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Evolutionary meta-algorithms for pulse shaping of broadband femtosecond duration laser pulses are proposed. The genetic algorithm searching the evolutionary landscape for desired pulse shapes consists of a population of waveforms (genes), each made from two concatenated vectors, specifying phases and magnitudes, respectively, over a range of frequencies. Frequency domain operators such as mutation, twopoint crossover average crossover, polynomial phase mutation, creep and three-point smoothing as well as a time-domain crossover are combined to produce fitter offsprings at each iteration step. The algorithm applies roulette wheel selection; elitists and linear fitness scaling to the gene population. A differential evolution (DE) operator that provides a source of directed mutation and new wavelet operators are proposed. Using properly tuned parameters for DE, the meta-algorithm is used to solve a waveform matching problem. Tuning allows either a greedy directed search near the best known solution or a robust search across the entire parameter space. [PUBLICATION ABSTRACT]

Repairing DNA double-strand breaks (DSBs) with homologous chromosomes as templates is the hallmark of meiosis. The critical outcome of meiotic homologous recombination is crossovers, which ensure faithful chromosome segregation and promote genetic diversity of progenies. Crossover patterns are tightly controlled and exhibit three characteristics: obligatory crossover, crossover interference, and crossover homeostasis. Aberrant crossover patterns are the leading cause of infertility, miscarriage, and congenital disease. Crossover recombination occurs in the context of meiotic chromosomes, and it is tightly integrated with and regulated by meiotic chromosome structure both locally and globally. Meiotic chromosomes are organized in a loop-axis architecture. Diverse evidence shows that chromosome axis length determines crossover frequency. Interestingly, short chromosomes show different crossover patterns compared to long chromosomes. A high frequency of human embryos are aneuploid, primarily derived from female meiosis errors. Dramatically increased aneuploidy in older women is the well-known \"maternal age effect.\" However, a high frequency of aneuploidy also occurs in young women, derived from crossover maturation inefficiency in human females. In addition, frequency of human aneuploidy also shows other age-dependent alterations. Here, current advances in the understanding of these issues are reviewed, regulation of crossover patterns by meiotic chromosomes are discussed, and issues that remain to be investigated are suggested.

Cloud computing promises elasticity, flexibility and cost-effectiveness to satisfy service level agreement conditions. The cloud service providers should plan and provision the computing resources rapidly to ensure the availability of infrastructure to match the demands with closed proximity. The workload prediction has become critical as it can be helpful in managing the infrastructure effectively. In this paper, we present a workload forecasting framework based on neural network model with supervised learning technique. An improved and adaptive differential evolution algorithm is developed to improve the learning efficiency of predictive model. The algorithm is capable of optimizing the best suitable mutation operator and crossover operator. The prediction accuracy and convergence rate of the learning are observed to be improved due to its adaptive behavior in pattern learning from sampled data. The predictive model’s performance is evaluated on four real-world data traces including Google cluster trace and NASA Kennedy Space Center logs. The results are compared with state-of-the-art methods, and improvements up to 91%, 97% and 97.2% are observed over self-adaptive differential evolution, backpropagation and average-based workload prediction techniques, respectively.

Genetic algorithm (GA) is an artificial intelligence search method that uses the process of evolution and natural selection theory and is under the umbrella of evolutionary computing algorithm. It is an efficient tool for solving optimization problems. Integration among (GA) parameters is vital for successful (GA) search. Such parameters include mutation and crossover rates in addition to population that are important issues in (GA). However, each operator of GA has a special and different influence. The impact of these factors is influenced by their probabilities; it is difficult to predefine specific ratios for each parameter, particularly, mutation and crossover operators. This paper reviews various methods for choosing mutation and crossover ratios in GAs. Next, we define new deterministic control approaches for crossover and mutation rates, namely Dynamic Decreasing of high mutation ratio/dynamic increasing of low crossover ratio (DHM/ILC), and Dynamic Increasing of Low Mutation/Dynamic Decreasing of High Crossover (ILM/DHC). The dynamic nature of the proposed methods allows the ratios of both crossover and mutation operators to be changed linearly during the search progress, where (DHM/ILC) starts with 100% ratio for mutations, and 0% for crossovers. Both mutation and crossover ratios start to decrease and increase, respectively. By the end of the search process, the ratios will be 0% for mutations and 100% for crossovers. (ILM/DHC) worked the same but the other way around. The proposed approach was compared with two parameters tuning methods (predefined), namely fifty-fifty crossover/mutation ratios, and the most common approach that uses static ratios such as (0.03) mutation rates and (0.9) crossover rates. The experiments were conducted on ten Traveling Salesman Problems (TSP). The experiments showed the effectiveness of the proposed (DHM/ILC) when dealing with small population size, while the proposed (ILM/DHC) was found to be more effective when using large population size. In fact, both proposed dynamic methods outperformed the predefined methods compared in most cases tested.

Radical-polar crossover (RPC) reaction bridges the gap between one- and two-electron reactivities, thus providing an ideal solution to overcome the limitations of both radical and polar chemistry. In this manifold, organic electrochemistry provides a uniquely facile strategy to access a diverse array of radical intermediates, thus broadening the chemical space of the RPC concept. This review highlights the synthetic advances in the field of electrochemical RPC reactions since 2020, with an emphasis on the substrate scope, reaction limitation and mechanistic aspect. The related RPC reactions are categorized as net-oxidative, net-reductive, or redox neutral transformations.

The selection of proper suppliers is one of the most complicated works of the purchasing department. Today, supplier selection includes different conflicting objectives. Because of contradictory multi-objective supplier selection is solving by using decision-making technique. This paper is presented a modified genetic algorithm by using a combination of crossover operators, Order crossover (OX), Simulated binary crossover (SBX) to assign the optimal order quantities to each supplier, with criteria of transportation cost, product quality, and delivery time with a quantity discount. The result shows that the modified genetic algorithm is an allocated optimal order for multi vendors with improves quality as well as less computational times.

During meiosis, crossovers (COs) are typically required to ensure faithful chromosomal segregation. Despite the requirement for at least one CO between each pair of chromosomes, closely spaced double COs are usually underrepresented due to a phenomenon called CO interference. Like Mus musculus and Saccharomyces cerevisiae, Arabidopsis thaliana has both interference-sensitive (Class I) and interference-insensitive (Class II) COs. However, the underlying mechanism controlling CO distribution remains largely elusive. Both AtMUS81 and AtFANCD2 promote the formation of Class II CO. Using both AtHEI10 and AtMLH1 immunostaining, two markers of Class I COs, we show that AtFANCD2 but not AtMUS81 is required for normal Class I CO distribution among chromosomes. Depleting AtFANCD2 leads to a CO distribution pattern that is intermediate between that of wild-type and a Poisson distribution. Moreover, in Atfancm, Atfigl1, and Atrmi1 mutants where increased Class II CO frequency has been reported previously, we observe Class I CO distribution patterns that are strikingly similar to Atfancd2. Surprisingly, we found that AtFANCD2 plays opposite roles in regulating CO frequency in Atfancm compared with either in Atfigl1 or Atrmi1. Together, these results reveal that although AtFANCD2, AtFANCM, AtFIGL1, and AtRMI1 regulate Class II CO frequency by distinct mechanisms, they have similar roles in controlling the distribution of Class I COs among chromosomes.

A multi‐objective genetic algorithm (MOGA) is a powerful global optimization tool, but its results are considerably affected by the crossover parameter ηc. Finding an appropriate ηc demands too much computing time because MOGA needs be run several times in order to find a good ηc. In this paper, a self‐adaptive crossover parameter is introduced in a strategy to adopt a new ηc for every generation while running MOGA. This new scheme has also been adopted for a multi‐generation Gaussian process optimization (MGGPO) when producing trial solutions. Compared with the existing MGGPO and MOGA, the MGGPO and MOGA with the new strategy show better performance in nonlinear optimization for the design of low‐emittance storage rings. A self‐adaptive crossover parameter is introduced in a strategy to adopt a new ηc for every generation while running a multi‐objective genetic algorithm.

BACKGROUND: Neuropathic pain (NeP), redefined as pain caused by a lesion or a disease of the somatosensory system, is a disabling condition that affects approximately two million Canadians. OBJECTIVE: To review the randomized controlled trials (RCTs) and systematic reviews related to the pharmacological management of NeP to develop a revised evidence‐based consensus statement on its management. METHODS: RCTs, systematic reviews and existing guidelines on the pharmacological management of NeP were evaluated at a consensus meeting in May 2012 and updated until September 2013. Medications were recommended in the consensus statement if their analgesic efficacy was supported by at least one methodologically sound RCT (class I or class II) showing significant benefit relative to placebo or another relevant control group. Recommendations for treatment were based on the degree of evidence of analgesic efficacy, safety and ease of use. RESULTS: Analgesic agents recommended for first‐line treatments are gabapentinoids (gabapentin and pregabalin), tricyclic antidepressants and serotonin noradrenaline reuptake inhibitors. Tramadol and controlled‐release opioid analgesics are recommended as second‐line treatments for moderate to severe pain. Cannabinoids are now recommended as third‐line treatments. Recommended fourth‐line treatments include methadone, anticonvulsants with lesser evidence of efficacy (eg, lamotrigine, lacos‐amide), tapentadol and botulinum toxin. There is support for some analgesic combinations in selected NeP conditions. CONCLUSIONS: These guidelines provide an updated, stepwise approach to the pharmacological management of NeP. Treatment should be individualized for each patient based on efficacy, side‐effect profile and drug accessibility, including cost. Additional studies are required to examine head‐to‐head comparisons among analgesics, combinations of analgesics, long‐term outcomes and treatment of pediatric, geriatric and central NeP.

Meiotic crossovers (COs) have intriguing patterning properties, including CO interference, the tendency of COs to be well-spaced along chromosomes, and heterochiasmy, the marked difference in male and female CO rates. During meiosis, transverse filaments transiently associate the axes of homologous chromosomes, a process called synapsis that is essential for CO formation in many eukaryotes. Here, we describe the spatial organization of the transverse filaments in Arabidopsis (ZYP1) and show it to be evolutionary conserved. We show that in the absence of ZYP1 ( zyp1a zyp1b null mutants), chromosomes associate in pairs but do not synapse. Unexpectedly, in absence of ZYP1, CO formation is not prevented but increased. Furthermore, genome-wide analysis of recombination revealed that CO interference is abolished, with the frequent observation of close COs. In addition, heterochiasmy was erased, with identical CO rates in males and females. This shows that the tripartite synaptonemal complex is dispensable for CO formation and has a key role in regulating their number and distribution, imposing CO interference and heterochiasmy.