Density Variables Research Articles

Risk valuation for E. coli contamination in Campania region shellfish from 2016 to 2021

This study set out to assess the microbiological quality of shellfish collected over a six-year period of time in the Campania Region Sea. A total of 1459 samples were examined in order to determine whether Escherichia coli was present. To investigate potential correlations between the E. coli counts and environmental parameters (salinity, pH, dissolved oxygen, seawater temperature, turbidity, rainfall) and pollution variables (density and distance of heavy and light discharges), data were gathered. With only roughly 19% of the samples not meeting European and Italian criteria (E. coli counts more than 230 most likely number MPN per 100 g of pulp and intravalvar liquid), the results showed that the microbiological quality of the shellfish was good.A correlation between microbial contamination, season, rainfall, and dissolved oxygen was found using statistical analysis. However, the discharge density along the coast per spatial unit (a 200 × 200 MT cell), which was determined using the "quartic" Kernel function, showed found to be the primary factor determining the E. coli concentration in the shellfish.An increase in rain millimeters was found to be associated with a higher risk of heightened E. coli contamination, according to a model that was fitted to assess the probability of detecting a higher E. coli count in connection to environmental parameters. This outcome could be explained by the discharge density near the coast as well as the increased availability of coliforms, particularly E. coli, and nutrients during periods of heavier rainfall.

Selective laser melting of a novel 13Ni400 maraging steel: Material characterization and process optimization

Selective laser melting (SLM) has attracted recent attention in building parts with improved functionality and properties. Accordingly, the present work attempts to fabricate a novel 13Ni400 maraging steel parts with maximum theoretical density by SLM. A Box Behnken Design response surface methodology (RSM) approach is used to evaluate the influence of critical process parameters (laser power, laser scan speed, layer thickness, and hatch spacing) on the relative density, micro hardness, surface roughness, and tensile strength. Both the powder and the fabricated parts were characterized for the structural and microstructural features using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The influences of energy density and other process variables are explored through careful parametric studies and 3-D surface plots. Analysis of variance (ANOVA) is carried out, which reveals that the laser power and layer thickness are the most dominant process parameters impacting the performance of the SLM process. A revolutionary preference ranking organization technique for enrichment evaluation (PROMETHEE) is adopted to convert the multiple responses into an equivalent net outranking flow and rank the alternatives. The PROMETHEE-based outcomes are further improved by using a cuckoo search (CS) algorithm. A confirmatory test is conducted on the optimum build conditions obtained by the hybrid methodology (combination of PROMETHEE and Cuckoo Search) to validate the proposed work. It is seen that the value of net outranking flow is enriched by ∼5 %. This work is proficient in producing defect-free parts, with maximum densification and with improved mechanical properties for a newly developed 13Ni-400 maraging steel.

Mengupas Kemiskinan di Provinsi Banten: Bagaimanakah Peran Faktor Kependudukan dan Ekonomi?

This study aims to analyze the simultaneous and partial effects of population and economic factors on poverty in Banten Province for the 2011-2019 period. Population factors include population growth rate, population density, and sex ratio. Meanwhile, economic factors cover the open unemployment rate, HDI, and GRDP. With secondary data from the publication page of Statistics Indonesia in Banten Province, this research was conducted using a descriptive quantitative approach. To analyze the data, the study used panel data regression analysis. The econometric model was estimated using the Ridge Regression model to overcome the multicollinearity problem between variables in the study. The statistical test results showed that the variables of population growth rate, open unemployment rate, sex ratio, human development index, and GRDP were reported to simultaneously and significantly affect poverty in Banten Province during 2011-2019. Partially, several variables, such as population growth rate, open unemployment rate, and HDI each had a significant negative effect on poverty. Interestingly, other variables, like the sex ratio, had a significant positive effect on poverty. The variables of population density and Gross Regional Domestic Product (GRDP) did not affect poverty. This study indicated that to reduce poverty, the Banten Provincial government should focus on improving the quality of human resources. They should improve health, education, skills, and expertise. Thus, people can have the competence to compete and obtain better jobs, which in turn can increase their income and welfare. In this way, they are expected to get out of the poverty cycle.

Impact of Different Oil Extraction Techniques on the Physicochemical Properties of Adansonia digitata Seed.

The seeds of baobab were found to have both industrial and domestic uses due to their essential oil qualities for topical medication. However, the seeds found in this study area in Ghana are underutilised and sometimes thrown away after being taken off the pulp. The present study is aimed at examining the impact of the two predominant techniques used for oil extraction from nonoily seeds, namely, mechanical extraction and Soxhlet (n-hexane) extraction, on both the oil yield and physicochemical properties of crude oil derived from baobab seeds. The study looked at the iodine value, peroxide value, acid value, colour, density, and other variables. Refractometers, chroma meters, and titration techniques were used for the determination of specific properties using standard methods. The Soxhlet method of oil extraction was superior in terms of maximum oil recovery, recording a value of 27.75%, in contrast to the mechanical method, which yielded a significantly lower recovery rate of 5.422%. The peroxide and iodine values were found to be 15.09 and 11.89 mEq/g and 85.89 and 88.45 g/100 g for the mechanical and Soxhlet extraction methods, respectively. Statistically significant differences (p ≤ 0.05) were observed between the two oil extraction methods in some of the properties measured. The study discussed the impact of these oil properties on the application of both food and nonfood products. Finally, the study has provided an essential set of data and information to enable product initiators in the cosmetic, food, and other industries to make informed decisions regarding the utilisation of baobab oil as a constituent in the formulation of products.

Tobacco retailer density and smoking behaviour: how are exposure and outcome measures classified? A systematic review

IntroductionTo date only a limited number of reviews have focused on how exposure and outcome measures are defined in the existing literature on associations between tobacco retailer density (‘density’) and smoking behaviour (‘smoking’). Therefore this systematic review classified and summarised how both density and smoking variables are operationalised in the existing literature, and provides several methodological recommendations for future density and smoking research.MethodsTwo literature searches between March and April 2018 and April 2022 were conducted across 10 databases. Inclusion and exclusion criteria were developed and keyword database searches were undertaken. Studies were imported into Covidence. Cross-sectional studies that met the inclusion criteria were extracted and a quality assessment was undertaken. Studies were categorised according to the density measure used, and smoking was re-categorised using a modified classification tool.ResultsLarge heterogeneity was found in the operationalisation of both measures in the 47 studies included for analysis. Density was most commonly measured directly from geocoded locations using circular buffers at various distances (n = 14). After smoking was reclassified using a smoking classification tool, past-month smoking was the most common smoking type reported (n = 26).ConclusionsIt is recommended that density is measured through length-distance and travel time using the street network and weighted (e.g. by the size of an area), or by using Kernel Density Estimates as these methods provide a more accurate measure of geographical to tobacco and e-cigarette retailer density. The consistent application of a smoking measures classification tool, such as the one developed for this systematic review, would enable better comparisons between studies. Future research should measure exposure and outcome measures in a way that makes them comparable with other studies.ImplicationsThis systematic review provides a strong case for improving data collection and analysis methodologies in studies assessing tobacco retailer density and smoking behaviour to ensure that both exposure and outcome measures are clearly defined and captured. As large heterogeneity was found in the operationalisation of both density and smoking behaviour measures in the studies included for analysis, there is a need for future studies to capture, measure and classify exposure measures accurately, and to define outcome measures in a manner that makes them comparable with other studies.

Strength constrained topology optimization of hyperealstic structures with large deformation-induced frictionless contact

This paper developed a strength constrained topology optimization method for hyperelastic structures with large deformation-induced frictionless contact. The Neo-Hookean hyperelastic constitutive equation is adopted as the material model that incorporates both material and geometric nonlinearity. The large deforming contact is described by the node-to-segment algorithm. The topology optimization model is developed under the SIMP framework. Given the SIMP-related fictitious domain, we develop a nodal variable-based interpolation scheme to build smooth correlation between the contact force and nodal density variables, thus enabling the smooth transition and variation of contact conditions. Moreover, to guarantee the structure strength, local strain energy constraints are formulated and aggregated by the P-norm function. The details of sensitivity analysis are explicitly explained. At last, several benchmark examples are conducted that validate the proposed method.

Urban classification of the built-up and seasonal variations in vegetation: A framework integrating multisource datasets

The growing emphasis on integrating natural elements into urban environments to counteract adverse impacts has increased research into the role of vegetation within cities. Nonetheless, the inclusion of vegetation in urban classifications remains limited due to the associated challenges, such as time and cost constraints related to its measurement. This study introduces a classification framework that integrates spatio-temporal vegetation characteristics and built-up density variables at the neighbourhood scale using open-access datasets and remote sensing for data retrieval. Through a combination of statistical and spatial autocorrelation analyses and the application of two distinct classification methods to the 15 assessed variables, we identified four primary urban clusters. These clusters are further refined considering vegetation categories, which encompass general vegetation cover, vegetation cover levels, and vegetation cover changes tracked across two different seasons, corresponding to winter and summer. This comprehensive classification not only characterizes the built-up elements but also elucidates the distribution of vegetation showing the nuances in vegetation within similar urban clusters. The resulting classifications aim to bridge the existing gap in urban studies by incorporating the spatio-temporal scale and cover changes of vegetation. This framework serves as a precedent for creating context-specific classifications, which can be subsequently used for conducting further assessments on various urban issues. The outcomes of this study offer an overview of a study area, encompassing urban density and seasonal variations in vegetation. This information facilitates the identification of specific areas where additional attention may be warranted, particularly concerning the provision of ecosystem services and the development of strategies to enhance urban microclimates and thermal comfort, among other aspects.

Environmental factors and prey availability determine wintering habitat use by shorebirds along the west coast of India.

The spatial and temporal factors governing shorebird habitat use are crucial for managing coastal habitats and halting the decline of shorebird populations in the Central Asian Flyway. Therefore, we investigated how environmental variables and prey availability influenced shorebird distribution and abundance across habitats and seasons along the west coast of India between January 2015 and December 2016. Systematic sampling design was followed to collect data on shorebirds, sediment and hydrological properties (organic matter and physico-chemical properties), and prey availability across habitats over different seasons. Prey density and environmental variables such as salinity, organic matter, and sediment moisture content differed significantly across habitats and seasons. Prey density was influenced by salinity, with higher densities in mudflats (>1000 individuals per m2) during the winter season. Prey density decreased considerably in all coastal habitats during the departure (748.45 ± 320.93) and breeding seasons (537.55 ± 342.29). The fluctuations in prey density and salinity levels had a strong influence on distribution and abundance of shorebirds. These findings highlight the importance of mudflats as a foraging ground during the winter and freshwater inflow in maintaining salinity in estuarine habitats. Therefore, any alteration of river flow (e.g., construction of dams and check dams) or mudflats (e.g., mangrove plantations) would have a serious impact on the availability of prey organisms and the population of shorebirds that depend on them along the Central Asian Flyway.

How do density, employment and transit affect the prevalence of COVID-19 pandemic? A study of 3,141 counties across the United States

Previous research has explored the effect of the built environment on the spread of the coronavirus disease (COVID-19) pandemic. This study extends the existing literature by examining the relationship between pandemic prevalence and density, employment, and transit factors at the county level. Using multilinear spatial-lag regressions and time series clustering analyses on the Smart Location Database encompassing 3141 counties in the United States, our findings reveal the following: (1) Density, employment, and transit variables yield heterogeneous effects to infection rate, death rate, and mortality rate. (2) Pedestrian-oriented road density is positively correlated to the prevalence of COVID-19, every 0.011 miles/acre increase is associated with 1% increase in the infection rate. (3) A consistent negative correlation is observed between jobs per household and infection rate, while a decrease in unemployment rate leads to an increase in the death rate. (4) The results from time series analysis suggest that areas characterized by low auto-oriented intersection density but high pedestrian-oriented road density are more susceptible to the impacts of pandemics. This highlights the need to prioritize pandemic prevention efforts in the suburban and rural areas with low population density, as emphasized in existing literature emphasized.

The Effect of Changes in Land Cover and Vegetation Density on Urban Heat Island in Semarang City

The urbanization process can be seen not only as influenced by increasing population growth but also the phenomenon of urbanization. The city of Semarang from 1999 to 2019 saw an increase of half a million people with a total population of around 1.81 million people. Along with population growth that occurs, land conversion to meet the needs of life often clashes with the presence of vegetated land. As a result, the area ofvegetated land slowly decreases. On the other hand, the massive build-up of this area makes it easier to reflect and absorb solar heat. As a result, the average surface temperature of the city gradually rises which causes the formation of hot spots that cause changes in climate and weather elements, thus triggering the formation of an Urban Heat Island (UHI). The increase in temperature in urban areas affects not only the comfort of cities but also the health of urban communities, which will impact various city line activities. This urban heat island study, related to changes in land use in Semarang, is urgently needed to make wiser spatial planning decisions. In line with the problems above, this study is aimed at analyzing the effect of changes in land cover and vegetation density on the area of Urban Heat Island (UHI) in Semarang City. The approach used is forecasting with multiple regression analysis methods. Sources of data used are secondary data and population data. The data used is time series data. Based on the statistical analysis results indicate that the variables of land cover and vegetation density have a significant influence on the distribution of surface temperature. The land cover component has a positive effect while the vegetation density component harms the surface temperature distribution area. The appearance of the trendline results in an increasing area of surface temperature distribution in 2030 with 3 scenarios, namely, pessimistic, moderate, and optimistic. The preparation of a planning scenario in which an optimistic scenario can be adopted by the government so that the area of high urban surface temperatures does not expand and have an impact on the level of community vulnerability to extreme weather.

Mapping Socio-Economic Vulnerability to Rob Flood Hazards in Coastal Cities, North Pekalongan District, Pekalongan City

Climate change brings danger to several areas, especially in coastal urban areas. One of them is the tidal flood which experienced inundation. Tidal floods pose a serious threat to the sustainability of social life and economic growth. Assessment of social and economic vulnerabilities is needed to overcome the risk of disaster hazards due to climate change in the form of coastal tidal floods in cities. This research is expected to be able to describe socio-economic vulnerability through the variables of population density, age, gender, occupation, and level of education to tidal floods that have occurred in 42% of the area. The research method used is quantitative analysis, scoring, and geographic information system modeling with village analysis units. The results showed that Panjang Baru Village was the most vulnerable area because of the high density and low-income levels of the people, most of whom were fishermen and farmers households. It also indicates the contribution of population density, level of education, and employment to the level of vulnerability. This study states that the socio-economic aspect is an important factor that must be considered for the sustainability of life and community adaptation to the threat of climate change, especially tidal floods.

AK-SEUR: An adaptive Kriging-based learning function for structural reliability analysis through sample-based expected uncertainty reduction

Reliability Analysis (RA) is a critical aspect of structural design and performance evaluation aiming to determine the probability of structural failure under given random input parameters. With modern development of modeling techniques, computational models have achieved higher fidelity but at the increased cost of computational time, which poses a significant challenge for RA. Consequently, surrogate model-assisted RA has been explored as a means of improved efficiency and accuracy. This study proposes a novel learning function, Sample-based Expected Uncertainty Reduction (SEUR), for surrogate model-assisted RA. The SEUR function uses statistical information from the metamodeling with fixed hyper-parameters to construct expected failure probability bounds to sequentially update the design of experiment (DoE). The joint probability densities of input variables are accounted for through simulation methods, including Monte Carlo (MC) and subset simulation (SS). Furthermore, the discrete simulated annealing algorithm is used to search for the optimal design point. The performance of proposed AK-SEUR function is systematically evaluated using six examples of different dimensions, failure probability levels and nonlinearities. The AK-SEUR function is demonstrated to be more effective and efficient than other popular active learning methods in dealing with nonlinear performance functions, small probabilities, and complex limit states. The proposed SEUR function has the potential to improve the efficiency and accuracy of RA, particularly in situations where computational models are time-consuming and the search for the optimal solution is challenging.

Assessment of short- to medium-term impacts of bench terrace construction on soil water repellency in north-central Portugal

Agrarian terraces are surely recognized as a traditional soil and water conservation technique, however the use of these methods in forestry are poorly studied, especially the hydrological impacts of bench terracing for forest plantations. The employment of heavy machinery in forests have been described to increase soil bulk density and compaction which might reduce soil water infiltration capacity, and thus, increase runoff generation. However, in the case of terraces, the flattening of the terrain may increase the infiltration and re-infiltration of runoff due to consecutive slope discontinuity. The present study assesses the short to medium-term impacts of bench terrace construction on soil water repellency and soil water infiltration in eucalypt forest plantations. A chrono-sequence approach was used to analyse a time series of sites terraced at different periods with neighbouring mature long-undisturbed sites. Therefore, Methanol droplet test was employed in-situ in four different periods of time-since-terracing (0, 5, 10 and 17 years after terracing). Three pairs of nearby terraced and non-terraced eucalypt plantations were studied for each period, counting a total of 24 study sites. Our results revealed clear differences in SWR between terraced and non-terraced eucalypt plantations, with all non-terraced sites showing extreme SWR values while at the terraced sites highly variable values were found. In addition, the median SWR increase with time elapsed since terrace construction, i.e. from very wettable immediately and 5 years after terracing, and increase to strong and moderate water repellent at 10 and 17 years following terracing. The infiltration variables were observed inversely correlated with SWR following terrace construction and were watched to decrease with time-since-terracing. The litter and the Oh humified layer were found positively correlated to the SWR as well as the stone and bulk density variables, while the percentage of organic matter and the soil moisture content in the soil were poorly correlated.

An enhanced proportional topology optimization with virtual elements: Formulation and numerical implementation

This paper presents an improved non-sensitivity structural topology optimization method incorporating virtual elements with unstructured polygonal meshes. Specifically, we employ the recently developed gradient-free proportional topology optimization (PTO) approach, for the first time, together with a new material distribution formula suitable for both minimum compliance and compliant mechanism problems. In order to improve performance, we integrate a linear virtual element method (VEM) module into the PTO algorithm. The linear VEM has a desirable characteristic: it does not require numerical integration and, more importantly, is less sensitive to small-edge elements, thus, significantly reducing computational time. Additionally, we utilize virtual elements with unstructured polygonal meshes inside PTO to suppress one-node connection instabilities. Furthermore, the Heaviside-type operator in the main PTO algorithm loop enhances the optimized results by encouraging the density variables to approach discrete (0/1) solutions more effectively. We demonstrate the performance of our developed method in terms of computational speed, diversity of applications, and improved black-and-white (0/1) structures through several benchmark examples of compliance and compliant mechanism designs.

Benefits for cardiovascular system, bone density, and quality of life of a long-term hormone therapy in hysterectomized women: a 20-year follow-up study.

The safety, consequences, and dosage of long-term hormone therapy (HT) for postmenopausal women remain unclear. Our aim was to analyze the effects of HT after 20 years of therapy in women after hysterectomy, focusing on the symptoms of menopause, blood pressure, lipid profiles, and bone density. A prospective observational longitudinal study was designed. The initial transdermal estradiol dose was reduced in half (0.025 mg/d) at 60 years of age. Different parameters including demographic, cardiovascular, bone density, and metabolic variables, as well as quality of life characteristics, were analyzed using bivariate analyses. Multivariate generalized estimating equations for longitudinal data were fitted for differences over time and between doses (<60 vs ≥60 y) using the R package geepack. After 20 years of HT, the mean age of 56 studied hysterectomized women was 67.1 years. The mean Kupperman index score decreased from 26.7 to 12.0 ( P < 0.001). A trend with total and low-density lipoprotein cholesterol reduction and high-density lipoprotein cholesterol increase was observed over time. A decrease in very-low-density lipoprotein cholesterol ( P = 0.05) and an increase in T score vertebral densitometry ( P = 0.014) were detected after HT. No changes in health outcome were detected in women older than 60 years with the reduced dose of HT. Breast cancer was the reason for dropouts in 0.02% women. HT for up to 20 years after hysterectomy may be beneficial for bone and cardiovascular health and for the overall quality of life. Our data suggest the importance of evaluating the dose and the timing of HT.

Defence-related components in cucumber susceptibility to target spot

Target spot is an important disease in cucumber culture. Due to differences in the susceptibility of cucumber cultivars to the disease, the objective was to evaluate the behavior of three cvs. in terms of leaf trichome density and biochemical variables in the interaction with the pathogen Corynespora cassiicola. The density of trichomes was evaluated on both sides of the leaves. The activity of peroxidase and polyphenol oxidase enzymes and the levels of free and bound phenolic compounds were evaluated one, three and five days after inoculation or not with the pathogen. The enzymatic activity was higher in the Safira cv., less susceptible to the disease, in relation to the Taiko and Soldier cvs. Inoculated plants showed higher peroxidase activity, showing that the response to infection was accompanied by the synthesis of this enzyme, and it increased with the days after inoculation. The levels of phenolic compounds varied according to the cvs. and as a function of time, with the highest levels in the Safira and Soldier cvs. Higher density of trichomes was found in the Safira cv., with no differences between Soldier and Taiko cvs. The adaxial side of the leaves had a greater number of trichomes than the abaxial side. No direct relationships were observed between biochemical and trichome variables and disease severity in cucumber cvs., since the Soldier cv., the most susceptible to the disease, did not differ in relation to 'Taiko' in enzymatic activities, free phenolic compounds and number of trichomes, including higher levels of bound phenolic compounds.

Tree Health Condition in Urban Green Areas Assessed through Crown Indicators and Vegetation Indices

The urban environment induces stress on trees and its impact can be identified by observing the condition of the crown. The aim of this study is to correlate the variables of crown density (Cdn), crown transparency (Ctr) and dieback (Cdie) with the following vegetation indices: the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), blue-normalized difference vegetation index (BNDVI), green-normalized difference vegetation index (GNDVI), green–red vegetation index (GRVI) and red–green–blue vegetation index (RGBVI) of the crowns of trees located in urban green areas, as well as chlorophyll fluorescence (Fv/Fm) as an indirect indicator of the overall tree health condition. A total of 549 trees were evaluated, represented in 24 families, 36 genera and 53 species; the variables had average values of 67.96% for Cdn, 35.19% for Ctr and 1% for Cdie. Correlations were found between Fv/Fm, NDVI and BNDVI. NDVI and BNDVI correlated with variables such as Cdn and Ctr, mainly in species such as Ligustrum lucidum, Jacaranda mimosifolia and Fraxinus uhdei. Therefore, it is possible to evaluate the tree health condition of trees in urban green environments through the identification of unfavorable conditions at the crown level by using vegetation indices for some of the species studied.

Optimisation of compressive strength of foamed concrete with a novel Aspergillus iizukae EAN605 fungus

The production of concrete by incorporating a microorganism has emerged as a promising research area, offering potential benefits such as reduce carbon footprint, enhance durability and increased strength. The present study reported for the first time using a fungal strain (Aspergillus iizukae EAN605) in biocementation. The study aims to investigate the effectiveness of incorporating Aspergillus iizukae EAN 605 into foam concrete to improve its performance, particularly its strength. The study employs the response surface methodology (RSM) to explore the relationship between density, microorganism concentration and water /cement ratio (w/c) and their effects on compressive strength. Through a series of experiments,the highest recorded compressive strength was achieved with a density of 1800 kg/m3, w/c ratio of 0.5, and Aspergillus iizukae EAN605 concentration of 0.5 g/l, resulting in a remarkable 37.5 % increase compared to foam concrete (FC). The variables of density, A. iizukae EAN 605 and their interaction density*fungi (D*F) significantly impacted compressive strength, with p-values of 0.000, 0.016, and 0.010, respectively.X-ray diffraction (XRD) analysis was employed to identify the crystalline composition of the precipitates formed on the fungal hyphae, providing insights into the mineralogical transformations occurring during the biocementation process. Additionally, scanning electron microscope (SEM) imaging was utilised to visualise the morphology and distribution of the calcite crystals, further supporting the evidence of fungal-mediated mineral precipitation in foam concrete. The findings of this study hold significant implications for the concrete industry, as the incorporation of Aspergillus iizukae EAN605 in foam concrete offers a sustainable solution to enhance compressive strength and contribute to environmental friendly construction practices. This study provides valuable insights for future research and practical applications in the field of bio-foamed concrete (B-FC).

Fuzzy‐based unequal clustering protocol for underwater wireless sensor networks

SummaryUnderwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy‐based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi‐hop and inter‐cluster routing. The FBUCP is compared with the LEACH‐UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH‐UWSN, CDBR, and FBCA.

Rotational grazing with cattle‐free zones supports the coexistence of cattle and wild herbivores in African rangelands

Abstract African wildlife populations are declining at an alarming rate. To stop further population declines and restore ecosystems, more areas for wildlife are needed. Community‐based conservation with wildlife‐livestock coexistence in the vast rangelands of Africa presents a major opportunity. However, the efficacy of wildlife conservation in mixed land‐use areas remains an outstanding question. To assess the ecological outcomes of land‐sharing between regulated livestock herds and wildlife populations in African savannas, we test how rotational cattle grazing affects spatiotemporal dynamics of 15 large herbivore species in the Maasai Mara, Kenya. First, we tested how wild herbivore distributions across the Greater Mara Ecosystem (the Mara, ~2600 km2) are related to cattle density and environmental variables using 584,561 observations of wild herbivores (ecosystem scale). In a second analysis, we tested how rotational cattle grazing affects wild herbivore distributions in a 300 km2 subsection of the Mara using 30,583 observations (landscape scale). Finally, we tested how functional traits of wild herbivores affect species‐level spatiotemporal responses to cattle grazing. At the ecosystem scale, the presence of five wild herbivore species was positively correlated with cattle density, while cattle effects on wild herbivore abundances were species‐dependent with both increases and decreases. At the landscape scale, rotational cattle grazing strongly impacted the spatiotemporal habitat selection of wild herbivores, resulting in distinct lag periods with which different species are attracted to areas previously grazed by cattle. These lag periods were linked to functional traits, with body mass and herd size explaining 35% of the interspecific differences. Small to medium‐sized herbivores with large herds select areas recently grazed by cattle, whereas large species with large herd sizes and small species with small herd sizes avoid recently grazed areas. Synthesis and applications: Our results revealed that the effect of cattle on wild herbivores varies considerably among species, suggesting that cattle‐wildlife interactions range from facilitation to competition. To maintain species that strongly avoid cattle, designated livestock‐free zones remain essential, also in rotational grazing systems. Rotational grazing systems with regulated livestock densities present an important opportunity to better manage wildlife‐livestock coexistence and thus improve wildlife conservation in African rangelands.