Design of dual-functional protic porous ionic liquids for boosting selective extractive desulfurization

Porous ionic liquids have demonstrated excellent performance in the field of separation,attributed to their high specific surface area and efficient mass transfer.Herein,task-specific protic porous ionic liquids(PPILs)were prepared by employing a novel one-step coupling neutralization reaction strategy for extractive desulfurization.The single-extraction efficiency of PPILs reached 75.0%for dibenzothiophene.Moreover,adding aromatic hydrocarbon interferents resulted in a slight decrease in the extraction efficiency of PPILs(from 45.2%to 37.3%,37.9%,and 33.5%),indicating the excellent extraction selectivity of PPILs.The experimental measurements and density functional theory calculations reveal that the surface channels of porous structures can selectively capture dibenzothiophene by the stronger electrophilicity(Eint(HS surface channel/DBT)=-39.8 kcal mol^(-1)),and the multiple extraction sites of ion pairs can effectively enrich and transport dibenzothiophene from the oil phase into PPILs throughπ...π,C-H...πand hydrogen bonds interactions.Furthermore,this straightforward synthetic strategy can be employed in preparing porous liquids,offering new possibilities for synthesizing PPILs with tailored functionalities.

Molecular engineering binuclear copper catalysts for selective CO_(2) reduction to C_(2) products

Molecular copper catalysts serve as exemplary models for correlating the structure-reaction-mechanism relationship in the electrochemical CO_(2) reduction(eCO_(2)R),owing to their adaptable environments surrounding the copper metal centres.This investigation,employing density functional theory calculations,focuses on a novel family of binuclear Cu molecular catalysts.The modulation of their coordination configuration through the introduction of organic groups aims to assess their efficacy in converting CO_(2) to C_(2)products.Our findings highlight the crucial role of chemical valence state in shaping the characteristics of binuclear Cu catalysts,consequently influencing the eCO_(2)R behaviour,Notably,the Cu(Ⅱ)Cu(Ⅱ)macrocycle catalyst exhibits enhanced suppression of the hydrogen evolution reaction(HER),facilitating proton trans fer and the eCO_(2)R process.Fu rthermore,we explo re the impact of diverse electro n-withdrawing and electron-donating groups coordinated to the macrocycle(R=-F,-H,and-OCH_3)on the electron distribution in the molecular catalysts.Strategic placement of-OCH_3 groups in the macrocycles leads to a favourable oxidation state of the Cu centres and subsequent C-C coupling to form C_(2) products.This research provides fundamental insights into the design and optimization of binuclear Cu molecular catalysts for the electrochemical conversion of CO_(2) to value-added C_(2) products.

Understanding the individual with Alzheimer’s disease: Can socioemotional selectivity theory guide us?

Individuals often get lost behind the diagnosis of Alzheimer’s disease (AD) while widespread differences between these patients are morecommon than similarities. Socioemotional Selectivity Theory (SST) suggests that as we age our goals change from future-oriented (acquiringnew information) to present-oriented (enhancing the emotional, especially positive, meaning of encounters). The goal of the current article is to examine whether the principles of SST might also apply for people with AD. Some aspects of SST are found especially in the early stages of AD when awareness is often intact and cognitive impairment is relatively limited. This review has clinical significance for the treatment of AD because it focuses on what is important to the individual rather than treating patients as a homogenous group. It also highlights the importance of social networks and emphasizes the role of the proxy in AD care. Lastly, it suggests that if those with AD (like the healthy elderly) have a positivity bias then positive emotional stimuli/wording/instructions could usefully be employed in their daily treatment. I suggest that SST may be a useful starting point when attempting to address what matters to individuals with AD and conclude by providing a few suggestions for future studies.

Integrity of Four Theories on Natural Selection Unit

[Objective] The aim was to study the internal relationship of the four theories on natural selection unit. [Method] The value field of fitness of heterozygote was investigated by constructing mathematical models, to clarify the internal relations of the four theories on natural selection unit. [Result] According to mathematical modes constructed in the study, only the mutated genes meet the requirements of natural selection on heterozygous and homozygous aspects, as well as show high fitness in heterozygous condition, could the mutated genes be kept, giving consideration to both individual and population adaptation. Thus, this methodology theoretically inte- grates the theories of individual selection, collective selection, and genetic selection as well as Kimura＇s neutral theory of health information. [Conclusion] The result of this study suggested that the four theories on natural selection unit can co-exist, and share common premises.

MULTIPLE ATTRIBUTE NETWORK SELECTION ALGORITHM BASED ON AHP AND SYNERGETIC THEORY FOR HETEROGENEOUS WIRELESS NETWORKS

It is a hot issue in communication research field to select the best network for Heterogeneous Wireless Networks(HWNs),and it is also a difficult problem to reduce the handoff number of vertical handoff.In order to solve this problem,the paper proposes a multiple attribute network selection algorithm based on Analytic Hierarchy Process(AHP)and synergetic theory.The algorithm applies synergetics to network selection,considering the candidate network as a compound system composed of multiple attribute subsystems,and combines the subsystem order degree with AHP weight to obtain entropy of the compound system,which is opposite the synergy degree of a network system.The greater the synergy degree,the better the network performance.The algorithm takes not only the coordination of objective attributes but also Quality of Service(QoS)requirements into consideration,ensuring that users select the network with overall good performance.The simulation results show that the proposed algorithm can effectively reduce the handoff number and provide uses with satisfactory QoS according to different services.

Theoretical Study of Hydration Effects on the Selectivity of 18-Crown-6 Between K~＋ and Na~＋

A combination of molecular dynamics （MD） and density functional theory （DFT） calculations were used to study the hydration structures of K＋ and Na＋ ions under the confinement of 18-crown-6 in order to identify the role of water in the selectivity of 18-crown-6 towards K＋.The radial distribution functions,coordination num-bers,orientation structures and interaction energies were analyzed to investigate the hydration of K＋ and Na＋ in 18-crown-6/cation complexes.All calculations of K＋ and Na＋ in bulk water were also conducted for comparison.The simulation results show that the orientation distributions of the water molecules in the first coordination shell of K＋ are more sensitive to the confinement of 18-crown-6 than those of Na＋.It is more favorable to confine a K＋ in 18-crown-6 than a Na＋ in terms of interaction energy.Good agreement is obtained between MD results and DFT results.

Uncertainty Theory Based Novel Multi-Objective Optimization Technique Using Embedding Theorem with Application to R &D Project Portfolio Selection

This paper introduces a novice solution methodology for multi-objective optimization problems having the coefficients in the form of uncertain variables. The embedding theorem, which establishes that the set of uncertain variables can be embedded into the Banach space C[0, 1] × C[0, 1] isometrically and isomorphically, is developed. Based on this embedding theorem, each objective with uncertain coefficients can be transformed into two objectives with crisp coefficients. The solution of the original m-objectives optimization problem with uncertain coefficients will be obtained by solving the corresponding 2 m-objectives crisp optimization problem. The R & D project portfolio decision deals with future events and opportunities, much of the information required to make portfolio decisions is uncertain. Here parameters like outcome, risk, and cost are considered as uncertain variables and an uncertain bi-objective optimization problem with some useful constraints is developed. The corresponding crisp tetra-objective optimization model is then developed by embedding theorem. The feasibility and effectiveness of the proposed method is verified by a real case study with the consideration that the uncertain variables are triangular in nature.

Influential Factors in Employment Location Selection Based on “Push-Pull” Migration Theory—A Case Study in Three Gorges Reservoir Area in China

In China, farmers employed in non-farm work have become important socio-economic actors, but few studies have examined the farmers' perspective in making their work location choices. Based on "push-pull" migration theory, this paper utilizes sectional data from a 2013 survey of farmers in China's Three Gorges Reservoir area to empirically analyze the factors influencing migrant workers' choice of employment location. The results indicate that 60.46% of laborers have migrated from their home province, whereas 39.54% have remained in their home province. Focusing on personal, household, and community characteristics—in addition to the economic characteristics of the sample counties—multinomial logistic regression models reveal that farmer-laborers' employment location decisions are influenced by their personal capital endowment(age, years of education and social networks), family structure(the number of laborers, elders, children and students), home village characteristics(location, economic development level and the degree of relief of the land) and home county economic development level. Notably, male and female laborers' location decisions reveal a converging trend, and their differences are not pronounced. Per capita arable land area has little influence on location decisions, whereas the educational level of laborers has a significant impact. The results differ significantly from those found in previous studies.

Game theory model of exit selection in pedestrian evacuation considering visual range and choice firmness

Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much information a pedestrian can perceive,thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit.Besides,the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed.By integrating game theory into a cellular automata simulation framework,the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper.A systematic analysis of the key factors influencing pedestrian evacuation is conducted,including visual radius and choice firmness of a pedestrian,initial crowd distribution of the room,exit layout as well as exit width.It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering,which is adverse to evacuation.The longer the pedestrian's visual radius,the earlier the pedestrian can determine his/her final selection of the exit.Compared with the scenario where the pedestrians are randomly distributed,pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits.Furthermore,the exit layout and exit width also have a certain influence on pedestrian evacuation process.The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.

Balancing the Activity and Selectivity of Propane Oxidative Dehydrogenation on NiOOH(001)and(010)

Propane oxidative dehydrogenation(ODH)is an energy-efficient approach to produce propylene.However,ODH suff ers from low propylene selectivity due to a relatively higher activation barrier for propylene formation compared with that for further oxidation.In this work,calculations based on density functional theory were performed to map out the reaction pathways of propane ODH on the surfaces(001)and(010)of nickel oxide hydroxide(NiOOH).Results show that propane is physisorbed on both surfaces and produces propylene through a two-step radical dehydrogenation process.The relatively low activation barriers of propane dehydrogenation on the NiOOH surfaces make the NiOOH-based catalysts promising for propane ODH.By contrast,the weak interaction between the allylic radical and the surface leads to a high activation barrier for further propylene oxidation.These results suggest that the catalysts based on NiOOH can be active and selective for the ODH of propane toward propylene.

Using Extension Theory and Fuzzy Analytic Hierarchy Process on Heterogeneous Wireless Network Selection Algorithm

In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analytic hierarchy process （FAHP） is proposed in this paper. In addition, user and operator codetermine the optimal network using the proposed algorithm, which can give consideration to user and operator benefits. The fuzzy judgment matrix is coustructed by membership degree of decision factors which is calculated according to extension theory. The comprehensive weight of each decision factor is obtained using FAHP. Finally, the optimal network is selected through total property value ranldng of each candidate network under user preference and operator preference. The simulation results show that the proposed algorithm can select the optimal network efficiently and accurately, satisfy user preference, and implement load balance between networks.

Synergistic Effect of Metal Doping and Tethered Ligand Promoted High-Selectivity Conversion of CO_(2)to C_(2)Oxygenates at Ultra-Low Potential

Effectively controlling the selectivity of C_(2) oxygenates is desirable for electrocatalytic CO_(2) reduction.Copper catalyst has been considered as the most potential for reducing CO_(2) to C_(2) products,but it still suffers from low C_(2) selectivity,high overpotential,and competitive hydrogen evolution reaction(HER).Here,we propose a design strategy to introduce a second metal that weakly binds to H and a functional ligand that provides hydrogen bonds and protons to achieve high selectivity of C_(2)oxygenates and effective suppression of HER on the Cu(100)surface simultaneously.Seven metals and eleven ligands are screened using first-principles calculations,which shows that Sn is the most efficient for inhibiting HER and cysteamine(CYS)ligand is the most significant in reducing the limiting potential of^(*)CO hydrogenation to^(*)CHO.In the post C-C coupling steps,a so-called“pulling effect”that transfers H in the CYS ligand as a viable proton donor to the C_(2)intermediate to form an H bond,can further stabilize the OH group and facilitate the selection of C_(2)products toward oxygenates.Therefore,this heterogeneous electrocatalyst can effectively reduce CO_(2)to ethanol and ethylene glycol with an ultra-low limiting potential of-0.43 V.This study provides a new strategy for effectively improving the selectivity of C_(2)oxygenates and inhibiting HER to achieve advanced electrocatalytic CO_(2)reduction.

Efficient Virtual Network Embedding Algorithm Based on Restrictive Selection and Optimization Theory Approach

Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.

Engine Selection Based on Utility Theory

Since an engine is seen as the″heart″of an airplane,the objective and scientific evaluation of it is significant to ensure normal operation of airlines.Aiming at the limitations of current studies on selecting engines,a quantitative comprehensive evaluation system of engine options was established and an optimization model based on the utility theory and analytic hierarchy process(AHP)was proposed.Considering the judgement of different customers on the balance between income and risk,the utility of each evaluation index was determined by utilizing the piecewise utility function.The AHP was used to analyze individual demands of customers.Finally,the optimal scheme was selected through calculating the weighted utility value.According to the actual needs of a domestic airline,the utility of three engine options was calculated.The results showed that the value of risk factor can be set to determine the selection scheme based on the degree of preferences(conservative type,neutral type or adventurous type).

Reasonable Drive Selecting of Parallel Mechanisms Based on Screw Theory

By rigidizing the input joints, all possible combinations of drive selecting for the 4-PPPS parallel mechanism are analyzed based on the screw theory in this paper, and the five of them are proved to be reasonable. Then choosing the one as mechanical actuators, the workspace of the 4-PPPS parallel mechanism is deduced according to the rational input scheme. Finally the rationality of input scheme for this mechanism is identified on the basis of the continuity of the workspace.

Use of Rough Sets Theory in Point Cluster and River Network Selection

In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network (TIN), Voronoi diagram, etc.;second, we manually assign decisional attributes to the information table according to conditional attributes. In doing so, the spatial information and attribute information are integrated together to evaluate the importance of points and rivers by rough sets theory. Finally, we select the point cluster and the river network in a progressive manner. The experimental results show that our method is valid and effective. In comparison with previous work, our method has the advantage to adaptively consider the spatial and attribute information at the same time without any a priori knowledge.

Unlocking the Network Traffic Password of the Sudden Popularity of Oriental Selection:Consumer Behavior Decision-Making Mechanism Based on Mental Accounting Theory

This paper explores the decision-making mechanism of the consuming behavior hidden behind the sudden popularity of the Oriental Selection Company in terms of the mental accounting theory.Firstly,according to the“Non-alternative”characteristics of mental accounting,this paper expounds how the strategy of the bilingual live-streaming of Oriental Selection promoters stimulates consumers’desire to buy the advertised products and services whilst using the utility theory of mental accounting to analyze how Oriental Selection promoters improve consumers’acquisition utility and total utility.Secondly,we sum up the successful experiences of Oriental Selection:The live-streaming industry should apply the theory of mental accounting in effectively overcoming the shortcomings of the live-streamed marketing by stimulating consumers’desire and influencing their decision-making behavior through the streaming of content that triggers them to make purchases.This is achievable by abandoning the traditional ways of loudly urging consumers to buy goods.Finally,this paper puts forward some suggestions on how to use the mental accounting theory in promoting sustainable consumption and points out the prospects for Oriental Selection.

Building up a general selection strategy and catalytic performance prediction expressions of heteronuclear double-atom catalysts for N_(2)reduction

The severe environmental problems and the demand for energy urgently require electrocatalysis to replace Haber-Bosch for the nitrogen reduction reaction(NRR).The descriptors and important properties of single-atom and homonuclear double-atom catalysts have been preliminarily explored,but the relationship between the inherent properties and catalytic activity of heteronuclear double-atom catalysts with better performance remains unclear.Therefore,it is very significant to explore the prediction expressions of catalytic activity of heteronuclear double-atom catalysts based on their inherent properties and find the rule for selecting catalytic centers.Herein,by summarizing the free energy for the key steps of NRR on 55 catalysts calculated through the first-principle,the expressions of predicting the free energy and the corresponding descriptors are deduced by the machine learning,and the strategy for selecting the appropriate catalytic center is proposed.The selection strategy for the central atom of heteronuclear double-atom catalysts is that the atomic number of central B atom should be between group VB and VIIIB,and the electron difference between central A atom and B atom should be large enough,and the selectivity of NRR or hydrogen evolution reaction(HER)could be calculated through the prediction formula.Moreover,five catalysts are screened to have low limiting potential and excellent selectivity,and are further analyzed by electron transfer.This work explores the relationship between the inherent properties of heteronuclear double-atom catalysts and the catalytic activity,and puts forward the rules for selecting the heteronuclear double-atom catalytic center,which has guiding significance for the experiment.

An Extended Fuzzy-DEMATEL System for Factor Analyses on Social Capital Selection in the Renovation of Old Residential Communities

China has been promoting the renovation of old residential communities vigorously.Due to the financial pressure of the government and the sustainability of the renovation of old residential communities,public-private partnerships(PPP)have already gained attention.The selection of social capital is key to improving the efficiency of the PPP model in renovating old residential communities.In order to determine the influencing factors of social capital selection in the renovation of old residential communities,this paper aims to find an effective approach and analyze these factors.In this paper,a fuzzy decision-making and trial evaluation laboratory(fuzzy-DEMATEL)technique is extended and amore suitable systemis developed for the selection of social capital using the existing group decisionmaking theory.In the first stage,grounded theory is used to extract the unabridged key influencing factors for social capital selection in the renovation of old residential communities.Secondly,by considering the impact of expert weights,the key influencing factors are identified.The interactions within these influencing factors are discussed and the credibility of the results is verified by sensitivity analysis.Finally,these key influencing factors are sorted by importance.Based on the results,the government should focus on a technical level,organizationalmanagement abilities,corporate reputation,credit status,etc.This study provides the government with a theoretical basis and a methodology for evaluating social capital selection.

Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.