. The numerical results show that, using the proposed adaptive sidelobes simultaneous reduction algorithm, a maximum sidelobe level of −50 dB can be achieved after only 10 iteration loops (especially for very large antenna arrays formed by 256 elements, wherein the processing time is reduced to approximately 25% of that required by the conventional fixed damping factor case). On the other hand, the generated array weights can be applied to practical linear antenna arrays under mutual coupling effects, which have shown very similar results to the radiation pattern of the isotropic antenna elements with very deep sidelobe levels and the same beamwidth.

Damping Properties of Hybrid Composites Made from Carbon, Vectran, Aramid and Cellulose Fibers

Hybridization of carbon fiber composites can increase the material damping of composite parts. However, there is little research on a direct comparison of different fiber materials—particularly for carbon fiber intraply-hybrid composites. Hence, the mechanical- and damping properties of different carbon fiber intraply hybrids are analyzed in this paper. Quasi unidirectional fabrics made of carbon, aramid, Vectran and cellulose fibers are produced, and their mechanical properties are analyzed. The material tests show an increased material damping due to the use of Vectran and aramid fibers, with a simultaneous reduction in strength and stiffness.

Numerical investigation on the impact of multiple injection strategies and spray included angles on combustion and emissions in a marine diesel engine

The computational fluid dynamical software AVL-FIRE code was used for investigating the impact of multiply injection strategies and spray included angles on combustion and emissions in a marine diesel engine. The fuel injection parameters of spray included angle and pilot injection timing with pilot-main injection, as well as post injection ratio and post injection duration angle with pilot-main-post injection, were all investigated and optimized. The results indicate that retarding pilot injection timing with pilot-main injection declines high temperature region, resulting in a notable reduction in NOx emissions. Since fuel evaporation and burn are hampered by long spray penetration due to low temperature and pressure with pilot injection, a suitable spray included angle are used to offer more efficient air-fuel mixing process. A wider spray included angle simultaneously reduces soot emission and indicated specific fuel consumption (ISFC). Post injection fuel exerts impact on combustion process by causing a great disturbance to flow field during post combustion. Increasing post injection ratio from 4% to 10% at a small post injection duration angle great emission performance is achieved by simultaneous reduction in NOx and soot emissions while only using a slight consumption of ISFC. To summarize, the defeat of traditional NOx-soot trade-off occurs as both NOx and soot emissions are decreased with optimized multiple injection strategy and spray included angle. Particularly, there are respectively four cases with pilot-main injection and two cases with pilot-main-post injection, that achieve simultaneous reduction in NOx emissions, soot emission, and ISFC, compared to the prototype.

An Attempt to Study Natural H2 Resources across an Oceanic Ridge Penetrating a Continent: The Asal–Ghoubbet Rift (Republic of Djibouti)

Dihydrogen (H2) is generated by fluid–rock interactions along mid-ocean ridges (MORs) and was not, until recently, considered as a resource. However, in the context of worldwide efforts to decarbonize the energy mix, clean hydrogen is now highly sought after, and the production of natural H2 is considered to be a powerful alternative to electrolysis. The Afar Rift System has many geological features in common with MORs and offers potential in terms of natural H2 resources. Here, we present data acquired during initial exploration in this region. H2 contents in soil and within fumaroles were measured along a 200 km section across the Asal–Ghoubbet rift and the various intervening grabens, extending from Obock to Lake Abhe. These newly acquired data have been synthesized with existing data, including those from the geothermal prospect area of the Asal–Ghoubbet rift zone. Our results demonstrate that basalt alteration with oxidation of iron-rich facies and simultaneous reduction in water is the likely the source of the hydrogen, although H2S reduction cannot be ruled out. However, H2 volumes at the surface within fumaroles were found to be low, reaching only a few percent. These values are considerably lower than those found in MORs. This discrepancy may be attributed to bias introduced by surface sampling; for example, microorganisms may be preferentially consuming H2 near the surface in this environment. However, the low H2 generation rates found in the study area could also be due to a lack of reactants, such as fayalite (i.e., owing to the presence of low-olivine basalts with predominantly magnesian olivines), or to the limited volume and slow circulation of water. In future, access to additional subsurface data acquired through the ongoing geothermal drilling campaign will bring new insight to help answer these questions.

Viscoelastic Polyurethane Foams with Reduced Flammability and Cytotoxicity

Consistent and proper use of respiratory protective devices (RPD) is one of the essential actions that can be taken to reduce the risk of exposure to airborne hazards, i.e., biological and nonbiological aerosols, vapours, and gases. Proper fit of the facepiece and comfort properties of RPDs play a crucial role in effective protection and acceptance of RPDs by workers. The objective of the present paper was to develop viscoelastic polyurethane foams for use in RPD seals characterised by proper elasticity, allowing for the enhancement of the device fit to the face and the capability of removing moisture from the skin in order to improve the comfort of RPD use. Moreover, it was pivotal to ensure the non-flammability of the foams, as well as a simultaneous reduction in their cytotoxicity. The obtained foams were characterised using scanning electron microscopy, infrared spectroscopy, thermogravimetry, and differential scanning calorimetry. Measurements also involved gel fraction, apparent density, compression set, rebound resilience, wettability, flammability, and cytotoxicity. The results are discussed in the context of the impact of modifications to the foam formulation (i.e., flame-retardant type and content) on the desired foam properties. The test results set directions for future works aimed to develop viscoelastic polyurethane foams that could be applied in the design of respiratory protective devices.

STUDY OF THE INFLUENCE OF DISPERSITY AND CHEMICAL COMPOSITION OF NICKEL RENEUAL ALLOYS ON THE SPECIFICITY OF REDUCTION OF ADAMANTANE-CONTAINING UNSATURED NITRILE

The regularities of the reduction of adamantane-containing unsaturated nitrile-nickel-aluminum alloy are investigated. It has been shown that under the conditions of synthesis it is possible to carry out the simultaneous reduction of both the double bond and the nitrile group. It was found that the reduction of nitriles containing 1 hydroxyl group in the position leads to a significant decrease in the rate of the process. The effect of the grain size composition of the alloy and damping additives on the reduction of unsaturated nitriles has been studied.

Effects of Selective Dry Cow Treatment on Intramammary Infection Risk after Calving, Cure Risk during the Dry Period, and Antibiotic Use at Drying-Off: A Systematic Review and Meta-Analysis of Current Literature (2000–2021)

The objectives of this paper were (i) to perform a systematic review of the literature over the last 21 yr and (ii) to evaluate the efficacy of selective dry cow treatment (SDCT) vs. blanket dry cow treatment (BDCT) in dairy cows regarding the risk of intramammary infection (IMI) after calving, new IMI risk after calving, cure risk during the dry period, and a reduction in antibiotic use at drying-off by meta-analysis. The systematic search was carried out using the databases PubMed, CAB Direct, and ScienceDirect. A meta-analytical assessment was performed for each outcome of interest using random-effects models, and the relative risk (RR) for IMI and cure or the pooled proportion for antibiotic use was calculated. The final number of included studies was n = 3 for IMI risk after calving and n = 5 for new IMI risk after calving, cure risk during the dry period, and antibiotic use. The RR levels for IMI (RR, 95% confidence interval [CI]: 1.02, 0.94–1.11; p = 0.592), new IMI (RR, 95% CI: 1.06, 0.94–1.20; p = 0.994), and cure (RR, 95% CI: 1.00, 0.97–1.02; p = 0.661) did not differ significantly between SDCT and BDCT. Substantial heterogeneity was observed between the trials regarding the pooled proportion of antibiotic use within the SDCT groups (I2 = 97.7%; p < 0.001). This meta-analysis provides evidence that SDCT seems to be an adequate alternative to BDCT regarding udder health with a simultaneous reduction in antibiotic use. Limitations might arise because of the small number of studies included.

NEE estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system

3-hourly Net Ecosystem Exchange (NEE) is estimated at spatial scales of 0.25 degrees over the European continent, based on the pre-operational inverse modelling framework CarboScope Regional (CSR) for the years 2006 to 2019. To assess the uncertainty originating from the choice of a-priori flux models and observational data, ensembles of inversions were produced using three terrestrial ecosystem flux models, two ocean flux models, and three sets of atmospheric stations. We find that the station set ensemble accounts for 61 % of the total spread of the annually aggregated fluxes over the full domain when varying all these elements, while the biosphere and ocean ensembles resulted in much smaller contributions to the spread of 28 % and 11 %, respectively. These percentages differ over the specific regions of Europe, based on the availability of atmospheric data. For example, the spread of the biosphere ensemble is prone to be larger in regions that are less constrained by CO2 measurements. We further investigate the unprecedented increase of temperature and simultaneous reduction of Soil Water Content (SWC) observed in 2018 and 2019. We find that NEE estimates during these two years suggest an impact of drought occurrences represented by the reduction of Net Primary Productivity (NPP), which in turn lead to less CO2 uptake across Europe in 2018 and 2019, resulting in anomalies up to 0.13 and 0.07 PgC yr-1 above the climatological mean, respectively. Annual temperature anomalies also exceeded the climatological mean by 0.46 °C in 2018 and by 0.56 °C in 2019, while standardized-precipitation-evaporation-index (SPEI) anomalies declined to −0.20 and −0.05 SPEI units below the climatological mean in both 2018 and 2019, respectively. Therefore, the biogenic fluxes showed a weaker sink of CO2 in both 2018 and 2019 (−0.22±0.05 and −0.28±0.06 PgC yr-1, respectively) in comparison with the mean −0.36±0.07 PgC yr-1 calculated over the full analysed period (i.e., fourteen years). These translate into a continental-wide reduction of the annual sink by 39 % and 22 %, respectively, larger than the typical year-to-year standard deviation of 19 % observed over the full period.

Bayesian networks application to forecast the national economies development taking into account the water factor

The influence of this factor on the development of national economies is studied. This study uses the Bayesian network, which illustrates the interaction of indicators of water supply and water use and includes nodes that are formally represented as vectors. The most valuable result of the modelling is not the general forecast obtained with the help of the model, but the structure of the network itself, which allows to identify connections within the model and explain the reason for the emerging interdependencies. modelling using Bayesian networks confirmed the fact that there is a direct relationship between GDP and water consumption and drainage. The obtained results confirm the possibility of achieving an increase in the overall GDP of the country with an increase in the amount of water resources used for production needs. However, this should be implemented in combination with a simultaneous reduction in the volume of return (wastewater) discharged into surface water bodies.