Seasonal Variations in Soil Conditions, Its Classification and Mapping of Dry Sub Tropical Region of Uthal, District Lasbela

The study on soil classification and seasonal variation was carried out during 2011-12 in Tehsil Uthal, District Lasbella (Balochistan). The water and soil samples were collected and subjected to determine for various physico-chemical properties and accordingly the results were formulated and compared with standard values. In winter soil EC in Zone 1, Zone 2, Zone 3 and Zone 4 area was 2.218, 1.99, 2.43 and 1.22 dS m-1,pH value 8.1, 8.3, 8.3 and 7.8, HCO3- 2.0125, 1.725, 1.675 and 2.5875 meq L-1, Na2+ 13, 12, 11.4125 and 14meq L-1 ,Ca2+ 7, 6, 6 and 7meq L-1 while the TDS in soil samples were 1571, 1638, 1902 and 837, respectively. In summer soil EC in Zone 1, Zone 2, Zone 3 and Zone 4area zones was 2.27, 2.04, 2.66 and 1.29 dS cm-1, pH value 8.7, 8.4, 8.4 and 8.0, HCO3-1.7375, 1.675, 1.5375 and 1.85meq L-1, Na2+ 13, 13, 12 and 16meq L-1,Ca2+6, 6, 6 and 7meq L-1 while the TDS in soil samples were 1605, 1713, 1001 and 952, respectively. Average value of ECe of 2.04 dSm-1.  The ECe values ranged 1.08 to 3 dSm-1. The average values of ECe at the given depth verify that marginal salinity was present in the soil. This may be due to the leaching of salts to the deeper layers. The average value of SAR is 9.18. The SAR ranged from 6.8 to 12.2. The ratios are less than 13 which show that concentration of Na+ ions to that of Ca+2 and Mg+2 is low. The average value of SAR is 9.18. The SAR ranged from 6.8 to 12.2. The ratios are less than 13 which show that concentration of Na+ ions to that of Ca+2 and Mg+2 is low. This shows improvement in soil. Keywords: Soil, Electrical Conductivity, SAR, Summer, Winter, Zones, Mappin

Opium for the Masses? Conflict-Induced Narcotics Production in Afghanistan

We show that the recent rise in Afghan opium production is caused by violent conflicts. Violence destroys roads and irrigation, crucial to alternative crops, and weakens local incentives to rebuild infrastructure and enforce law and order. Exploiting a unique data set, we show that Western hostile casualties, our proxy for conflict, have strong impact on subsequent local opium production. This proxy is shown to be exogenous to opium. We exploit the discontinuity at the end of the planting season: Conflicts have strong effects before and no effect after planting, assuring causality. Effects are strongest where government law enforcement is weak

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

Knowledge Economy from the Pakistani Perspective

Business Dictionary (2010) defines knowledge economy as: “Economy based on creating, evaluating, and trading knowledge. In a knowledge economy, labour costs become progressively less important and traditional economic concepts such as scarcity resources and economics of scale cease to apply”. World Bank (2008) document states regarding knowledge economy, “For countries in the vanguard of the world economy, the balance between knowledge and resources has shifted so far towards the former that knowledge has become perhaps the most important factor determining the standard of living – more than land, than tools, than labour. Today’s most technically advanced economies are truly knowledge based.” World Bank highlighted the four pillars for knowledge economy are 1. Economic and Institution management 2. Education and Skill 3. Information and Communication Infrastructure 4. Innovative System i.e. Research The knowledge economy focused on the production and management of knowledge in the frame of economic constraints, or to a knowledge-based economy. In another meaning, it refers to the use of knowledge technologies to produce economic benefits. The essential difference is that in a knowledge economy, knowledge is a product, in knowledge-based economy, knowledge is a tool. In this way, brain attains a status of resource, ideas and thoughts are considered the products and the money so earned – konwledge money or economy (Wikipedia, 2010). Drucker (1969) opines that unlike most resources that reduce when used, information and knowledge can be shared, and actually grow through application. Human capital — competencies — are a key component of value in a knowledge-based company. Communication is increasingly being seen as fundamental to knowledge flows. Social structures, cultural context and other factors influencing social relations are therefore of fundamental importance to knowledge economies. (p.263) Developing countries differ from developed countries not only because they have less wealth and capital but because they have less knowledge. It is often costly to create and that is why much of it is created in industrial countries. United States dominates the world’s knowledge economy because 45 out of 50 regions with best knowledge base in the world are situated in the America. (Omar, 2003