Towards multifunctional landscapes coupling low carbon feed and bioenergy production with restorative agriculture: Economic deployment potential of grass-based biorefineries

Grass-based biomass from grasslands can be used as feedstock in green biorefineries (GBs) that produce a range of biobased products. In addition, adjustments made as part of crop rotation to increase areas under temporary grasslands can yield benefits such as carbon sequestration, increased soil productivity, reduced eutrophication and reduced need for pesticides. In this paper, a flexible modeling framework is developed to analyze the deployment options for GBs that use grass–clover to produce protein feed and feedstock for bioenergy. The focus is placed on optimal deployment, considering system configuration and operation, as well as land use changes designed to increase grass–clover cultivation on cropland. A case study involving 17 counties in Sweden showed that the deployment of GB systems could support biomethane and protein feed production corresponding to 5–60 and 13–154%, respectively, of biomethane and soybean feed imports to Sweden in 2020

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Investment planning and strategic management of sustainable systems for clean power generation: An epsilon-constraint based multi objective modelling approach

Biomass based energy production has been considered as a part of the solution to energy crisis, which is mainly caused by diminishing fossil fuel resources and environmental pollution from traditional fossil fuel based energy production systems. Therefore, it is important to design sustainable and effective systems for biomass based energy production to provide competitive advantage on fossil fuel resourced systems. This study develops a novel optimization model to aid investment planning and strategic management of biomass based clean power generation systems. The model integrates the location, capacity and technology decisions to find the optimal combination of bioenergy production systems to meet electricity demand of particular regions and accounts for multiple biomass types and power technologies. The modelling approach and data analysis are presented to outline the important characteristics of the problem for minimization of the supply chain cost and minimization of the greenhouse gas (GHG) emissions simultaneously. To handle the multi objective problem efficiently, an integrated approach based on fuzzy decision making and epsilon-constraint method is proposed and used, considering both sustainability aspects and uncertainties in the system parameters. The viability of the proposed approach is explored on a case study of Izmir region in Turkey. Different supply chain configuration alternatives are provided for the case study region considering various weights for objective functions representing relative importance of each objective. Corresponding supply chain performance measures in terms of total cost and GHG emissions are proposed and discussed for each configuration alternative. Further enviro-economic analyses denote that discounted investment cost and GHG emissions associated with energy production activities receive the biggest shares in the total cost and in the total GHG emissions, respectively. The government and private investors can employ the model and solution algorithm to design the most cost effective and environment friendly supply chain, to monitor the economic and environmental performance of the current biomass based supply chains and identify policies to support a viable, profitable and eco-friendly energy industry. (C) 2016 Elsevier Ltd. All rights reserved

Ultrasound assisted extraction of polysaccharides from hazelnut skin

WOS: 000371096700003PubMed ID: 25680369In this study ultrasound assisted extraction (UAE) of polysaccharides from hazelnut skin has been studied. Optimum sonication time has been evaluated depending on responses such as amount of carbohydrate and dried sample and thermogravimetric analysis. Chemical and structural properties of extracted material have been determined by Fourier transform spectroscopy attenuated-total reflectance (FTIR-ATR) spectroscopy. Pretreated hazelnut skin powders were extracted in distilled water. Mixture was sonicated by ultrasonic processor probe for 15, 30, 45, 60, 90, and 120min. The results of UAE showed that maximum ethanol insoluble extracts in 60min and the highest dry matter content could be obtained in 120min extraction. Although total carbohydrate content of ethanol insoluble dry extract decreased with time, total carbohydrate in ethanol soluble fraction increased. Polysaccharides extracted from hazelnut skin were assumed to be pectic polysaccharide according to the literature survey of FTIR analysis result. Application time of UAE has an important effect on extraction of polysaccharide from hazelnut skin. This affect could be summarized by enhancing extraction yield up to critical level. Decrease of the yield in ethanol insoluble part could be explained by polymer decomposition. Most suitable model was hyperbolic model by having the lowest root mean square error and the highest R-2 values.Celal Bayar University Scientific Research Project DepartmentCelal Bayar University [2014/04]Financial requirement of this study was supported by Celal Bayar University Scientific Research Project Department (No: 2014/04)

Improved decisions for marketing, supply and purchasing: Mining big data through an integration of sentiment analysis and intuitionistic fuzzy multi criteria assessment

This study proposes a novel decision support system for product ranking problems which integrates multi criteria decision making (MCDM) and aspect level sentiment analysis techniques. The main purpose of the developed methodology is to rank the alternative products taking into account a set of product criteria and the customer comments related to these criteria posted on websites to recommend the most appropriate alternative to potential customers. The decision support system comprises two stages, in the first stage, the online customer reviews are transformed into customer satisfaction scores through aspect level sentiment analysis to obtain performance scores corresponding to alternative products, whereas the second stage deals with ranking the alternative products via a novel MCDM methodology, namely "IF-ELECTRE integrated with VIKOR" according to the performance scores obtained in the first level. Intuitionistic fuzzy sets (IFSs) are utilized to effectively represent the customer reviews including hesitant expressions in decision matrix. The weights of criteria (the product aspects of significant importance for customers) are determined using entropy method. The applicability of the developed approach is explored by a case study, in which customer reviews about hotel experiences are evaluated using lexicon based sentiment analysis and alternative hotels are ranked according to the findings from the sentiment analysis by the Intuitionistic fuzzy (IF)-ELECTRE integrated with VIKOR methodology

Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach

This study aims to develop a comprehensive decision model for sustainable design of biomass based renewable energy supply chains and district heating systems (DHS) with thermal energy storages. The model integrates the strategic decisions such as location and capacity selection for energy plants, DHS, thermal storages and biomass storages with tactical decisions related to biomass production, supply and transportation planning, inventory management and energy production. The main purpose is to find the optimum configuration of the supply chain and DHS to meet the heat demand of a particular locality. The model combines cost and service level objectives and accounts for biomass supply, material flow, capacity, demand and technical constraints. The problem is formulated as a fuzzy Mixed Integer Linear Programming (MILP) model that comprises multiple biomass types and system uncertainties. To explore the viability of the proposed model, computational experiments are performed on a real-world case. Sensitivity analyses are conducted to examine the impacts of cost and capacity limit of thermal energy storage, as well as heat demand, on the objective functions and thermal storage capacity. The results reveal that the proposed model can effectively be used in practice to assist the decision makers in planning energy production systems in a sustainable and effective manner. (C) 2016 Elsevier Ltd. All rights reserved

A novel outranking based multi criteria group decision making methodology integrating ELECTRE and VIKOR under intuitionistic fuzzy environment

This study proposes a new group decision making (GDM) methodology to solve outranking problems efficiently under uncertainty integrating multi criteria decision making (MCDM) and intuitionistic fuzzy set (IFS) theory. To this aim, ELECTRE I, an outranking based MCDM approach is extended with VIKOR method, an ideal solution based approach, under intuitionistic fuzzy environment. The methodology utilizes pairwise comparison and outranking relation concepts of ELECTRE methods to construct different concordance and discordance sets in order to reflect preferences of decision makers effectively. By the help of similarities between concordance and discordance characteristics of ELECTRE and maximum group utility and minimum individual regret characteristics of VIKOR, the methodology enables the intuitionistic fuzzy ELECTRE to overcome its weakness in ranking process and presents complete ranking. In addition, this study employs entropy method to identify the weights of criteria and decision makers, and weighted distance approach to determine the weights of different concordance sets. Utilizing these methods leads to specifying these weights objectively. The applicability of the proposed approach is explored by an illustrative example on supplier selection problem by explaining the method step by step. Furthermore, four computational experiments are conducted in order to demonstrate its applicability to the other areas and the results are compared. (C) 2018 Elsevier Ltd. All rights reserved