Search

AbstractUnsheltered homelessness is associated with a myriad of barriers including unmet medical, mental health, physical, and social needs. This study evaluated a Street Medicine approach to examine and reduce the complex barriers to care by providing coordinated mobile services. Participants were urban adults with mental health, substance use, or co-occurring issues who were experiencing unsheltered homelessness. Services provided were integrated, person-centered, and trauma-informed based on participants’ needs. The range of offered services included psychiatric and medical care, case management, housing support, mental health, and substance abuse treatment, as well as a variety of supportive services. Structured baseline interviews (N = 295) and 6-month follow-ups (N = 118) were conducted, and a range of outcomes were examined including quality of life, behavioral and physical health indicators, substance use, and recovery domains. Using a bivariate analysis approach, promising results were seen at follow-up including improved quality of life, reduced PTSD symptom severity, reduced substance use, and reduced risk behavior. Several significant interactions were also discovered including the impact of housing status on quality of life and recovery. Race and gender differences were examined and improvement across outcomes differed by race/ethnicity. The results suggest that mobile services targeting unsheltered persons are viable options towards improved health, health equity, and quality of life. Further research should continue to evaluate interventions and ways to reduce stigma, discrimination, and barriers to treatment for unsheltered persons experiencing homelessness.

By increasing resource heterogeneity, mistletoe-infected trees can restructure plant community processes and distribution patterns. No information is available on how mistletoe-infected Vachellia (Acacia) karroo trees within V. karroo dominated stands are spatially distributed, and on how they influence the spatial patterns of their surrounding conspecifics and heterospecifics. Each woody plant was stem mapped using a cartesian plane (x, y) within three 50×50 m plots located in V. karroo dominated stands in a semi-arid savanna, South West Zimbabwe. Pair correlations g(r) were used for the univariate analysis and Poisson process null models were applied to quantify and detect overall departure from randomness. For the bivariate analysis, pair correlations g12(r) under the null model of independence were used, whilst the mark correlation function (kmm(r)) was used to analyse the correlation of tree canopy area and mistletoe infection intensity. For each plot, size class distributions, based on tree height and basal stem diameter displayed negative J curves, with steep negative regression slopes across the size classes, clearly indicating a strongly recruiting population of V. karroo. The univariate patterns of all trees (infected and non-infected) were consistent with a random pattern, which is attributed to unsystematic mistletoe seed dispersal by birds. The univariate analysis of all woody plants (adults and juveniles) exhibited aggregation at small spatial scales due to the high abundance of clustered seedlings and saplings. At small spatial scales, understory woody plants (both conspecifics and non-conspecifics) were positively associated with mistletoe-infected trees due to mistletoephily which is the facilitation (or nurse protégé interactions) within the more resource-rich mistletoe-infected tree subcanopies. These results provide strong evidence suggesting that the variations in spatial pattern modification by mistletoe-infected trees could further increase spatial heterogeneity in this semi-arid savanna. As such, by increasing heterogeneity, mistletoe-infected trees can increase the resilience of semi-arid savannas in the face of perturbations and stochastic events.

Abstract Global warming increases the atmospheric water‐holding capacity, consequently altering the frequency, and intensity of extreme hydrological events. River floods characterized by large peak flow or prolonged duration can amplify the risk of social disruption and affect ecosystem stability. However, previous studies have mostly focused on univariate flood magnitude characteristics, such as flood peak or volume, and there is still limited understanding of how these joint flood characteristics (i.e., magnitude and duration) might co‐evolve under different warming levels. Here, we develop a systematical bivariate framework to project future flood risk in 11,528 catchments across the globe. By constructing the joint distribution of flood peak and duration with copulas, we examine global flood risk with a bivariate framework under varying levels of global warming (i.e., within a range of 1.5–3.0°C above pre‐industrial levels). The flood projections are produced by driving five calibrated lumped hydrological models (HMs) using the simulations with bias adjustment of five global climate models (GCMs) under three shared socioeconomic pathways (SSP126, SSP370, and SSP585). On average, global warming from 1.5 to 3.0°C tends to amplify flood peak and lengthen flood duration across almost all continents, but changes are not unidirectional and vary regionally around the globe. The joint return period (JRP) of the historical (1985–2014) 50‐year flood event is projected to decrease to a median with 36 years under a medium emission pathway at the 1.5°C warming level. Finally, we evaluate the drivers of these JRP changes in the future climate and quantify the uncertainty arising from the different GCMs, SSPs, and HMs. Our findings highlight the importance of limiting greenhouse gas emission to slow down global warming and developing climate adaptation strategies to address future flood hazards.

Species distribution modelling based on bioclimatic variables to understand habitat suitability and changes in range dominates studies on the spatial distribution of baobabs, which limits our understanding of how the small-scale plant–plant interactions influence the spatial point pattern of this keystone species in semi-arid regions of sub-Saharan Africa. Here, we investigated the spatial distribution of the baobab in two protected areas, Chipinge Safari Area (CSA) and Save Valley Conservancy (SVC) which lie in the semi-arid Southeastern lowveld of Zimbabwe. CSA was previously a sparsely human populated area before its proclamation as a protected area, has a small number of herbivores and baboons, and has no elephants, while SVC has a high density of elephants (1.5 km−2) and large number of herbivores. At each site, 1 km2 plots, SVC (n = 4) and CSA (n = 3), were established for spatial analysis. In each plot, we recorded the spatial location, elevation, height, diameter at breast height, and canopy cover of each baobab. Spatial point-pattern was assessed using both the inhomogeneous transformed L-function for Ripley's K-function and the pair-correlation function. Baobabs in SVC were larger (height, canopy cover, and basal area) relative to those in CSA. At both sites, baobabs were clustered at small spatial scale (0–50 m), indicating that competition was insufficient to cause density-dependent thinning that can lead to even distribution as we expected. The distribution of small baobabs was independent of large baobabs, which reflects the importance of other environmental factors such as site conditions and seed dispersal rather than nurse-protégé on seedling establishment. The random distribution pattern of adult baobabs could be the legacy effects of these random factors and processes at establishment. Overall, our study shows that the distribution of baobabs is not dependent on local plant–plant interactions, but most likely from larger scale random pattern forming factors and processes such as seed dispersal and environmental heterogeneity.

Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production. LSB is inherently a categorical trait and should be analysed with threshold models. Objective: Bayesian threshold models were used to analyze sheep LSB to estimate genetic parameters. Methods: Data was based on 7,901 LSB records from 14,968 dams and 682 sires collected from 1986 to 2012 at Makouie Sheep Breeding Station in Iran. Means of posterior distributions (MPDs) of LSB's genetic parameters were estimated, and the best-fitted models were selected using the deviance information criterion. Results: In the repeated measurement analysis, the estimated direct and maternal heritabilities, and permanent environmental effect (±SE), according to the best-fitted model (model 5), were 0.01 (0.010), 0.02 (0.014), and 0.01 (0.011), respectively. In the univariate analysis, the best estimates of direct and maternal heritabilities were 0.12 (0.064) and 0.08 (0.045), respectively. An increasing trend for direct and maternal heritabilities was observed in parity 2 (0.15 (0.082) and 0.25 (0.083), respectively). In the bivariate analysis, the best estimates of direct and maternal heritabilities for LSB were 0.03 (0.027) and 0.22 (0.041), respectively. The direct and maternal genetic correlations among parities were 0.25 (0.054) and 0.12 (0.021), respectively. Conclusions: The results showed a considerable influence of environmental factors on LSB in each parity of sheep; also, statistically different genetic parameters (p

Installation of a biogas plant in a rural region has become a viable alternative energy source with a variety of health and environmental advantages. Though Bangladesh has enormous resources for biogas production, biogas energy production is infancy stage in Bangladesh. The study aims to explore the economic aspect of household-level biogas plants and determine the relationship between biogas plant functionality and different factors. For doing this, 300 biogas plant owners were interviewed from fifteen Upazilla in Bangladesh and respondents were chosen by a two-stage random sampling technique. The study shows by measuring partial budgeting, USD 294.80 per year can be earned by a family by introducing biogas plant. Cost-benefit analysis showed that a small biogas plant (USD 143.07/year) was most profitable, followed by a large biogas plant (USD 142.17/year). In discounted cost-benefit analysis, medium size biogas plant was found to be the most beneficial investment, followed by a small size biogas plant. Average NPV, BCR, PBP, and IRR of Biogas plant were USD 1629.11, 1.77, 2.93, and 48% with subsidy where USD 1525.25, 1.77, 3.75, and 43% without subsidy. The measurement of carbon trading also highlights the economic benefit of a biogas plant in Bangladesh. The bivariate relationship between the functionality of biogas plants with different factors highlights that higher educated, trained plant owners with quality mason and follow up services ensured the efficient operation of the biogas plant.

In hydrological practice, individual elements of the hydrological cycle are most often estimated and evaluated separately. Uncertainty in the size estimation of extrema discharges and their return period can affect the statistical assessment of the significance of floods. One example is the simultaneous occurrence and joining of extremes at the confluence of rivers. The paper dealt with the statistical evaluation of the occurrence of two independent variables and their joint probabilities of occurrence. Bivariate joint analysis is a statistical approach for the assessment of flood threats at the confluence of rivers. In our study, the annual maximum discharges monitored on four selected Slovak rivers and their tributaries represent the analyzed variables. The Archimedean class of copula functions was used as a set of mathematical tools for the determination and evaluation of the joint probability of annual maximal discharges at river confluences. The results of such analysis can contribute to a more reliable assessment of flood threats, especially in cases where extreme discharges occur simultaneously, increasing the risk of devastating effects. Finally, the designed discharges of the different return periods calculated by using the univariate approach and the bivariate approach for the gauging station below the confluence of the rivers was evaluated and compared.

Hydrological dam safety analyses should assess the frequency curve of maximum reservoir water levels in flood events by routing a large set of inflow hydrographs. Therefore, stochastic bivariate analyses are used. Hydrograph shapes obtained by using hydrometeorological simulations are required for each flood peak-hydrograph volume pair. Hydrograph shapes depend on hyetograph shapes. A sensitivity analysis is required to select the appropriate hyetograph shape, focusing on the influence of the hyetograph time step on the hydrograph shape. In this study, the Cuerda del Pozo Dam in central Spain is selected as a case study.

Background and Aim: Brucellosis is an important zoonotic disease that affects fertility in farm animals. The risk factors of brucellosis have not been well studied. This study aimed to understand the seroprevalence and risk factors of brucellosis among livestock in Bangriposi block of Mayurbhanj district in Odisha, a region that borders Similipal wildlife reserve. Materials and Methods: Rose Bengal plate test (RBPT) was carried out to estimate the seroprevalence of the livestock in this region. Bivariate analysis was carried out to analyze the association between the variables and brucellosis. Binary logistic regression was performed to assess the risk factors associated with brucellosis in the livestock. Results: Based on RBPT, the seroprevalence of brucellosis among cattle and goats was estimated to be 1.1% and 11.2%, respectively. Binary logistic regression analysis indicates that study area, age, goats, animals with a history of abortion, and rearing practices were the major risk factors in this region. Conclusion: This is one of the first studies in India to shed light on risk factors of brucellosis, an important neglected disease that affects the health of animals and humans and nation's economy.

The performance of a suspension system is affected by the behavior and posture of its components. However, published studies usually conduct this research using the based-equivalent model without considering the characteristic curves or postures. In this paper, an improved ride comfort model that considers three nonlinearities in suspensions is first developed, and this model is validated through experimental results and demonstrates good accuracy. Then, the dynamic response is presented to investigate the effects of multilevel suspension parameters and nonlinear factors on ride comfort, and it is concluded that the front chassis suspension is the most significant system for ride comfort. Next, a multivariable co-optimization method based on the improved model is proposed to obtain more accurate optimized results that are more suitable for automotive applications. Subsequently, a multiobjective genetic algorithm (MGA) is applied to obtain the Pareto solution set. Furthermore, comparing the RMS value before and after optimization shows an obvious reduction, with averages of 19.7%, 17.8%, and 12.0% for the weighted root mean square (RMS) of the driver seat acceleration and the RMS of the working spaces of the front chassis suspension and the rear chassis suspension, respectively. Finally, the results are also verified by experiments, indicating that the improved ride comfort model and the multivariable co-optimization method are feasible and practical.

A range of nutritional needs are met through the use of fortified farm-based foods. Wheat biorfortification with zinc is such an example where biorfortification is carried out for a crucial element like Zinc. Zinc-biofortified wheat (Zn-wheat) has been officially launched in Pakistan since 2016 but its wide-scale dissemination, adoption and consumption have not taken place till to date. On the other hand, essential nutrients deficiencies have wide-ranging implications for public health especially for children and lactating mothers. This study is undertaken to know the reasons for the slow progression of scaling up of biofortified wheat varieties in Pakistan, people’s awareness about biofortified wheat and to recognize the role of information in acceptance and willingness to pay for this wheat. For this purpose, randomly selected 474 households were interviewed from four districts of Punjab province. They were categorized into four groups based on their exposure to information in real and hypothetical cheap talk (game theory context). Study findings reveal that respondents were ready to pay for fortified wheat if they are aware about nutrient aspects and Zn deficiency. Using Discrete Choice Experiment, the preferences for and factors affecting the willingness to pay for fortified wheat are evaluated. Main factors having positive impact include household head’s education and income, having pregnant women and children

Grain size distribution and classes present in sedimentary rocks are responsive to the physical changes of the transporting media and the basin of deposition. Analyzing grain size data is germane in reconstructing the sedimentary processes including identifying the palaeoenvironment of deposition. Twenty-three (23) samples, mainly sandstones, collected within latitude 6 055’-6 059’N and Longitude 005 044’-005 053’E in the Anambra Basin, were subjected to granulometric analysis, where grain size parameters (mean grain size, sorting, skewness, and kurtosis) sensitive to environmental conditions were calculated. These parameters were integrated with bivariate and multivariate analyses. Graphics mean (Mz) in the study area range from 1.1 to 2.27 ɸ with an average value of 1.7 ɸ, suggesting that grains are predominantly fine to medium; sorting range from 0.71 to 1.36 ɸ with an average value of 1.02 ɸ, suggesting sediments are moderately sorted; skewness range from -0.57 to 0.51 ɸ with an average value of 1.28 ɸ suggesting coarsely skewed to fine skewed with a predominating near symmetrical skewness and kurtosis range from 0.57 to 1.51ɸ, with an average of 1.28 ɸ suggesting a very platykurtic to leptokurtic character. Bivariate scatter plots of the grains size parameters predicted the environment of deposition as a shallow marine. Multivariate analysis calculated from established functions suggested environments that range from the beach (backshore) to shallow marine (subtidal). The integration of the granulometric parameters, bivariate and multivariate plots predict an environment that is dominated by high energy indicating that the sediments of the study area were deposited in a shallow marine environment. In addition, the Visher and Passega’s C-M diagrams characterized the transport mechanism of the sediments as predominantly by saltation although traction and suspension modes also play some roles.

Although exercise-induced fatigue has been mostly studied from a reductionist and component-dominant approach, some authors have started to test the general predictions of theories of self-organized change during exercises performed until exhaustion. However, little is known about the effects of fatigue on interlimb coordination in quasi-isometric actions. The aim of this study was to investigate the effect of exercise-induced fatigue on upper interlimb coordination during a quasi-isometric exercise performed until exhaustion. In order to do this, we hypothesized an order parameter that governs the interlimb coordination as an interlimb correlation measure. In line with general predictions of theory of phase transitions, we expected that the locally averaged values of the order parameter will increase as the fatigue driven system approaches the point of spontaneous task disengagement. Seven participants performed a quasi-isometric task holding an Olympic bar maintaining an initial elbow flexion of 90 degrees until fatigue induced spontaneous task disengagement. The variability of the elbow angle was recorded through electrogoniometry and the obtained time series were divided into three segments for further analysis. Running correlation function (RCF) and adopted bivariate phase rectified signal averaging (BPRSA) were applied to the corresponding initial (30%) and last (30%) segments of the time series. The results of both analyses showed that the interlimb correlation increased between the initial and the final segments of the performed task. Hence, the hypothesis of the research was supported by evidence. The enhancement of the correlation in the last part means a less flexible coordination among limbs. Our results also show that the high magnitude correlation (%RCF > 0.8) and the %Range (END-BEG) may prove to be useful markers to detect the effects of effort accumulation on interlimb coordination. These results may provide information about the loss of adaptability during exercises performed until exhaustion. Finally, we briefly discuss the hypothesis of the inhibitory percolation process being the general explanation of the spontaneous task disengagement phenomenon.

The production environments of the German–Austrian Brown Swiss population show a wide range due to differences in topography, landscapes, local climates, and different farm management systems. Extensive production systems such as organic farming have become increasingly popular in recent decades because of interest in sustainability and consumer preferences. Compared with conventional farmers, organic farmers put more weight on fitness traits. Besides the official total merit index (TMI), a selection index applying relative economic weights (REWs) suitable for organic production systems is provided for Brown Swiss cattle in Germany. The aim of the study was to investigate genotype-by-environment interactions (GxE) for milk production traits and functional traits (including longevity, fertility traits, and calving traits) in a sample of the German–Austrian Brown Swiss population housed in Baden-Wuerttemberg (southern Germany) by applying bivariate and random regression sire models. For bivariate analyses, the production environment was binary classified by farm management system (organic and conventional) and altitude of farm location (above or below 800 m above sea level (ASL)). Milk energy yields (MEY) obtained from herd effects were used as continuously scaled environmental descriptor in the reaction norm approach. The TMIs for sires were calculated based on breeding values estimated with different models and environment-specific REWs to determine possible GxE at TMI levels and rerankings of sires. In bivariate analyses, genetic correlations at the trait level were high and ranged from rg = 0.99 (calving to first insemination, cystic ovaries, and maternal stillbirth rate) to rg = 0.79 (first insemination to conception for altitude). Except for the latter, no severe GxE were found at the trait level using the bivariate models. Fat yield was the only trait showing minor GxE in the reaction norm model approach. Investigating the environmental sensitivity at the TMI level revealed rank correlations between the different environment-specific TMIs that were close to unity, implying no severe reranking effects. The results show no need to account for different environments in Brown Swiss cattle breeding programs.

Over the last decades, the evaluation of hazards and risks associated with coastal flooding has become increasingly more important in order to protect population and assets. The general purpose of this research was to assess reliable coastal flooding hazard maps due to overflow and wave overtopping. This paper addresses the problem of defining credible joint statistics of significant wave heights Hs and water levels ζ, focusing on the selection of the sample pair that characterizes each sea storm, to evaluate the occurrence probability of extreme events. The pair is selected maximizing a spatial structure variable, i.e., a linear combination of Hs and ζ, specific to each point of the area at risk. The structure variable is defined by the sensitivity of the flooding process to Hs and ζ, as found by analyzing a set of inundation maps produced through a Simplified Shallow-Water numerical model (SSW). The proposed methodology is applied to a coastal stretch in the Venetian littoral (Italy), by means of a 30 year-long time series recorded at the “Acqua Alta” oceanographic research tower, located in the Northern Adriatic Sea in front of the Venetian lagoon. The critical combination of Hs and ζ forming the structure variable is presented in a map, and it can be related to the topography and the presence of mitigation measures. The return period associated with the two recent large storms that occurred in this area in 2018 and 2019 is also investigated. The proposed procedure gives credible occurrence probabilities for these events, whereas other approaches would consider them extremely unlikely.

Predicting anomalous emission of pollutants into the atmosphere well in advance is crucial for industries emitting such elements, since it allows them to take corrective measures aimed to avoid such emissions and their consequences. In this work, we propose a functional location-scale model to predict in advance pollution episodes where two pollutants are involved. Functional generalized additive models (FGAMs) are used to estimate the means and variances of the model, as well as the correlation between both pollutants. The method not only forecasts the concentrations of both pollutants, it also estimates an uncertainty region where the concentrations of both pollutants should be located, given a specific level of uncertainty. The performance of the model was evaluated using real data of SO 2 and NO x emissions from a coal-fired power station, obtaining good results.

In Romania, landslides together with the multitude geomorphological processes linked to them are some of the most common hazards which manifested in vulnerable areas with important human activities can induce many negative effects. From this perspective, identifying the areas affected by landslides, based on GIS spatial analysis models and statistical methods, is a subject frequently discussed in the national and international literature. This research was focused on the methods and practices of GIS spatial analysis, with a target of creating a complex model and a viable methodology of assessment the probability of occurrence of landslides, applicable within any territory. The study was based on the identification and analysis in a bivariate systemic manner of the numerous factors involved in the production of landslides, such as topography, morphology, hydrography, geological, lithology, weather, land use. The area in which the analysis has been conducted, The Metropolitan Area of Cluj-Napoca, was chosen due to the exacerbated urbanization of the recent years, coupled with a massive increase in the number of inhabitants, thus being a space of socioeconomic importance and a real challenge regarding spatial planning. Applying the model in this area has generated relatively good results, with a power of predictability of over 80%, measured in landslides sample areas used for the validation of the results, fact which attest the viability of the model and the fact that the model can be used in different areas with related morphometric and environmental characteristics.

A problem of today organizations is to adapt to rapid changes taking place in society, and this can not be donewithout giving special attention to human capital and intangible goods (knowledge, information, creativity). As thehuman factor plays an essential role in the economic growth strategy, making an investment in training leads to longtermprofitability growth. In order to strengthen the above, the paper presents an economic study related toprofessional development of the employees working within the National Forest Administration ROMSILVA, and theway in which selection was made in order to participate in these courses. In the analysis and interpretation of data wasused the chi-square test.

Flood frequency estimation for the design of hydraulic structures is usually performed as a univariate analysis of flood event magnitudes. However, recent studies show that for accurate return period estimation of the flood events, the dependence and the correlation pattern among flood attribute characteristics, such as peak discharge, volume and duration should be taken into account in a multivariate framework. The primary goal of this study is to compare univariate and joint bivariate return periods of floods that all rely on different probability concepts in Yermasoyia watershed, Cyprus. Pairs of peak discharge with corresponding flood volumes are estimated and compared using annual maximum series (AMS) and peaks over threshold (POT) approaches. The Lyne-Hollick recursive digital filter is applied to separate baseflow from quick flow and to subsequently estimate flood volumes from the quick flow timeseries. Marginal distributions of flood peaks and volumes are examined and used for the estimation of typical design periods. The dependence between peak discharges and volumes is then assessed by an exploratory data analysis using K-plots and Chi-plots, and the consistency of their relationship is quantified by Kendall’s correlation coefficient. Copulas from Archimedean, Elliptical and Extreme Value families are fitted using a pseudo-likelihood estimation method, verified using both graphical approaches and a goodness-of-fit test based on the Cramér-von Mises statistic and evaluated according to the corrected Akaike Information Criterion. The selected copula functions and the corresponding joint return periods are calculated and the results are compared with the marginal univariate estimations of each variable. Results indicate the importance of the bivariate analysis in the estimation of design return period of the hydraulic structures.

Carotenoids have shown an interindividual variability that may be due to genetic factors. The only study that has reported heritability of serum α- and β-carotene has not considered the environmental component. This study aimed to estimate the contribution of both genetic and common environmental effects to the variance of carotenoid concentrations and to test whether their phenotypic correlations with cardiometabolic risk factors are explained by shared genetic and environmental effects. Plasma carotenoid concentrations (α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene, zeaxanthin, and total carotenoids) of 48 healthy subjects were measured. Heritability estimates of carotenoid concentrations were calculated using the variance component method. Lutein and lycopene showed a significant familial effect (p = 6 × 10−6 and 0.0043, respectively). Maximal heritability, genetic heritability, and common environmental effect were computed for lutein (88.3%, 43.8%, and 44.5%, respectively) and lycopene (45.2%, 0%, and 45.2%, respectively). Significant phenotypic correlations between carotenoid concentrations and cardiometabolic risk factors were obtained for β-cryptoxanthin, lycopene, and zeaxanthin. Familial resemblances in lycopene concentrations were mainly attributable to common environmental effects, while for lutein concentrations they were attributable to genetic and common environmental effects. Common genetic and environmental factors may influence carotenoids and cardiometabolic risk factors, but further studies are needed to better understand the potential impact on disease development.

Abstract In this study we introduce a method that accounts for false positive and false negative results in attempting to estimate the true proportion of quantitative trait loci that affect two different traits. This method was applied to data from a genome scan that was used to detect QTL for three independent milk production traits, Australian Selection Index (ASI), protein percentage (P%) and fat percentage corrected for protein percentage (F% – P%). These four different scenarios are attributed to four biological pathways: QTL that (1) increase or decrease total mammary gland production (affecting ASI only); (2) increase or decrease lactose synthesis resulting in the volume of milk being changed but without a change in protein or fat yield (affecting P% only); (3) increase or decrease protein synthesis while milk volume remains relatively constant (affecting ASI and P% in the same direction); (4) increase or decrease fat synthesis while the volume of milk remains relatively constant (affecting F% – P% only). The results indicate that of the positions that detected a gene, most affected one trait and not the others, though a small proportion (2.8%) affected ASI and P% in the same direction.

Este trabalho teve como objetivo avaliar o desempenho biológico de sistemas consorciados de cenoura e alface, sob diferentes combinações de densidades populacionais, com uso das análises bivariada de variância e envoltória de dados (DEA). O delineamento experimental usado foi o de blocos ao acaso completos, com cinco repetições, com os tratamentos arranjados em esquema fatorial 4x4. Os tratamentos resultaram da combinação de quatro populações de plantas de cenoura (40, 60, 80 e 100% da população recomendada no cultivo solteiro - PRCS) com quatro populações de plantas de alface (40, 60, 80 e 100% da PRCS). As populações recomendadas para os cultivos solteiros da cenoura e alface foram 500 mil e 250 mil plantas por hectare, respectivamente. Tanto o método bivariado como o método de análise de envoltória de dados são bastante eficazes na discriminação dos melhores sistemas de cultivo consorciados, por meio dos rendimentos das culturas. Os resultados da eficiência produtiva, medidos por modelos DEA, permitem uma análise estatística simples do ensaio consorciado. A robustez do método de análise bivariada de variância assegura a validade dos resultados.The objective of this paper was to evaluate the biological performance of carrot and lettuce intercropping systems under different combinations of population densities, using the bivariate analysis of variance and data envelopment analysis (DEA). The experimental design was the randomized complete blocks, in a 4x4 factorial scheme (carrot densities: 40, 60, 80 and 100% of the recommended sole crop density (RSCD); lettuce densities: 40, 60, 80 and 100% of the RSCD), with five replications. The recommended population density for carrot in sole crop is 500 thousand plants per hectare and for lettuce in sole crop is 250 thousand plants per hectare. Both bivariate method of variance and data envelopment analysis are quite effective in discriminating the best intercropping systems as assessed through component crop yields. The results of the yield efficiency as assessed by DEA models allow a simple statistical analysis of the intercropping experiment. The robustness of the bivariate analysis of variance method assures the validity of the results.

O objetivo deste trabalho foi estimar as correlações, herdabilidades, repetibilidades, tendências genéticas e fenotípicas, e avaliar as distribuições univariada e bivariada da produção de leite e do intervalo entre partos, em fêmeas bubalinas da raça Murrah, paridas no período de 1982 a 2003. As tendências genéticas e fenotípicas foram estimadas pelas regressões das variáveis dependentes sobre o ano de parto, pelos métodos: regressão linear e regressão não paramétrica, utilizando-se a função de alisamento Spline. As herdabilidades estimadas foram 0,21 e 0,02, e as repetibilidades, 0,32 e 0,06, para a produção de leite e intervalo entre partos, respectivamente. As correlações genética, fenotípica e ambiental foram -0,22, 0,01 e 0,03, respectivamente. As tendências genéticas (regressão linear) foram significativas e iguais a 1,57 kg por ano e 0,085 dia por ano, e as tendências fenotípicas foram 27,74 kg por ano e 0,647 dia por ano, para a produção de leite e intervalo entre partos, respectivamente, tendo sido significativa apenas para a produção de leite. A correlação negativa sugere a existência de antagonismo favorável entre produção de leite e intervalo entre partos; assim é possível selecionar animais com altos valores genéticos para a produção de leite e com menores valores para o intervalo entre partos.The objective of this work was to estimate the correlations, heritabilities, repeatabilities, phenotypic and genetic trends, and to evaluate the univariate and bivariate distributions of the milk yield and calving interval of Murrah breed buffalo, calved from 1982 to 2003. The genetic and phenotypic trends were estimated by regressions of the dependant variables on year of the animals calving, based on two methods: linear regression and articulated polynomial regression. The heritabilities estimates were 0.21 and 0.02, and the repeatabilities 0.32 and 0.06, for milk yield and calving interval, respectively. The genetic, phenotypic and environmental correlations were -0.22, 0.01 and 0.03, respectively. Genetics trends (linear regression) were significant and equal to 1.57 kg per year and 0.085 day per year, and the phenotypics trends were 27.74 kg per year and 0.647 day per year, for milk yield and calving interval, respectively, being significant just for milk yield. The negative genetic correlation suggests that there is a favorable relationship between milk yield and calving intervals, thus it is possible to select animals of high breeding values for milk yield and with low breeding values for calving intervals.

Interannual variation of Indian summer monsoon rainfall (ISMR) is linked to El Niño-Southern oscillation (ENSO) as well as the Equatorial Indian Ocean oscillation (EQUINOO) with the link with the seasonal value of the ENSO index being stronger than that with the EQUINOO index. We show that the variation of a composite index determined through bivariate analysis, explains 54% of ISMR variance, suggesting a strong dependence of the skill of monsoon prediction on the skill of prediction of ENSO and EQUINOO. We explored the possibility of prediction of the Indian rainfall during the summer monsoon season on the basis of prior values of the indices. We find that such predictions are possible for July–September rainfall on the basis of June indices and for August–September rainfall based on the July indices. This will be a useful input for second and later stage forecasts made after the commencement of the monsoon season.