The dung beetle optimizer (DBO) is a metaheuristic algorithm with fast convergence and powerful search capabilities, which has shown excellent performance in solving various optimization problems. However, it suffers from the problems of easily falling into local optimal solutions and poor convergence accuracy when dealing with large-scale complex optimization problems. Therefore, we propose an adaptive DBO (ADBO) based on an elastic annealing mechanism to address these issues. First, the convergence factor is adjusted in a nonlinear decreasing manner to balance the requirements of global exploration and local exploitation, thus improving the convergence speed and search quality. Second, a greedy difference optimization strategy is introduced to increase population diversity, improve the global search capability, and avoid premature convergence. Finally, the elastic annealing mechanism is used to perturb the randomly selected individuals, helping the algorithm escape local optima and thereby improve solution quality and algorithm stability. The experimental results on the CEC 2017 and CEC 2022 benchmark function sets and MCNC benchmark circuits verify the effectiveness, superiority, and universality of ADBO.

The power optimization of mixed polarity Reed–Muller (MPRM) logic circuits is a classic combinatorial optimization problem. Existing optimization approaches often suffer from slow convergence and a propensity to converge to local optima, limiting their effectiveness in achieving optimal power efficiency. First, we propose a novel multi-strategy fusion memetic algorithm (MFMA). MFMA integrates global exploration via the chimp optimization algorithm with local exploration using the coati optimization algorithm based on the optimal position learning and adaptive weight factor (COA-OLA), complemented by population management through truncation selection. Second, leveraging MFMA, we propose a power optimization approach for MPRM logic circuits that searches for the best polarity configuration to minimize circuit power. Experimental results based on Microelectronics Center of North Carolina (MCNC) benchmark circuits demonstrate significant improvements over existing power optimization approaches. MFMA achieves a maximum power saving rate of 72.30% and an average optimization rate of 43.37%; it searches for solutions faster and with higher quality, validating its effectiveness and superiority in power optimization.

Abstract The connectivity is an important measurement for the fault-tolerance of networks. To provide more accurate measures for the fault-tolerance of networks than the connectivity, some generalizations of connectivity have been introduced. Substructure connectivity and structure connectivity are two extended concepts of classical connectivity. As a variant of the popular network hypercube, the Möbius cubes is also a famous interconnection network in parallel and distributed systems. In this article, we calculate $H$-substructure connectivity and $H$-structure connectivity of Möbius cubes when $H$ is isomorphic to $P_{m},C_{m}$ and $K_{1,m}$.

Area and power optimization of Fixed Polarity Reed–Muller (FPRM) circuits has received a lot of attention. Polarity optimization for FPRM circuits is essentially a binary multi-objective optimization problem. However, the existing area and power optimization approaches for FPRM logic circuits rarely produce a frontier and a greater number of Pareto optimal solutions . In this paper, a Multi-strategy Multi-objective Artificial Bee Colony (MMABC) algorithm is proposed to solve the binary multi-objective optimization problem. The main innovation of MMABC can be summarized as follows: a flexible foraging behavior strategy for employed bees is proposed to improve the searching ability of the algorithm; a genetic retention evolution for onlooker bees is proposed to improve the quality of the population; an efficient transform strategy is proposed to help the algorithm to jump out the local optimal and increase convergence speed. Moreover, we propose an area and power optimization approach for FPRM logic circuits, which uses the MMABC to search for the polarities (i.e., Pareto optimal solutions) with smaller area and lower power. Experimental results demonstrated the effectiveness and superiority of our approach in optimizing area and power of FPRM logic circuits.

This study identified a positive role of augmented reality (AR) hypnosis in the field of psychotherapy. The study utilised a 2 (gender: male vs. female) × 2 (hypnosis mode: AR hypnosis vs. ordinary hypnosis) between-groups experimental design. The psychological perception utility was significantly higher in females than in males, and the psychological perception utility of AR hypnosis was significantly higher than that of ordinary hypnosis. Differences existed between AR hypnosis and ordinary hypnosis for both males and females. The results show that AR hypnosis is effective in the psychotherapy of psychological stress and anxiety. This study serves as an important reference regarding psychotherapy based on AR.

As Network-based curriculum forum (NCF) is the main place for teachers and students to interact, the collaborative design is the basis for network-based curriculum, the study on the learning results of network-based curriculum forum becomes particularly important. The traditional studies on the effects of the NCF are mainly qualitative ones, which think that students' positive participation, such as posting the topics and replying the topics, makes great contribution to the study of curriculum. However, this hasn' t been verified by any empirical researches. A curriculum forum of Anqing Teachers College numbered 03001152 in the teaching platform based on network is taken as the study object to explore the relations between the NPT (number of posting topics), the NSR (number of students' replies) and SAP (students' academic performance) by variance analysis and regression analysis. It is found that: (1) The academic performance of students who post topics is better than that of those who do not post topics by 5.3%. (2)NPT and NTR (number of topics replying) are the two primary factors which affect SAP according to the variance analysis. Along with the increasing of the NSR and NTR, the SAP rises. The academic performance of students who reply more than 3 times is overall better than that of those who reply less than 3 times by 6.0%. The SAP whose topic is replied more than 2 times is overall better than that of those less than 3 times by 5.6%. (3)NSR and NTR are the two primary variables which affect SAP according to the regression analysis. The primary variables affecting SAP are explored for the first time through an empirical research at home and abroad. The study can instruct the collaborative design of network-based curriculum and valuable for the network-based education.

In the subsection ''Initial probabilities'' of the Results section, the first sentence was incorrect and should say: These probabilities, denoted by P 0 (RET) and P 0 (LOSS) 1 P 0 (RET), specify the probabilities of RET and LOSS for the pterminal marker on a chromosome.

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples.

Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ.

The captured data must be adapted for the humanoid because its kinematics and dynamic differ from those of the human actor. The kinematics constraints such as ground contact conditions are crucial for humanoid locomotion. Furthermore, it is desirable that the humanoid motion have of high similarity with those of the human actor. In this paper, first the similarity function of the humanoid motion is proposed. Then, the kinematics constrains including ground contact conditions are formulated, and the algorithm to derive the humanoid motion with a high similarity and satisfying kinematics constraints is present. Finally, the effectiveness is confirmed by the experiment of Chinese Kungfu "Taiji" using our developed 33 DOF humanoid robot.