Crossover Mechanism Research Articles

Synthetic Approaches to Phosphasugars (2-oxo-1,2-oxaphosphacyclanes) Using the Anomeric Alkoxyl Radical β-Fragmentation Reaction as the Key Step.

The anomeric alkoxyl radical β-fragmentation (ARF) of carbohydrates possessing an electron-withdrawing group (EWG) at C2, promoted by PhI(OAc)2/I2, gives rise to an acyclic iodide through which a pentavalent atom of phosphorus can be introduced via the Arbuzov reaction. After selective hydrolysis and subsequent cyclization, the phosphonate or phosphinate intermediates can be converted into 2-deoxy-1-phosphahexopyranose and 2-deoxy-1-phosphapentopyranose sugars. The ARF of carbohydrates with an electron-donor group (EDG) at C2 proceeds by a radical-polar crossover mechanism, and the cyclization occurs by nucleophilic attack of a conveniently positioned phosphonate or phosphinate group to the transient oxocarbenium ion. This alternative methodology leads to 5-phosphasugars with a 4-deoxy-5-phosphapentopyranose framework. The structure and conformation of the 2-oxo-1,2-oxaphosphinane and 2-oxo-1,2-oxaphospholane ring systems in different carbohydrate models have been studied by NMR and X-ray crystallography.

Vicinal, Double C-H Functionalization of Alcohols via an Imidate Radical-Polar Crossover Cascade.

A double functionalization of vicinal sp3 C-H bonds has been developed, wherein a β amine and γ iodide are incorporated onto an aliphatic alcohol in a single operation. This approach is enabled by an imidate radical chaperone, which selectively affords a transient β alkene that is amino-iodinated in situ. Overall, the radical-polar-crossover cascade entails the following key steps: (i) β C-H iodination via 1,5-hydrogen atom transfer (HAT), (ii) desaturation via I2 complexation, and (iii) vicinal amino-iodination of an in situ generated allyl imidate. The synthetic utility of this double C-H functionalization is illustrated by conversion of aliphatic alcohols to a diverse collection of α,β,γ substituted products bearing heteroatoms on three adjacent carbons. The radical-polar crossover mechanism is supported by various experimental probes, including isotopic labeling, intermediate validation, and kinetic studies.

Analysis of Gas Permeation Phenomena in a PEM Water Electrolyzer Operated at High Pressure and High Current Density

In this study, on-line mass spectrometry is used to determine hydrogen permeation during proton exchange membrane water electrolyzer (PEM-WE) operation for a wide range of current densities (0–6 A cm−2) and operating pressures (1–30 bar, differential pressure). H2 permeation measurements with a permeation cell setup, i.e., without applying a current, show a linear correlation between permeation rate and H2 partial pressure, indicating diffusion as the main crossover mechanism. Measurements with full membrane electrode assemblies (MEAs) during PEM-WE operation reveal a significant increase of the gas permeation rate at high current densities, by up to ≈20-fold at 1 bar H2 and up to ≈1.2-fold at 30 bar H2 (Nafion® 212 or Nafion® 117 membrane; Ir-black (anode) and Pt/C (cathode)). Recently, H2 super-saturation of the ionomer phase in the cathode catalyst layer was shown to be the reason for this increase, and we discuss the impact of this effect for different electrode compositions and operating conditions. Finally, the determined H2 permeation rates and electrolyzer performance are used to discuss the overall PEM-WE efficiency for different membrane thicknesses and it is shown that the formation of an explosive gas mixture in the anode at low current densities requires additional mitigation strategies.

Solving Travelling Salesman Problem (TSP) by Hybrid Genetic Algorithm (HGA)

The Traveling Salesman Problem (TSP) is easy to qualify and describe but difficult and very hard to be solved. There is known algorithm that can solve it and find the ideal outcome in polynomial time, so it is NP-Complete problem. The Traveling Salesman Problem (TSP) is related to many others problems because the techniques used to solve it can be easily used to solve other hard Optimization problems, which allows of circulating it results on many other optimization problems. Many techniques were proposed and developed to solve such problems, including Genetic Algorithms. The aim of the paper is to improve and enhance the performance of genetic algorithms to solve the Traveling Salesman Problem (TSP) by proposing and developing a new Crossover mechanism and a local search algorithm called the Search for Neighboring Solution Algorithm, with the goal of producing a better solution in a shorter period of time and fewer generations. The results of this study for a number of different size standard benchmarks of TSP show that the proposed algorithms that use Crossover proposed mechanism can find the optimum solution for many of these TSP benchmarks by (100%) ,and within the rate (96%-99%) of the optimal solution to some for others. The comparison between the proposed Crossover mechanism and other known Crossover mechanisms show that it improves the quality of the solutions. The proposed Local Search algorithm and Crossover mechanism produce superior results compared to previously propose local search algorithms and Crossover mechanisms. They produce near optimum solutions in less time and fewer generations.

A Disassembly Sequence Planning Method With Team-Based Genetic Algorithm for Equipment Maintenance in Hydropower Station

Disassembly sequence planning (DSP) is an important part of equipment maintenance in a hydropower station. In this paper, the generation of an excellent disassembly sequence (DS) for equipment is studied. Firstly, according to the characteristics of hydropower equipment, a combination node type is added to the directed graph analysis model, and the distance factor of components in space is added to the evaluation function of DS. Secondly, a DSP strategy including the grouping and minimization of the node's scope is adopted to reduce computational complexity. Thirdly, a novel team-based genetic algorithm (TBGA) combining teams, fast feasible solution generator (FFSG), precedence preservative crossover (PPX) mechanism, multi-point heuristic mutation (MHM) mechanism, and forward-and-backward optimization operator (FBOO) is designed for DSP. The proposed TBGA maintains global search capabilities through teams and enhances local search capabilities through individuals. In the evolutionary process, teams, MHM, and FBOO have good complementarity to improve the comprehensive performance of the algorithm. Finally, four experiments are conducted and the performance of TBGA is tested based on the comparison of a well-known genetic algorithm, simplified teaching-learning-based optimization, and simplified swarm optimization algorithm. The results show that the proposed method can get better search results in limited iterations and require only about 25% time of other algorithms.

Smart crossover mechanism for parallel neuroevolution method of medical diagnostic models synthesis

Smart crossover mechanism for parallel neuroevolution method of medical diagnostic models synthesis

σ-Bond initiated generation of aryl radicals from aryl diazonium salts.

σ-Bond nucleophiles and molecular oxygen transform aryl diazonium salts into aryl radicals. Experimental and computational studies show that Hantzsch esters transfer hydride to aryl diazonium species, and that oxygen initiates radical fragmentation of the diazene intermediate to produce aryl radicals. The operational simplicity of this addition-fragmentation process for the generation of aryl radicals, by a polar-radical crossover mechanism, has been illustrated in a variety of bond-forming reactions.

Iron-Catalyzed Meerwein Carbooxygenation of Electron-Rich Olefins: Studies with Styrenes, Vinyl Pyrrolidinone, and Vinyl Oxazolidinone.

The arylative oxygenation of the electron-rich olefins styrene, α-methylstyrene, vinyl pyrrolidinone, and vinyl oxazolidinone was accomplished using arenediazonium salts and catalytic amounts of FeSO4 in an effective single electron transfer radical process. A broad range of aryldiazonium salts was tolerated using water, methanol, or their combination with acetonitrile to furnish the corresponding carbohydroxylated and carbomethoxylated products (42 examples), including functionalized dihydroisocoumarin and dihydrobenzofuran systems in good to excellent yields (up to 88%). The protocols developed for the Fe(II)-catalyzed carbohydroxylation were also compared to Ru(II) and Ir(III) photoredox carbooxygenations of these electron-rich olefins. The Fe(II)-catalyzed process proved to be highly competitive compared to the photoredox and the uncatalyzed processes. The proposed mechanism for the Fe(II)-catalyzed reactions involves the synergic combination with an effective Fe+2/Fe+3 redox system and a radical polar crossover mechanism featuring an unprecedented capture of the reactive N-acyliminium in the case of vinyl pyrrolidinone and vinyl oxazolidinone.

Terminal crossover and steering-based particle swarm optimization algorithm with disturbance

Particle swarm optimization (PSO) is an efficient and simple evolutionary algorithm, which has been successfully applied to solve optimization problems in many real-world fields. Nevertheless, the disadvantage of easy loss of population diversity makes it difficult for particles to jump out of local optimum. The deterioration of population diversity often occurs in the terminal iteration stage. Therefore, to overcome this drawback, terminal crossover and steering-based PSO with distribution(TCSPSO) is proposed in this paper. Firstly, to enhance the diversity of population, a new crossover mechanism is constructed. Meanwhile, in order to make the particle easily jump out of the local optimum, a global disturbance is utilized and the direction of motion of the particle is changed at the later stage. Finally, a nonlinear inertia weight and elastic mechanism are introduced to balance exploration and exploitation better. 34 benchmark functions and two engineering problems are utilized to verify the promising performance of TCSPSO, experimental results and statistical analysis indicate that TCSPSO has competitive performance compared with 15 state-of-the-art algorithms.

I see you in me, and me in you

PurposeBased on the theory of crossover, the purpose of this paper is to explore the limited but growing body of research on positive crossover, wherein the authors investigated the direct and indirect crossover of work passion between the dyadic setting of leader and followers. The authors hypothesized that the leader’s (follower’s) work passion influence follower’s (leader’s) work passion through direct crossover phenomena (i.e. crossover via empathy). In the study, the authors also examined the underlying indirect crossover mechanism of leader’s (follower’s) work passion via personal identification – the process by which individuals (supervisors and subordinates) realize cognitive overlap between the self and other over time in a relationship. In an attempt to fully understand the crossover of leader’s (follower’s) work passion, the authors scrutinized the pattern of leader–follower relationship quality, which has the capacity to moderate the direct and indirect crossover of work passion from leader to follower and vice versa.Design/methodology/approachThe authors conducted two independent studies and collected a time-lagged data from the dyadic settings of a large trade multinational company (n=77 supervisor and 373 subordinates) and a large manufacturing multinational company (n=89 supervisor and 411 subordinates) situated in Anhui province of China to test the authors’ moderated mediation model of work passion.FindingsAs expected the authors found support for all the authors’ hypothesized relationships. Specifically, the results provide support for the notion of direct and indirect crossover of work passion within leader–follower dyads. Moreover, the authors’ findings also support the moderated mediation model of direct and indirect crossover of work passion.Originality/valueOverall, this study provides a potential way to stimulate work passion in employees (leader and followers) from the perspective of their relationship quality with each other. Moreover, implications for theory, research and practice with prospective future research topics are discussed.

A novel genetic algorithm for stable multicast routing in mobile ad hoc networks

Data transmission among multicast trees is an efficient routing method in mobile ad hoc networks (MANETs). Genetic algorithms (GAs) have found widespread applications in designing multicast trees. This paper proposes a stable quality-of-service (QoS) multicast model for MANETs. The new model ensures the duration time of a link in a multicast tree is always longer than the delay time from the source node. A novel GA is designed to solve our QoS multicast model by introducing a new crossover mechanism called leaf crossover (LC), which outperforms the existing crossover mechanisms in requiring neither global network link information, additional encoding/decoding nor repair procedures. Experimental results confirm the effectiveness of the proposed model and the efficiency of the involved GA. Specifically, the simulation study indicates that our algorithm can obtain a better QoS route with a considerable reduction of execution time as compared with existing GAs.

Multi-objective item evaluation for diverse as well as novel item recommendations

Most of the traditional Recommendation Systems (RSs) focus on recommending only the popular items as they deal with a single objective precision/popularity. However, focusing on the diversity of the items in the recommendation list is also equally important to improve its relevance to the user, i.e., it is required to view RSs as a multi-objective optimization problem. Nevertheless, owing to popularity and diversity to be conflicting with each other, it degrades the accuracy of the recommendation list. Therefore, in this work, we use a multi-objective optimization method to maintain a trade-off between the popularity and the diversity and obtain multiple trade-off solutions in a single run. We first incorporate Bhattacharyya Coefficient in an existing nonlinear similarity computation model to create a new similarity model named as Bhat_sim to increase the prediction accuracy of the exiting rating evaluation methods. Further, we formulate a multi-parent crossover mechanism NewCross in the proposed multi-objective recommendation filtering NewCrossPMOEA which preserves the order and the frequency in the parents genes to bring good objectivity in the trade-off of recommending popular and diverse items in the recommendation list. The obtained results on the Movielens dataset demonstrate that the NewCrossPMOEA performs superior in terms of average precision, diversity, and novelty to its competing methods. Moreover, the Pareto-dominance concept of NewCrossPMOEA suggests multiple recommendation solutions of diverse and novel items to the target users in a single run.

The Optimal Energy Dispatch of Cogeneration Systems in a Liberty Market

This paper proposes a novel approach toward solving the optimal energy dispatch of cogeneration systems under a liberty market in consideration of power transfer, cost of exhausted carbon, and the operation condition restrictions required to attain maximal profit. This paper investigates the cogeneration systems of industrial users and collects fuel consumption data and data concerning the steam output of boilers. On the basis of the relation between the fuel enthalpy and steam output, the Least Squares Support Vector Machine (LSSVM) is used to derive boiler and turbine Input/Output (I/O) operation models to provide fuel cost functions. The CO2 emission of pollutants generated by various types of units is also calculated. The objective function is formulated as a maximal profit model that includes profit from steam sold, profit from electricity sold, fuel costs, costs of exhausting carbon, wheeling costs, and water costs. By considering Time-of-Use (TOU) and carbon trading prices, the profits of a cogeneration system in different scenarios are evaluated. By integrating the Ant Colony Optimization (ACO) and Genetic Algorithm (GA), an Enhanced ACO (EACO) is proposed to come up with the most efficient model. The EACO uses a crossover and mutation mechanism to alleviate the local optimal solution problem, and to seek a system that offers an overall global solution using competition and selection procedures. Results show that these mechanisms provide a good direction for the energy trading operations of a cogeneration system. This approach also provides a better guide for operation dispatch to use in determining the benefits accounting for both cost and the environment in a liberty market.

An Improved Genetic Algorithm for Optimal Layout of Flow Meters and Valves in Water Network Partitioning

The paradigm of “divide and conquer” has been well used in Water Distribution Systems (WDSs) zoning planning in recent years. Indeed, Water Network Partitioning (WNP) has played an irreplaceable role in leakage control and pressure management; meanwhile it also has certain drawbacks, such as reduction of the supply reliability of the pipe network system and increased terminal dead water, as a result of the closure of the pipe section. In this paper, an improvement is made to the method proposed by Di Nardo et al. (2013) for optimal location of flow meters and valves. Three improvements to the genetic algorithm are proposed in this work for better and faster optimization in the dividing phase of WNP: preliminary hydraulic analysis which reduces the number of decision variables; modifications to the crossover mechanism to protect the superior individuals in the later stage; and boundary pipe grouping and mutation based on the pipe importance. The objective function considers the master–subordinate relationship when minimizing the number of flow meters and the difference of hydraulic state compared to original WDS. Another objective function of minimizing the deterioration of water quality compared to original WDS is also evaluated. The proposed method is applied for the WNP in a real WDS. Results show that it plays an effective role in the optimization of layout of the flow meters and valves in WNP.

Preparation of Cu nanoparticle‐doped ZIF‐8/RGO composites for effective photodegradation of organic pollutant

Cu nanoparticle‐connected ZIF‐8/reduced graphite oxide (RGO) composite was successfully prepared through a facile hydrothermal reaction using sulfate in this paper. The crossover mechanism of metal nanoparticles loading and RGO decoration to enhance the photocatalytic efficiency of pristine ZIF‐8 was studied. The results showed that the prepared Cu‐S@ZIF‐8/RGO has a strong ability to take advantage of sunlight, indicating an appreciable application prospect. RGO can act as a base to support the whole structure and serve as an electron sink to accept photoexcited electrons, realizing the formation of reactive oxygen species (ROS) and inhibition of electron–hole pair recombination. Cu nanoparticles act as connectors between ZIF‐8 and RGO to transfer electrons and realize the formation of partial ROS on its surface. The doped sulfate radical can promote to extend the utilization of the wavelength range by generating surface states. Cu‐S@ZIF‐8/RGO showed the best photocatalytic activity in simulated sunlight for eliminating rhodamine B and 4‐chlorophenol among all the prepared samples, the structure kept intact even in the presence of different kinds of anions. The crossover study of metal loading and RGO decoration can develop a new way for only UV‐responsive metal–organic frameworks to remove organic contaminants under sunlight irradiation.

Visible-Light-Promoted [5 + 1] Annulation Initiated by Electron-Donor-Acceptor Complexes: Synthesis of Perfluoroalkyl- s-Triazines.

A visible-light-promoted electron-donor-acceptor (EDA) complex-initiated [5 + 1] annulation between biguanides and perfluoroalkyl halides for the construction of perfluoroalkyl- s-triazines has been developed. It was found that both visible light and dioxygen in the air are favorable for the reaction. A radical-polar crossover mechanism was proposed, in which sequential SET, radical combination, HF elimination, electrocyclization, and aromatization are involved.

Copper-catalyzed remote C(sp3)\u2013H azidation and oxidative trifluoromethylation of benzohydrazides

The Hofmann-Löffler-Freytag (HLF) reaction is a prototypical example of radical-based remote functionalization of unactivated C(sp3)–H bond. While 1,5-hydrogen atom transfer (1,5-HAT) of the amidyl radical is thermodynamically favorable and is well-established, the method for the subsequent functionalization of the translocated carbon radical is still limited. We report herein two catalytic remote C(sp3)–H functionalization protocols. Cu(MeCN)4PF6-catalyzed reaction of 2-alkyl benzohydrazides 3 with TMSN3 in the presence of MeCO2OtBu affords the γ-azido amides 4, while CuCl-catalyzed reaction of 3 with Togni’s reagent provides 2-(β-trifluoromethylvinyl)benzamides 5 via an oxidative δ-trifluoromethylation of the alkyl group. Mechanistic studies suggest that the γ-azidation of benzohydrazides 3 goes through 1,5-HAT followed by a Cu-mediated azido transfer cascade, while the oxidative δ-trifluoromethylation of 3 proceeds via, after 1,5-HAT process, a radical-polar crossover mechanism.

An Interpretable Disease Onset Predictive Model Using Crossover Attention Mechanism From Electronic Health Records

Analysis of patients' Electronic Health Records (EHRs) can help guide the prevention of diseases and personalization of treatment. Therefore, it is an important task to predict the disease onset information (referred to as medical codes in this paper) within the upcoming visit based on patients' EHR data. In order to achieve this objective, the real-time nature and high dimensionality of EHR data must be addressed. Moreover, the prediction results of the model must be interpretable. Existing methods mainly use Recurrent Neural Networks (RNNs) to model EHR data and adopt attention mechanism to provide interpretability. However, diagnosis and treatment information have usually been regarded as the same kind of information, the difference and relationship between the two parts being ignored. This has led to unclear analysis about the patient's disease development and inaccurate prediction results. To address this limitation, we propose a CrossOver Attention Model (COAM). This model adopts two RNNs to process diagnosis and treatment information, respectively, and then deploys a crossover attention mechanism to improve prediction accuracy by leveraging the correlation between the two parts of information. It can learn effective representations of personal medical diagnosis and treatment, and provide interpretable prediction results. Experiments demonstrate that COAM can significantly improve the accuracy of prediction and provide clinically meaningful explanations.

Using polymorphism to master the spin crossover mechanism in [Fe(PM-PeA)2(NCSe)2

Polymorphism drives the mechanism of the spin-crossover in [Fe(PM-PeA)2(NCSe)2] single-crystals.

Ab initiostudy of luminescence in Ce-dopedLu2SiO5: The role of oxygen vacancies on emission color and thermal quenching behavior

We study from first principles the luminescence of Lu$_2$SiO$_5$:Ce$^{3+}$ (LSO:Ce), a scintillator widely used in medical imaging applications, and establish the crucial role of oxygen vacancies (V$_O$) in the generated spectrum. The excitation energy, emission energy and Stokes shift of its luminescent centers are simulated through a constrained density-functional theory method coupled with a ${\Delta}$SCF analysis of total energies, and compared with experimental spectra. We show that the high-energy emission band comes from a single Ce-based luminescent center, while the large experimental spread of the low-energy emission band originates from a whole set of different Ce-V$_O$ complexes together with the other Ce-based luminescent center. Further, the luminescence thermal quenching behavior is analyzed. The $4f-5d$ crossover mechanism is found to be very unlikely, with a large crossing energy barrier (E$_{fd}$) in the one-dimensional model. The alternative mechanism usually considered, namely the electron auto-ionization, is also shown to be unlikely. In this respect, we introduce a new methodology in which the time-consuming accurate computation of the band gap for such models is bypassed. We emphasize the usually overlooked role of the differing geometry relaxation in the excited neutral electronic state Ce$^{3+,*}$ and in the ionized electronic state Ce$^{4+}$. The results indicate that such electron auto-ionization cannot explain the thermal stability difference between the high- and low-energy emission bands. Finally, a hole auto-ionization process is proposed as a plausible alternative. With the already well-established excited state characterization methodology, the approach to color center identification and thermal quenching analysis proposed here can be applied to other luminescent materials in the presence of intrinsic defects.