Understanding and improving the feeding value of wheat for broilers

Wheat is the main cereal used in broiler feed formulations in North West Europe, the Americas and Australasia.The nutritional value of wheat and variation in feeding quality have significant commercial importance,as it influences efficiency and rate of broiler chicken growth.This thesis deals with the investigation of variation in nutrient composition of currently available wheat samples for commercial broiler diets in the UK, the relationship between wheat characteristics, AME and growth performance of broilers,and the use of exogenous xylanase on the bioavailability of nutrients and AME of wheat.The first study revealed variation in CP, ash and soluble NSP contents of wheat samples. There were differences (P< 0.05) in AME and N-corrected AME (AMEn) of wheat. The AME of wheat had a maximum range of 1.13 MJ/kg DM between wheat samples. The main energy yielding nutrients (starch and protein)of wheat did not relate with the large variation in AME, moreover, there was no relationship between specific weight and AME. There were differences (13 –14%; P < 0.05) in daily feed intake and weight gain of broilers fed different wheat samples, however, differences were not associated with chemical composition and physical characteristics of wheat. The study also indicated no relationship between AME of wheat and growth performance of broilers. The second study indicated that growing site of wheat crop affected(P < 0.05) the nutrient composition, AME and growth performance, whereas,wheat variety had no influence. The variations in AME were due to differences in polysaccharides composition of wheat between growing sites.The xylanase response to improve AME was related to NSP content (the level of arabinoxylans)of wheat. The findings suggested that the supplementation of xylanase to wheat-based diets should be carefully considered if wheat samples consist of varieties sourced from different growing locations. The third study revealed that the in vivorate of starch digestion differed (P < 0.05) by 25% between two wheat samples with similar proximate nutrients and starch content. Previously,both wheat samples resulted in large differences (11 –12%; P< 0.05) in growth performance of broilers. The study proposed that differences in feed intake and growth rate of broilers may be influenced by the in vivorate of starch digestion and should be investigated using a large set of wheat samples.This project proposed that the future selections of wheat samples for broiler feeds are based on the actual analysis of wheat instead of predicted values. Conventional analytical tests of determining the nutrient composition are unable to predict the AME of wheat. Future research is warranted on factors affecting the growing conditions of wheat crop and the possible influence of growing condition on the nutritive value of wheat for broiler chickens

Wheat sample affects growth performance and the apparent metabolisable energy value for broiler chickens

The aim of this study was to examine chemical composition, quality characteristics, apparent metabolisable energy (AME) and nutrient utilisation of wheat samples currently available to the UK poultry industry and their effect on broiler growth performance. Seventeen current UK wheat samples were used to formulate 17 diets, all of which included 670 g/kg of each wheat sample and 330 g/kg of a balancer feed. Eight hundred (800), day old male Ross 308 broilers were allocated randomly to 160 raised floor pens. Each diet was replicated eight times, fed ad libitum from 0 to 21d age in a randomised complete block design. Excreta were quantitatively collected during the last three days for AME determination. The content of protein, ash and gross energy (GE) ranged from 97 to 143 g/kg DM, 12.8 to 19.6 g/kg DM and 17.81 to 18.24 MJ/kg DM, respectively. The amount of starch and total non-starch polysaccharides (NSP) ranged from 671 to 728 and 80.1 to 98.2 g/kg DM, respectively. The quality characteristics of wheat samples were in the expected range. There were differences (P<0.05) in AME and AMEn of wheat samples. The AME of the wheat had a maximum range of 1.13 MJ/kg DM between samples. Dry matter retention (DMR) and fat digestibility (FD) were significantly different (P<0.05) between wheat samples. The daily feed intake (FI) and weight gain (WG) of broilers fed two wheat samples were significantly (P<0.05) lower as compared to other samples and their low FI and WG were not related to their chemical composition and quality characteristics. The ash content of wheat samples was negatively associated with AMEn (r = − 0.489, P<0.05). The coefficient of FD was positively related to AMEn (r = 0.552, P<0.05). Chemical composition and quality characteristics of the wheat did not relate (P>0.05) to FI and WG of broilers. There was no relationship between growth performance of broilers and AMEn of the wheat samples

Step and Step-Nc as a Tool for Big Data in Cloud Manufacturing

The terms big data, cloud manufacturing, predictive and additive manufacturing, and Internet of Things (IoT) are being most commonly used in the manufacturing industry nowadays. These terms are related to the fourth industrial revolution that emphasizes automation and data exchange between manufacturing tools/elements. Communication occurs between machines, products and even technicians or operators through various technologies while creating records of each interaction resulting in rapid growth of amount of data to be stored. Data acquisition is not a major issue since a structure or framework can properly connect these data in improving manufacturing efficiency. However, lack of effort in collecting and storing manufacturing data in the whole product life cycle process has made integration to be almost difficult to achieve. In this study, the adoption of STEP-NC method/technique was demonstrated in suiting the current explosion of big data in the industrial and manufacturing sector. The proposed methodology was developed through a study of an entity file structure and hierarchical concept in STEP and STEP-NC in gathering manufacturing data in a unified database. The challenge would be in making sense of the data, revealing the patterns in it and using them for operational improvements. The outcome of this study will be useful to support strategic decision making in product manufacturing

Determinants of snakebite mortality in Asia: A systematic review

Purpose: This systemic review summarizes the evidence exploring the determinants of mortality due to snakebite envenomation in Asia. Materials and methods: The database PubMed, Web of Science and Science Direct were searched to identify the relevant literatures concerning mortality due to snakebites mortality in Asia. All the articles chosen were critically appraised for its quality using a mixed-method assessment tool by two independent reviewers with discrepancies sorted by a third person. Results: A total of 7 studies were included in the final analysis which was 3 cross-sectional studies, 2 case reports, 1 observation prospective study and 1 randomized control trial study. Two studies were conducted in India and two studies in Sri Lanka while one study was conducted in Taiwan, Vietnam and Nepal respectively. The cases of snakebite victims were retrieved from the year of 1987 until 2017. In total, there were 762 cases of snakebite victims recorded, with 61 of those victims succumbed to death. From the final total of 7 studies, 4 of the studies showed snakebites mortality were related to delayed treatment access and 3 studies due to suboptimal care. Conclusion: Mortality and morbidity can be reduced if there is a quick access for victims to emergency medical care, rapid transfer time to hospital and receiving immediate optimal medical treatment from trained medical staff once in the hospital or dispensary. © 202

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Diversity and conservation status of small mammals in Kelantan, Malaysia

There is little information and research on the diversity of the small mammals in Kelantan. Thus, a series of wildlife surveys were done at five localities in Kelantan to further elucidate the diversity of small mammals in this state. There were 39 species of small mammals recorded, 13 of these are new records for Kelantan. This significantly increased the known diversity of small mammals from 71 to 84 species. However, the diversity of small mammals in Kelantan is still underrepresented and further surveys are needed to add more information to the current knowledge

Influence of alkaline treatment and fiber loading on the physical and mechanical properties of kenaf/polypropylene composites for variety of applications

Due to current trend and increasing interest towards natural based fiber products, Kenaf (Hibiscus cannabinus) fibers have been used for the developments of many products. Therefore, Kenaf fiber-reinforced composites have been widely used in engineering and industrial applications. The present work deals with the fabricating and characterization of untreated and treated kenaf/polypropylene (PP)-reinforced composites. Composites of PP reinforced with treated and untreated kenaf fibers were fabricated using the injection molding technique. Different fiber loadings of 10, 20, 30, 40, 50 wt% treated and untreated kenaf composites were also prepared. X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy and thermo gravimetric analysis (TGA) were performed on the treated, untreated kenaf fibers and kenaf/PP composites. Moreover, the alkaline-treated kenaf composites exhibit better physical, morphological, and mechanical properties because of the compatibility of kenaf with PP. However, variations in tensile and flexural properties depend on treatment and kenaf fiber contents. The percentage increase in the mechanical properties of the treated kenaf/PP composites relative to that of PP was also measured. In addition, 40 wt% kenaf fiber loading resulted in higher mechanical properties. By contrast, kenaf/PP composite with 50% fiber loading was not successfully prepared because of improper mixing and the burning of kenaf fibers in the PP matrix. To conclude, 40% kenaf/PP composites with superior physical and mechanical properties may be used in variety of applications such as automotive, sports, construction, animal bedding, and mass production industries