Forecasts play a central role in decision-making under uncertainty. After a brief review of the general issues, this article considers ways of using high-dimensional data in forecasting. We consider selecting variables from a known active set, known knowns, using Lasso and One Covariate at a time Multiple Testing, and approximating unobserved latent factors, known unknowns, by various means. This combines both sparse and dense approaches to forecasting. We demonstrate the various issues involved in variable selection in a high-dimensional setting with an application to forecasting UK inflation at different horizons over the period 2020q1–2023q1. This application shows both the power of parsimonious models and the importance of allowing for global variables.

A total of 108 diverse sorghum (Sorghum bicolor) accessions were characterized for quantitative and qualitative fodder-related traits and zonate leaf spot (ZLS) (Gloeocercospora sorghi) disease during two successive wet seasons of 2019 and 2020 in augmented randomized block design. The Shannon's diversity index and analysis of variance showed the existence of significant variability among qualitative and quantitative traits. K-mean clustering showed strong relationship between green fodder yield (GFY) and other yield-contributing traits. The dendrogram constructed based on morphological traits classified accessions into four diverse groups and most of genotype fall under cluster II. The principal component analysis bi-plot analysis showed a total variation of 68.96%, where GFY, stem weight per plant, panicle length and dry matter yield (DMY) contributed significantly. From the experimental results, three sorghum genotypes viz., IG-03-424, IG-01-436 and IG-03-438 were identified as promising for higher GFY (808.66 g/plant) and DMY (238.0 g/plant), respectively. Further, based on disease reactions under natural condition, five genotypes viz., EC-512397, EC512393, EC512394, EC512399 and IG-02-437 were identified as potential donor for resistance to ZLS disease. These selected lines could be used as promising sources for high biomass and disease resistance in forage sorghum breeding programme.

The shape of the flower can vary based on the type of pollinator or the environment in which the plant develops. In Vanilla insignis, there are no studies that analyse the shape of the labellum of the flower as has been done in V. planifolia. Therefore, the study aimed to determine the variation in the shape of the labellum of V. insignis through a morphometric analysis in different environmental conditions in the state of Quintana Roo, Mexico. The results showed that there were significant differences in the variables analysed. Principal component analysis and dendrogram analysis reveal that four V. insignis morphotypes were possibly associated with soil water availability conditions because there were significant differences between the variables that define the apical region. In addition, the distribution of the morphotypes corresponded with the presence of humidity regardless of geographical distances such as in the populations of Tenampulco, Puebla and Caobas, Quintana Roo. The presence of these morphotypes allows the development of conservation programmes and genetic improvement of the species of V. insignis and related commercial species.

This study assessed the genetic diversity of African yam bean (AYB) accessions using morphological and molecular markers. The accessions were grown, and morphological data collected were subjected to analysis of variance and multivariate analyses. Genomic DNA extracted from the accessions were amplified with inter simple sequence repeat (ISSR) markers. The diversity analysis was conducted using MEGA4 software. The accessions varied significantly (P < 0.05) in growth, flowering and seed-related parameters. Flowering commenced early in most accessions. Weight of 100-seed range from 15.01 to 21.15 g with the mean value of 18.30 g. Significant correlations existed between stem height, the number of leaves and leaf dimensions. Also, days to flowering correlated with pod formation; likewise, seed dimension had a positive association with seed weight. The principal biplot revealed that two components accounted for 41.77% of the observed variation. Analysis of the electropherogram showed 95 loci comprising 1351 alleles were detected by the ISSR markers with 65.26% polymorphism and combined polymorphic information content of 0.85. The principal coordinate analysis placed accessions together on a plane based on their spatial relationship. The dendrogram showed accession pairs (TSs-77, TSs-95) and (TSs-111, TSs-84) are closely related. The phylogram identified three kinships with a total length of 454. Accession TSs-115 is likely the progenitor while TSs-82 and TSs-86 are the most recent. The study concluded that a combination of morphological and ISSR markers is effective for the diversity study of AYB and the existing, genetic diversity in the accessions could be harnessed for its improvement, conservation and utilization.

We provide a new way of deriving a number of dynamic unobserved factors from a set of variables. We show how standard principal components may be expressed in state space form and estimated using the Kalman filter. To illustrate our procedure, we perform two exercises. First, we use it to estimate a measure of the current account imbalances among northern and southern euro area countries that developed during the period leading up to the outbreak of the euro area crisis, before looking at adjustment in the post-crisis period. Second, we show how these dynamic factors can improve forecasting of the euro exchange rate.

The description of the growth of the Japanese quails is necessary to characterize the genetic potential of these birds raised in different countries. Thus, the aim of this study was to describe the genetic potential of Japanese quails by conducting a meta-analysis considering studies conducted in different countries. Only data about the subspecies Coturnix coturnix japonica were considered; studies regarding Coturnix coturnix coturnix were not examined. The criteria investigated were BW (W), age (t), year of publication and location of the study. Each set of genetic material within a publication was coded as one study. The Gompertz function was used to interpret the growth of laying quails; thus, each study was represented by Gompertz parameters. The W and t data were applied to estimate the values of Gompertz growth parameters, including BW at maturity (Wm), BW at birth (Wi), maturity rate (B) and inflection point (IP). The age at which the maximum growth rate was achieved (t*) was calculated considering the parameters Wm, Wi and B. To estimate these parameters, random regression was used to randomize the parameter Wm. The parameters estimated for each assay were used in exploratory, grouping, and principal component analyses. The values of Wi ranged from 4.1 to 11.6 g. The values of B ranged from 0.0393 to 0.1039/day, and consequently, the values of t* and IP ranged from 14 to 31 days and 9.21 to 31.03 g, respectively. These results show that there is considerable variability in the growth potential of Japanese quails. To better understand this variation, two groups were examined: Brazil and other countries, according to the grouping of Wi, Wm, B and t*; parameter B was the variable that presented the highest specificity, indicating that both groups modified the maturity rate. For the principal component analysis, the year of publication showed a relationship with the growth parameters but only for studies performed in Brazil. For studies carried out in other countries, the changes in growth parameters were not related to the year of publication. In Brazilian studies, there was a decrease in the maturity rate, but the weight at maturity was higher. Therefore, it appears that different strategies of genetic selection were adopted in Brazil compared to other countries.

The topic of anomaly detection in networks has attracted a lot of attention in recent years, especially with the rise of connected devices and social networks. Anomaly detection spans a wide range of applications, from detecting terrorist cells in counter-terrorism efforts to identifying unexpected mutations during ribonucleic acid transcription. Fittingly, numerous algorithmic techniques for anomaly detection have been introduced. However, to date, little work has been done to evaluate these algorithms from a statistical perspective. This work is aimed at addressing this gap in the literature by carrying out statistical evaluation of a suite of popular spectral methods for anomaly detection in networks. Our investigation on the statistical properties of these algorithms reveals several important and critical shortcomings that we make methodological improvements to address. Further, we carry out a performance evaluation of these algorithms using simulated networks and extend the methods from binary to count networks.

The gastrointestinal alterations associated with the consumption of an obesogenic diet, such as inflammation, permeability impairment and oxidative stress, have been poorly explored in both diet-induced obesity (DIO) and genetic obesity. The aim of the present study was to examine the impact of an obesogenic diet on the gut health status of DIO rats in comparison with the Zucker (fa/fa) rat leptin receptor-deficient model of genetic obesity over time. For this purpose, female Wistar rats (n 48) were administered a standard or a cafeteria diet (CAF diet) for 12, 14·5 or 17 weeks and were compared with fa/fa Zucker rats fed a standard diet for 10 weeks. Morphometric variables, plasma biochemical parameters, myeloperoxidase (MPO) activity and reactive oxygen species (ROS) levels in the ileum were assessed, as well as the expressions of proinflammatory genes (TNF-α and inducible nitric oxide synthase (iNOS)) and intestinal permeability genes (zonula occludens-1, claudin-1 and occludin). Both the nutritional model and the genetic obesity model showed increased body weight and metabolic alterations at the final time point. An increase in intestinal ROS production and MPO activity was observed in the gastrointestinal tracts of rats fed a CAF diet but not in the genetic obesity model. TNF-α was overexpressed in the ileum of both CAF diet and fa/fa groups, and ileal inflammation was associated with the degree of obesity and metabolic alterations. Interestingly, the 17-week CAF group and the fa/fa rats exhibited alterations in the expressions of permeability genes. Relevantly, in the hyperlipidic refined sugar diet model of obesity, the responses to chronic energy overload led to time-dependent increases in gut inflammation and oxidative stress.

Closed basin playas are among the most sensitive hydrologic systems globally and are excellent indicators of current and past climatic variability. This variability can significantly impact hydrologic regimes and biotic communities, and is often expressed in lake-bed deposits and shoreline features. We analyzed two playa basins in western North America that lie to either side of the current divide between monsoon and westerly precipitation regimes. Using a 23-year sequence of Landsat images at a 16-day time step, we determined the playa inundation response to varying precipitation inputs. Our results show that a strongly contrasting lake-inundation response occurs in lake basins separated by only 200 km. The Animas/Lordsburg Basin shows a marked lake-area increase in response to winter precipitation events, while the more southerly Palomas Basin shows a stronger response to monsoonal and El Niño-type events. This sensitivity to different input sources over short distances may explain some of the apparent asynchronous behavior of playa response found in lake records. Comprehensive regional-scale inundation records could be used to understand the dynamics of playa inundation events and how these events are linked to atmospheric circulation, and possibly to understand the observed asynchronous behavior of lake basins during the late Pleistocene and Holocene.

Traditional methods for the assessment of dietary intake are prone to error; in order to improve and enhance these methods increasing interest in the identification of dietary biomarkers has materialised. Metabolomics has emerged as a key tool in the area of dietary biomarker discovery and to date the use of metabolomics has identified a number of putative biomarkers. Applications to identify novel biomarkers of intake have in general taken three approaches: (1) specific acute intervention studies to identify specific biomarkers of intake; (2) searching for biomarkers in cohort studies by correlating to self-reported intake of a specific food/food group(s); (3) analysing dietary patterns in conjunction with metabolomic profiles to identify biomarkers and nutritypes. A number of analytical technologies are employed in metabolomics as currently there is no single technique capable of measuring the entire metabolome. These approaches each have their own advantages and disadvantages. The present review will provide an overview of current technologies and applications of metabolomics in the determination of new dietary biomarkers. In addition, it will address some of the current challenges in the field and future outlooks.

This study examines the valuation of research as intangible capital in agriculture using Tobin's q theory. The market value of public research capital is estimated to be 8.6 times higher than conventional assets. Private research capital is valued 5.2 times higher than conventional assets. The estimated valuation multiplier for all farm assets dropped 1/3 over the last decade. In recent years the valuation multiplier has dropped below a dollar, which indicates the market is undervaluing farm assets.

The main purpose of this article is: given a score matrix called S, find out the joint proportional contribution of factors due to persons (conditions, situations, and so forth) and factors due to variables, for any sij observed score, where i identifies persons, and j, variables. This approach makes it possible a) to show that the same score in a given variable may have a different quantitative interpretation in terms of persons or conditions, and b) to find out how subjects differ in the way in which they relate variables.

We study ensembles of similar systemsunder load of environmental factors. The phenomenon of adaptationhas similar properties for systems of different nature. Typically,when the load increases above some threshold, then the adaptingsystems become more different (variance increases), but thecorrelation increases too. If the stress continues to increasethen the second threshold appears: the correlation achievesmaximal value, and start to decrease, but the variance continue toincrease. In many applications this second threshold is a signalof approaching of fatal outcome.
This effect is supported by many experiments and observation ofgroups of humans, mice, trees, grassy plants, and on financialtime series. A general approach to explanation of the effectthrough dynamics of adaptation is developed. H. Selye introduced“adaptation energy" for explanation of adaptation phenomena. Weformalize this approach in factors – resource models anddevelop hierarchy of models of adaptation. Different organizationof interaction between factors (Liebig's versus synergisticsystems) lead to different adaptation dynamics. This gives anexplanation to qualitatively different dynamics of correlationunder different types of load and to some deviation from thetypical reaction to stress.
In addition to the “quasistatic" optimization factor – resourcemodels, dynamical models of adaptation are developed, and asimple model (three variables) for adaptation to one factor loadis formulated explicitly.

The role of diet in promoting health and preventing disease is difficult to elucidate due to its complex network of foods and nutrients. Besides total energy intake, dietary composition is probably the most important discriminator within and between populations. Dietary composition is reflected in dietary patterns, which have recently gained popularity. The present paper reviews the most commonly applied methods to identify dietary patterns, data-driven methods such as factor and cluster analysis, investigator-driven methods such as indices and score, and methods combining the two, namely reduced rank regression. We describe the techniques and their application, discuss strengths and limitations, and discuss the usefulness of dietary pattern analyses.

Visual evoked responses to dichoptically presented multifocal stimuli were recorded for 92 eyes. Two stimulus variants were explored: temporally sparse and rapidly contrast reversing. We used hierarchal decomposition (HD) to represent the multifocal responses in terms of a small number of potentially unique component waveforms that are interrelated in a multivariate linear autoregressive (MLAR) relationship. The HD method exploits temporal correlations over a range of delays in the responses to estimate parallel, feedforward and feedback relationships between the HD components. Three HD components having temporal interrelationships constrained (at P < 0.05) to a moving ∼20 ms window could describe the multifocal responses well (median r2-values up to 90%). HD components were similar for both stimulus types and the component waveforms were temporally correlated, especially the first and third components. The data set was large enough to estimate separate HD components for each multifocal stimulus region. The component waveforms differed somewhat by region but the MLAR relationships were similar. At short delays parallel processing dominated. At longer delays the proportion of response drives that were attributed to feedback and feedforward relationships grew. Overall HD analysis seems to provide an informed summary of multifocal responses and insights into their sources.