Wage led aggregate demand in the United Kingdom

The wage led aggregate demand hypothesis is examined for the United Kingdom over the period 1971 - 2007. Existing studies disagree on the aggregate demand regime for the UK, and this appears to be due to differing empirical approaches. Studies relying on equation-by-equation estimation procedures tend to find support for wage led aggregate demand in the UK, while the single study using systems estimation finds no support for the hypothesis. In order to resolve this incongruity, we test the wage led aggregate demand hypothesis in the UK using VAR models estimated on quarterly data. We use a liberal partial identification strategy based on movements in real earnings rather than in the labour share. The results provide support for the wage led aggregate demand hypothesis during the period of study

Chemical properties of 11 date cultivars and their corresponding fiber extracts

Date palm fruit from 11 Tunisian cultivars (Phoenix dactylifera L.) were analyzed for their main chemical composition. Results showed that date fruits were rich in sugar (79.93 - 88.02 g/100 g dry matter), fiber(8.09 - 20.25 g/100 g dry matter) and ash (1.73 - 2.59 g/100 g dry matter). Mineral fraction was dominated by potassium and sugar fraction was dominated by reducing sugar (glucose, fructose) except for Deglet Nour, Kentichi and Bajo which are rich in sucrose. Date fiber concentrates (DFC) were extracted and analyzed for their proximate content (moisture, fiber, protein, lipid and ash) and some functional properties such as water holding capacity (WHC) and oil holding capacity (OHC). DFC presented high dietary fiber content (90.71 - 93.92 g/100g dry matter). Protein and lipid contents (dry matter basis) ranged between 3.66 and 6.06 g/100 g and between 0.35 and 1.08 g/100 g, respectively. DFC presentedhigh WHC (6.20 g water/g dry fiber) and high OHC (1.80 g oil/g dry fiber). Results showed that dates could be a valuable source of highly techno-functional fibers that could be used in food formulations

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Biogeochemical Stoichiometry of Antarctic Dry Valley Ecosystems

Among aquatic and terrestrial landscapes of the McMurdo Dry Valleys, Antarctica, ecosystem stoichiometry ranges from values near the Redfield ratios for C:N:P to nutrient concentrations in proportions far above or below ratios necessary to support balanced microbial growth. This polar desert provides an opportunity to evaluate stoichiometric approaches to understand nutrient cycling in an ecosystem where biological diversity and activity are low, and controls over the movement and mass balances of nutrients operate over 10–10⁶ years. The simple organisms (microbial and metazoan) comprising dry valley foodwebs adhere to strict biochemical requirements in the composition of their biomass, and when activated by availability of liquid water, they influence the chemical composition of their environment according to these ratios. Nitrogen and phosphorus varied significantly in terrestrial and aquatic ecosystems occurring on landscape surfaces across a wide range of exposure ages, indicating strong influences of landscape development and geochemistry on nutrient availability. Biota control the elemental ratio of stream waters, while geochemical stoichiometry (e.g., weathering, atmospheric deposition) evidently limits the distribution of soil invertebrates. We present a conceptual model describing transformations across dry valley landscapes facilitated by exchanges of liquid water and biotic processing of dissolved nutrients. We conclude that contemporary ecosystem stoichiometry of Antarctic Dry Valley soils, glaciers, streams, and lakes results from a combination of extant biological processes superimposed on a legacy of landscape processes and previous climates

Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review.

BACKGROUND: Accurately identifying patients with hypoglycemia is key to preventing adverse events and mortality. Natural language processing (NLP), a form of artificial intelligence, uses computational algorithms to extract information from text data. NLP is a scalable, efficient, and quick method to extract hypoglycemia-related information when using electronic health record data sources from a large population. OBJECTIVE: The objective of this systematic review was to synthesize the literature on the application of NLP to extract hypoglycemia from electronic health record clinical notes. METHODS: Literature searches were conducted electronically in PubMed, Web of Science Core Collection, CINAHL (EBSCO), PsycINFO (Ovid), IEEE Xplore, Google Scholar, and ACL Anthology. Keywords included hypoglycemia, low blood glucose, NLP, and machine learning. Inclusion criteria included studies that applied NLP to identify hypoglycemia, reported the outcomes related to hypoglycemia, and were published in English as full papers. RESULTS: This review (n=8 studies) revealed heterogeneity of the reported results related to hypoglycemia. Of the 8 included studies, 4 (50%) reported that the prevalence rate of any level of hypoglycemia was 3.4% to 46.2%. The use of NLP to analyze clinical notes improved the capture of undocumented or missed hypoglycemic events using International Classification of Diseases, Ninth Revision (ICD-9), and International Classification of Diseases, Tenth Revision (ICD-10), and laboratory testing. The combination of NLP and ICD-9 or ICD-10 codes significantly increased the identification of hypoglycemic events compared with individual methods; for example, the prevalence rates of hypoglycemia were 12.4% for International Classification of Diseases codes, 25.1% for an NLP algorithm, and 32.2% for combined algorithms. All the reviewed studies applied rule-based NLP algorithms to identify hypoglycemia. CONCLUSIONS: The findings provided evidence that the application of NLP to analyze clinical notes improved the capture of hypoglycemic events, particularly when combined with the ICD-9 or ICD-10 codes and laboratory testing

High-Normal Albuminuria and Risk of Heart Failure in the Community

Albuminuria has been associated with cardiovascular risk, but the relationship of high-normal albuminuria to subsequent heart failure has not been well established

Productive Structure in the Neo-Kaleckian Model of Growth and Distribution: Simulations to the Brazilian Economy

This chapter has as its main objective to analyze the relationship between structural change, exchange rate devaluation, growth and income distribution in Brazil. The neo-Kaleckian model of growth and distribution as designed by Cimoli et al. (2016) is simulated to the short run, where there are no restrictions to deficits on the balance of payments. This is a post-Keynesian model with Schumpeterian and Latin American structuralist ideas. The shocks in the model are made in order to understand impacts of structural change, wage level increases, and exchange rate devaluations in the Brazilian economy. To accomplish these objectives, the model is calibrated in this chapter using real data for 2011. The results indicate the dynamics of the neo-Kaleckian model and lead to an analysis of possible impacts of changes in the productive sector on growth and income distribution in Brazil

The Rise and Fall of Export-Led Growth

This paper traces the rise of export-led growth as a development paradigm and argues that it is exhausted owing to changed conditions in emerging market (EM) and developed economies. The global economy needs a recalibration that facilitates a new paradigm of domestic demand-led growth. Globalization has so diversified global economic activity that no country or region can act as the lone locomotive of global growth. Political reasoning suggests that EM countries are not likely to abandon export-led growth, nor will the international community implement the international arrangements needed for successful domestic demand-led growth. Consequently, the global economy likely faces asymmetric stagnation

Association of Southeast Asian Nations, People's Republic of China, and India Growth and the Rest of the World: The Role of Trade

This paper explores the impact of past and future growth in the Association of Southeast Asian Nations (ASEAN)1 Since the mid-1990s, ACI growth has improved the non-oil terms of trade of the developed countries. There have also been strong complementarities between ACI suppliers of intermediate inputs and PRC exports. More developed Asian countries have benefited from PRC capital goods demand. ACI growth has, however, put competitive pressures on other less-developed manufacturing exporters, worsening their terms of trade and constraining their pricing ability. ACI growth has been especially beneficial for oil and minerals commodity producers. On the other hand, net food importers and oil importing countries have been adversely affected by high import costs. , the People's Republic of China (PRC), and India - here referred to as the ACI countries - on aggregate welfare, relative wages, and global emissions in the rest of the world. It outlines several analytical frameworks, considers effects over the past decade and, based on consensus forecasts, the implications of that growth for the rest of the world in the decades to come. Future ACI growth provides opportunities and challenges for the rest of the world. For developed countries the opportunities are for selling high-end services and capital and consumer goods in the ACI markets and enjoying the benefits from intra-industry trade; the challenges will come from increased head-to-head competition in manufactured goods and services that should become more intense in future decades. For medium-income producers currently at between 30% and 60% of US levels, there will be a tougher tradeoff between more intensive competition with the PRC and serving the growing middle classes in ACI countries. For poorer countries, there will greater opportunities for becoming part of global supply chains in manufactured exports. Standard frameworks that assume internal factor mobility suggest continuing pressures for wage inequality in developed countries. But these hinge on the assumption that the ACI and developed countries will continue to produce similar products and that the ACI will specialize in unskilled labor-intensive products. In fact, as their exports become more technology - intensive and developed countries more specialized these pressures could be alleviated. On the one hand, as the "flying geese" process continues, exports from countries with lower incomes than the PRC are likely to displace PRC labor-intensive exports rather than domestic production in developed countries. On the other hand, while it may cause job loss and erode the returns to specific factors, PRC export growth is less likely to be a source of wage inequality in advanced economies

Airflow Obstruction, Lung Function, and Incidence of Atrial Fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study

Reduced low forced expiratory volume in 1 second (FEV1) is reportedly associated with an increased risk of atrial fibrillation (AF). Extant reports do not provide separate estimates for never smokers, and for African Americans, who incongruously have lower AF incidence than Caucasians