An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

Food Waste(FW)is a pressing environmental concern that affects every country globally.About one-third of the food that is produced ends up as waste,contributing to the carbon footprint.Hence,the FW must be properly treated to reduce environmental pollution.This study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial aspects.The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection.The SPOTIS method is adopted to rank the alternative hassle-free,following the criteria.The proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an alternative.In addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

Chemical Composition, Antioxidant and Antibacterial Activities of the Essential Oil and Methanol Extract from Mentha Iongifolia L. Hudson from North of Iran

This study was designed to evaluate antimicrobial and antioxidant activities of the essential oil and methanol extract from Mentha longifolia L. hudson. Antioxidant activity was evaluated through 2,2-diphenyl-l-picrylhydrazyl （DPPH） assay and β-carotene/linoleic acid assay. The essential oil and methanol extract were individually tested [disc-diffusion assay and evaluating minimum inhibition concentration （MIC）] against a number of bacteria. The essential oil showed strong antimicrobial activity against bacteria tested whereas the methanol extract almost remained inactive. In contrast, the extract showed much better activity than the essential oil in antioxidant activity assays employed, e.g. in the inhibition of free radical DPPH and β-carotene/linolcic acid systems. In the former, the extract was able to reduce the stable free radical DPPH with an IC50 of 55.3μg/mL while that of the oils were 10,630μg/mL. When compared to BHT （butylated hydroxytoluene）, a synthetic antioxidant, both showed weaker antioxidative potential. Similarly, in β-carotene/linoleic acid assay, these samples were not effectively able to inhibit the linoleic acid oxidation; exhibiting only 24% and 36% inhibitions at 2 mg/mL, respectively; both were far below than that of BHT. Total phenolic constituent of the extract was approximately 4.5 g/100 g as gallic acid equivalent. Gas chromatography-mass spectroscopy （GC-MS） analysis of the oil resulted in the identification of 45 constituents, ei^-piperitone epoxide, pulegone and piperitenone oxide being the main components. The results indicate that essential oil and extract ofM. longifolia L. hudson may be used as natural preservative in food against the agents of foodborne diseases and food spoilage.

Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs

With the growing number of Web services on the internet,there is a challenge to select the best Web service which can offer more quality-of-service(QoS)values at the lowest price.Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet.In this paper,we modify the interval data envelopment analysis(DEA)models[Wang,Greatbanks and Yang(2005)]for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors.We conduct a set of experiments using a synthesized dataset to show the capabilities of the proposed models.The experimental results show that the correlation between the proposed models and the interval DEA models is significant.Also,the proposed models provide almost robust results and represent more stable behavior than the interval DEA models against QoS variations.Finally,we demonstrate the usefulness of the proposed models for QoS-aware Web service composition.Experimental results indicate that the proposed models significantly improve the fitness of the resultant compositions when they filter out unsatisfactory candidate services for each abstract service in the preprocessing phase.These models help users to select the best possible cloud service considering the dynamic internet environment and they help service providers to improve their Web services in the market.

Using Blockchain Technology in Mobile Network to create decentralized Home Location Registry(HLR)

Blockchain can mean many things to many people.It is a set of protocols and encryption technologies for securely storing data on a distributed network for the developers.It is a distributed ledger for business and finance and the technology underlying the explosion of new digital currencies.For technologists,it is the driving force behind the next generation of the internet.On the other hand,it is a transformational technology facilitating large-scale human progress in previously unimagined ways for the rest of the people,a tool for radically reshaping society and economy.Some view it as a disruptive technology that can be the source of a great deal of fraud,illegal activity,where others see opportunities to bring into existing systems by providing decentralization,transparency,and efficiency.This complex technological,economic,and social phenomenon has been the subject of fervent debate.It calls into question what might have been seen to be established parameters of the modern world like currency,economics,trust,value,and exchange.It is a revolutionary new computing paradigm and one of the most significant,fundamental digital platforms’advances since the internet.It is an emergent technology experiencing very rapid evolution,and so is our understanding of what it is and what it can be.This paper is subject to the use of Blockchain concepts in mobile networks to strengthen the Home Location Registry(HLR)database and make it decentralized for secure transactions and in banking and financial centers.Blockchain also holds potential implications for global commerce.It could make trade more efficient by removing the manual and paper-based processes and introducing streamlined and automated processes.

Key Trends in the Global Labor Market

In this study,the globalization of the labor force and its reflections on the labor markets are discussed.In this section,the results of the study will be evaluated.The fact that production can be divided into stages has enabled the production of each stage of production to be produced where it can be produced at the lowest cost internationally,thus production is organized in the form of global value chains.Global value chains have a hierarchical structure based on power relations.At the top of the chain is an oligopolist MNC,while at the very bottom there are a large number of micro-production units that compete against each other with costly competition.This situation causes an asymmetric structure in international markets.The globalization of the workforce is in the form of such a production organization and participation in such international markets.The pressures that transfers to reduce the cost of production make them feel at different intensities depending on the level of labor force being added to a ring in the global value chain.

Adsorption of Natural Surfactant on Sandstone in Enhanced Oil Recovery: Isotherms and Kinetics Studies

In chemical enhanced oil recovery, surfactants are injected into the reservoir with the intention to lower interfacial tension (IFT) between the water and oil phases, and thereby bring about efficient displacement of oil. However, the adsorption of the surfactants to reservoir rock surfaces leads to the loss and reduction in concentration of the surfactants, which in turn reduces the overall efficiency of the oil recovery process, with attendant financial losses. In this work, the adsorption of Quillaja Saponaria (QS), a novel, natural, non-ionic surfactant, on crushed sandstone reservoir rock is investigated. X-ray diffraction (XRD) study of clean sandstone particles has been undertaken to determine the main components present in the sand particles. The conductivity method was used to measure CMC and the surfactant concentrations in aqueous solutions. Batch adsorption experiments were used to determine the amount of QS adsorbed on rock surface. Equilibrium conditions were reached after almost 5 days. From the results of the study, the Langmuir isotherm model is more suited for predicting the adsorption behaviour of QS on sandstone. The kinetic adsorption of QS obeys the pseudo-second order model. This study is particularly relevant in surfactant selection for chemical EOR processes.

Digital economy and carbon dioxide emissions:Examining the role of threshold variables

Considering that previous literature has mainly focused on the impact of the digital economy(DE)on environmental degradation,ignoring the role of natural resources,this study uses two key factors(natural resource rent and anticorruption regulation)as threshold variables to reveal the effect of natural resources on the association between DE and carbon dioxide(CO_(2))emissions.In doing so,the study covers 97 countries,uses annual data between 2003 and 2019,and applies a panel threshold model.The outcomes present that the influence of the DE on CO_(2)emissions has a single-threshold effect(i.e.,there is an inverted U-shaped link between the DE and CO_(2)emissions)when natural resource rent is the threshold variable.Specifically,the DE significantly increases CO_(2)emissions when the natural resource rent is at a low-to-medium level,but the DE suppresses CO_(2)emissions growth when natural resource rent exceeds the threshold.Moreover,the DE drives overall CO_(2)emissions growth when anticorruption regulation is the threshold variable and there are double thresholds for its impact on CO_(2)emissions.Specifically,a rise in anticorruption regulation initially exacerbates the contribution of DE impact on CO_(2)emissions and then weakens it over time.Based on the results,the study proposes various implications,such as formulating a DE development strategy,considering natural resources in the development of the DE,and strengthening anti-corruption efforts in the field of environmental protection.

Do investments in green energy,energy efficiency,and nuclear energy R&D improve the load capacity factor?An augmented ARDL approach

Renewable energy,energy efficiency,and nuclear energy research and development(RER,EER,and NER)budgets are immensely important to fulfill sustainable development goals 7,9,and 13,by accelerating energy innovation,energy transition,and climate control.The literature on the drivers of the load capacity factor(LCF),a recently developed ecological quality measure,is mounting;however,the roles of energy investments in the LCF are largely unknown.Accordingly,this study assesses the impacts of RER,EER,NER,and financial globalization(FIG)on the LCF using data from 1974 to 2018 for Germany.Advanced and reliable time series tests(Augmented ARDL,DOLS,and Fourier causality)are adopted to analyze cointegration,long-run impacts,and causal connections.The outcomes unveil that both green energy and energy efficiency R&D promote the LCF by enhancing ecological quality.However,the positive impact of NER on the LCF is found to be weaker than the impacts of RER and EER.FIG curbs ecological degradation by expanding the LCF.Additionally,the U-shaped connection between economic growth(ECG)and the LCF confirms the load capacity curve.Therefore,policymakers should focus on RER and EER to preserve the environment and promote sustainable growth.

Investigation on tribological performance of CuO vegetable-oil based nanofluids for grinding operations

With ball-bearing and tribofilm lubrication effects,CuO vegetable oil-based nanofluids have exhibited excellent anti-wear and friction reduction properties.In this study,CuO nanofluids were synthesized by a one-step electro discharge process in distilled water containing polysorbate-20 and vegetable oil as a nanoparticle stabilizer and source of fatty-acid molecules in the base fluid,respectively.Pin-on-disk tribotests were conducted to evaluate the lubrication performance of synthesized CuO nanofluids between brass/steel contact pairs under various loadings.Surface grinding experiments under minimum lubrication conditions were also performed to evaluate the effectiveness of the synthesized nanofluids in improving the machining characteristics and surface quality of machined parts.The results of pin-on-disk tests revealed that adding nanofluids containing 0.5%and 1%(mass fraction)CuO nanoparticles to the base fluid reduced the wear rate by 66.7%and 71.2%,respectively,compared with pure lubricant.The lubricating action of 1%(mass fraction)CuO nanofluid reduced the ground surface roughness by up to 30%compared with grinding using lubricant without nano-additives.These effects were attributed to the formation of a lubrication film between the contact pairs,providing the rolling and healing functions of CuO nanoparticles to the sliding surfaces.The micrography of ground surfaces using a scanning electron microscope confirmed the tribological observations.

Abstract Elliptic Equations with Integral Boundary Conditons

This paper focuses on nonlocal integral boundary value problems for elliptic differential-operator equations. Here given conditions guarantee that maximal regularity and Fredholmness in L_p spaces. These results are applied to the Cauchy problem for abstract parabolic equations, its infinite systems and boundary value problems for anisotropic partial differential equations in mixed L_p norm.

Review of application of artificial intelligence techniques in petroleum operations

In the last few years,the use of artificial intelligence(AI)and machine learning(ML)techniques have received considerable notice as trending technologies in the petroleum industry.The utilization of new tools and modern technologies creates huge volumes of structured and un-structured data.Organizing and processing of these information at faster pace for the performance assessment and forecasting for field development and management is continuously growing as an important field of investigation.Various difficulties which were faced in predicting the operative features by utilizing the conventional methods have directed the academia and industry toward investigations focusing on the applications of ML and data driven approaches in exploration and production operations to achieve more accurate predictions which improves decision-making processes.This research provides a review to examine the use cases and application of AI and ML techniques in petroleum industry for optimization of the upstream processes such as reservoir studies,drilling and production engineering.The challenges related to routine approaches for prognosis of operative parameters have been evaluated and the use cases of performance optimizations through employing data-driven approaches resulted in enhancement of decision-making workflows have been presented.Moreover,possible scenarios of the way that artificial intelligence will develop and influence the oil and gas industry and how it may change it in the future was discussed.