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International audience; Objectives: To examine the association between high intakes of ultra-processed foods (UPF) and recurrence of depressive symptoms (DepS) in a Western non-Mediterranean country and its contribution to the overall diet-depression relationship.Methods: Analyses were carried out on British participants from the Whitehall II cohort. Present analyses were restricted to white participants N = 4554 (74% men, mean age = 61; SD = 5.9). UPF consumption was estimated from a 127-item food frequency questionnaire using the NOVA classification, and cumulative average of UPF intakes (g/day) over 11 years of exposure (1991/1994–2002/2004) was computed. Recurrent DepS after measurement of UPF was defined as having two or more episodes of DepS (the Center for Epidemiologic Studies Depression Scale (CES-D) score ≥ 16 or antidepressants use) during four phases of follow-up (2002/2004–2015/2016).Results: Over the follow-up, 588 (12.9%) cases of recurrent DepS were observed. After adjusting for socio-demographic factors, health behaviours and health status, participants in top quintile of UPF intakes [mean 33% of total daily intakes in grams] had 31% higher odds of recurrent DepS (odds ratio 1.31; 95% CI 1.04–1.64) compared to participants in the four lowest quintiles of UPF [mean 18.1% of total daily intakes in grams]. Additional analyses showed that associations between adherence to several diet quality measures and recurrent DepS were partially attenuated (17–27%) by UPF intakes.Conclusion: In this British population, high intakes of ultra-processed foods were associated with increased odds of recurrent depressive symptoms and contributed to the overall diet quality-depressive symptoms association.

Integrating sustainability in the risk management process is an emergent problem, especially for efficient infrastructure delivery. For the case of complex projects like public–private partnerships (P3), traditional management practices offer a limited capacity to address long-ranging risk impacts on the social, economic, and environmental fabric within and around the project boundaries. Although P3 projects are objective-based contracts, present risk models rarely delineate risk impacts on focused project objectives. The relevant studies are very scarce creating a limited understanding of available approaches to conducting sustainability-based risk management for P3 projects. As risk and sustainability are two inherently subjective concepts with multiple interpretations, their combined assessment within a single framework demands a pragmatic approach. Therefore, the current study presents a model for conducting a sustainability-based risk assessment of P3 infrastructure projects through global data. Monte Carlo simulation is employed to further define the probabilistic risk ranges and risk ranks over relevant triple-bottom-line-based sustainability indicators for highway sector P3 projects. Findings are further demonstrated through two highway case studies and relevant mitigation strategies are also suggested. In the end, an implementation framework and future recommendations for the application of study findings on actual projects are also suggested. The study has useful implications for practitioners and researchers alike aiming for the delivery of sustainable complex projects.

The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D0%, D20%, and D40% from the field capacity (FC) and D100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of D0%, D20%, D40%, and D100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region.

The field of nutritional psychiatry has generated observational and efficacy data supporting a role for healthy dietary patterns in depression onset and symptom management. To guide future clinical trials and targeted dietary therapies, this review provides an overview of what is currently known regarding underlying mechanisms of action by which diet may influence mental and brain health. The mechanisms of action associating diet with health outcomes are complex, multifaceted, interacting, and not restricted to any one biological pathway. Numerous pathways were identified through which diet could plausibly affect mental health. These include modulation of pathways involved in inflammation, oxidative stress, epigenetics, mitochondrial dysfunction, the gut microbiota, tryptophan-kynurenine metabolism, the HPA axis, neurogenesis and BDNF, epigenetics, and obesity. However, the nascent nature of the nutritional psychiatry field to date means that the existing literature identified in this review is largely comprised of preclinical animal studies. To fully identify and elucidate complex mechanisms of action, intervention studies that assess markers related to these pathways within clinically diagnosed human populations are needed.

The live water storage of the reservoirs is decreasing by the sedimentation, which is affecting the reservoir’s capacity and cause a severe problem for the irrigation system at the downstream side. Floods occur at the downstream by the poor management at upstream due to the heavy rainfall and snow melting. For annual accumulations of sediment load and estimation of the peak flow at Tarbela reservoir near Besham Qila station having area of 170,000 km2 was selected. Estimation of the peak flow and sediment yield at the Tarbela reservoir, SWAT (distributed hydrological model) was used. The expected decrease in reservoir storage capacity was also estimated with the SWAT model. For runoff modelling, calibration was done for three years (2004-2006) and validation was also done for three years (2007-2009). Nash-Sutcliffe Efficiency (NSE) and Standard Error of Estimate existed the statistical indices to evaluate the results. Coefficient of determination (R2) was found as 0.75 for the calibration period and 0.80 for the validation. Whereas, NSE for calibration was observed 0.69 and 0.70 for the validation. Monthly mean sediment yield was about 0.13 BCM estimated at the Tarbela reservoir near Besham Qila.

The problem of climate change has become very strongly during last two decades on global scale in view of the projected consequences on the environment of unguarded states. Gradually rising temperature and its effects on the crops here and rainfall are obvious in many areas around the world. Climate change related to natural and anthropogenic processes in Pakistan is the major source of study in this report. The impacts of these climate changes appear to be additional component of the large number of existing water related problems in every station of Pakistan. The objective of this report is to analyze the global warming effect on CWR. For this purpose, we made seven scenarios So, S1, S2, S3, S4, S5 and S6. From So-S3 crop water requirement increases in all regions but from S4-S6 crop water requirement remains same. For this purpose we selected different cities from agro ecological stations to check the effect of climate change on CWR. Faisalabad, Gupis, Jacobabad, Kalat, Karachi, Multan, Nawabshah, Peshawar and Zhob are the regions selected for this research. Different scenarios have been made such that, in So scenario temperature remains same but from S1, S2 and S3 scenarios temperature is increases 1, 2 and 3 degree centigrade respectively. While, in S4, S5 and S6 scenarios precipitation increases or decreases according to the climatic changes of that area (So, S1, S2, S3, ) and then we increase or decrease the precipitation rate by 5%, 10% and 15% (S4, S5, S6) in accordance with the zone. From result it is concluded that the crop water requirement in arid and in semi-arid is increasing annually on the other hand the total value of effective rainfall in Pakistan is decreasing.

PurposeThe construction industry struggles in environmental and economic performance due to waste generation. Several studies have measured this waste in the construction industry of developing countries like India, Brazil, China, Nigeria and Iran, and proposed strategies to enhance the overall efficiency. But no such work exists in Pakistan's context. The construction industry of Pakistan contributes significantly to the country's gross domestic product (GDP). And with several mega projects in progress to overcome the energy crises and improve the infrastructure of the country, the absence of proper waste management policies and plans calls for empirical research. Therefore, this study quantifies and benchmarks material waste in the local context, its impact on project cost and the effect of multiple subcontracting arrangements on waste generation. It also proposes a conceptual waste management plan (WMP) for local conditions which can be generalized for developing countries.Design/methodology/approachThis paper uses a mixed research approach by leveraging Saunders's research onion model. To benchmark the current wastage practices, quantitative data of material waste in the Pakistani construction industry are gathered through document review of accounting systems, inventory and payment records of 40 completed building projects. Using the data, the waste rate of different materials is measured along with their impact on cost. Additionally, the role of subcontracting arrangements in waste generation is also investigated. Also, semi-structured interviews are conducted with project managers of high- and low-performing construction organizations to propose a conceptual WMP for the local industry and developing countries.FindingsThe highest wasteful materials by quantity are wood, sand and concrete blocks, and those by cost are wood, bricks and steel. By quantity, 123% more material was used on average than the actual productive work. Also, the labor only (L-O) subcontracting arrangement causes maximum waste. Moreover, the difference between the highest (155%) and lowest wasting company (104%) is 51%, highlighting the proactive and resistive waste management culture and approach by the worst- and best-performing companies. Further, the impact of waste quantities is more than 2% of the project cost. Finally, a conceptual model consisting of measures at the project, industry and national levels is also proposed as a guide for developing countries.Practical implicationsThe findings of this benchmarking study can help improve the project planning, execution and monitoring, and control practices by providing a better understanding of the material waste potential. This will help economize the construction industry and improve its sustainability.Originality/valueThis is the first benchmarking study that quantitatively measures material waste in the construction industry of Pakistan. It highlights that costly as well as sustainability-implicating materials are frequently wasted in the local construction projects. Also, this study correlates the wastage with subcontracting arrangements. Additionally, an original conceptual WMP is proposed that could help the industry improve its performance. The findings could help the construction professionals identify the loopholes in their material management practices and not only save money but also ensure better sustainability.

Economic growth, social wellbeing, and infrastructure are strongly interrelated and jointly contribute to national development. Therefore, evaluation and selection of a road infrastructure project direly need a comprehensive sustainability assessment integrating holistic decision criteria. This study presents an elaborate life cycle sustainability-based project evaluation tool, comprising an assessment framework, an integration model, and a decision framework. In the first phase, a life cycle sustainability assessment (LCSA) framework for road infrastructure is established using mixed methods. In the second phase, interviews are conducted to obtain pairwise comparisons among impact categories and subjective reasoning of their priorities. Analytical hierarchy process (AHP) is adopted to develop the LCSA integration model. The minimum threshold limits of impact categories are evaluated and integrated into the proposed decision framework. Further, thematic and cross-sectional analyses are performed on the interview findings to rationalize the proposed decision framework. The findings include a detailed and customized project assessment framework, an integration model, and a decision framework for the assessment of different project alternatives. This study helps policy- and decision-makers in selecting the project alternative by maximizing sustainability in road infrastructure projects. Insights into environmental and social externalities and their quantitative interpretation throughout the life of the road are also achieved.

Near real-time estimation of soil loss from river catchments is crucial for minimizing environmental degradation of complex river basins. The Chenab river is one of the most complex river basins of the world and is facing severe soil loss due to extreme hydrometeorological conditions, unpredictable hydrologic response, and complex orography. Resultantly, huge soil erosion and sediment yield (SY) not only cause irreversible environmental degradation in the Chenab river catchment but also deteriorate the downstream water resources. In this study, potential soil erosion (PSE) is estimated from the transboundary Chenab river catchment using the Revised Universal Soil Loss Equation (RUSLE), coupled with remote sensing (RS) and geographic information system (GIS). Land Use of the European Space Agency (ESA), Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, and world soil map of Food and Agriculture Organization (FAO)/The United Nations Educational, Scientific and Cultural Organization were incorporated into the study. The SY was estimated on monthly, quarterly, seasonal, and annual time-scales using sediment delivery ratio (SDR) estimated through the area, slope, and curve number (CN)-based approaches. The 30-year average PSE from the Chenab river catchment was estimated as 177.8, 61.5, 310.3, 39.5, 26.9, 47.1, and 99.1 tons/ha for annual, rabi, kharif, fall, winter, spring, and summer time scales, respectively. The 30-year average annual SY from the Chenab river catchment was estimated as 4.086, 6.163, and 7.502 million tons based on area, slope, and CN approaches. The time series trends analysis of SY indicated an increase of 0.0895, 0.1387, and 0.1698 million tons per year for area, slope, and CN-based approaches, respectively. It is recommended that the areas, except for slight erosion intensity, should be focused on framing strategies for control and mitigation of soil erosion in the Chenab river catchment.

Contains fulltext : 219531.pdf (Publisher’s version ) (Closed access) The present study investigates the relationship between birth rank and academic achievement of children in a cross-country study to examine whether firstborn children perform better in primary school than later-born children when controlling for individual, social and parental characteristics. Data were drawn from the School Children Mental Health in Europe (SCMHE) study, which included samples from Bulgaria, Germany, Italy, Netherlands, Lithuania, Romania and Turkey (n = 7,518). Children's academic performance in reading and mathematics was evaluated by teachers and parents reported sociodemographic variables including birth rank and parental attitudes. Controlling for individual, sociodemographic variables and parental attitudes in multinomial regressions, first- or second-born children displayed greater performance in mathematics and in reading as compared to children whose birth rank was third or above. Children from large families, especially when they are not first- or second-born appear to be at greater risk for academic difficulties and should benefit from targeted prevention efforts. 20 p.

Complex construction projects are risky owing to several features and factors. Their management involves risk assessment which is subjected to various behavioural tendencies and the existing body of knowledge lacks appropriate methods to quantify these effects. The prevalent standard model of Expected Utility Theory does not differentiate between threat and opportunity, resulting into an identical estimation for both facets of risk. This limitation was addressed by Prospect Theory which better captures risk preferences. However, construction industry still relies upon conventional methods of risk assessment. The current study introduces a weighting function to better quantify the cognitive errors in construction risk assessment by adjusting the over- and under-estimation. In doing so, detailed scenario-based, semi-structured interviews are conducted engaging senior professionals. It is found that, typically, opportunities are underestimated by 7.5% and threats are overestimated by 8%. Integrating these findings into risk response strategies results into a realistic and effective resource allocation.

© Penerbit Universiti Sains Malaysia, 2017. The construction industry consumes a large part of raw material and global energy, and produces huge amount of solid waste. It is established that waste generated by construction processes has significant negative impact on the economy and environment. Effective waste management helps in reducing quantity of wastes and making a substantial contribution towards sustainable development and cost control. Based on a benchmarking approach, this research quantifies the material wastage and its causes in different types of building projects. In a waste diagnostic survey, 38 project sites were surveyed. Results revealed that bricks, tiles, and plaster from mortar are the most wasteful materials, and improper worker's skills, poor supervision, and lack of management the most significant causes. Buildings with substantial architectural works tend to generate maximum amount of waste while contractor size does not affect waste generation rate. Based on expert opinion, practical recommendations are given to control material waste. The findings offer a new perspective on sustainable construction by correlating building types with waste generation, as contribution to the existing body of knowledge. It will lead the construction managers to better understand the actual situation of construction waste and devise control measures.

Electricity crisis has become a key issue in Pakistan mainly due to a tenacious and spreading gap between demand and supply. Moreover, the current production is causing severe environmental and energy security issues due to reliance on thermal sources. Stakeholders are hindered to address these issues due to a significant knowledge gap causing discrepancies in power policies. A comprehensive approach over the sustainability dimensions is missing due to non-adoption of life cycle thinking. This study adopts an integrated approach of life cycle sustainability assessment of the electricity sector in Pakistan for proposing policy guidelines and implementation framework to optimize the future energy mixes. In total, 20 sustainability indicators have been assessed covering life cycle of seven electricity generation sources, currently in use. These sources have been ranked by equally weighting the sustainability dimensions and respective indicators. Hydropower is found as the most sustainable option having lowest environmental and economic impacts. While due to worst economic and social impacts, oil is found to be the least sustainable option for the country. While establishing tradeoffs between different electricity generation sources, this study presents an unbiased view and highlights the worth of life cycle approach in sustainability assessment for improving the energy policies.