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The preparation of high-performance electro-optical materials is one of the key factors determining the application of optoelectronic communication technology such as 5G communication, radar detection, terahertz, and electro-optic modulators. Organic electro-optic materials have the advantage of a high electro-optic coefficient (~1000 pm/V) and could allow the utilization of photonic devices for the chip-scale integration of electronics and photonics, as compared to inorganic electro-optic materials. However, the application of organic nonlinear optical materials to commercial electro-optic modulators and other fields is also facing technical bottlenecks. Obtaining an organic electro-optic chromophore with a large electro-optic coefficient (r33 value), thermal stability, and long-term stability is still a difficulty in the industry. This brief review summarizes recent great progress and the strategies to obtain high-performance OEO materials with a high electro-optic coefficient and/or strong long-term stability. The configuration of D-π-A structure, the types of materials, and the effects of molecular engineering on the electro-optical coefficient and glass transition temperature of chromophores were summarized in detail. The difficulties and future development trends in the practical application of organic electro-optic materials was also discussed.

Highlights The intimate NG@SiC heterostructure has been constructed via a direct thermal decomposition method. The NG@SiC heterostructure anode delivers enhanced capacity and cycling stability both in the half-cell and in the full cell. DFT analysis reveals that this NG@SiC anode possesses lower lithium-ion adsorption energy and higher charge and discharge rates.

Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) is an extension of the traditional VRPTW by considering dynamic customer characteristics. In this problem, new customers with specific time windows are received dynamically as time progresses and must be incorporated into the evolving schedule. The goal of DVRPTW is to use the minimum number of vehicles to fulfill all the customer demands with the minimum total traveling time. Little work has been done for solving this dynamic variant. In this paper, an evolutionary algorithm using Ant Colony System and Kuhn-Munkres bipartite graph matching, named ACS-KM, is proposed. It can tackle the dynamic issues during the evolutionary process. Experiments show that the proposed algorithm is very effective and has fast convergence. It achieves the best results on 40 out of 48 benchmark instances. For the DVRPTW instances with different levels of dynamicity, the algorithm can always produce better solutions than the previous works.

Abstract The development of electro‐optical materials with high chromophore loading levels that possess ultrahigh electro‐optic coefficients and high long term alignment stability is a challenging topic. Anthracene‐maleimide Diels–Alder (DA) reaction and π–π interaction of Anthracene‐pentafluorobenzene and benzene‐pentafluorobenzene are developed for making highly efficient binary cross‐linkable/self‐assembled dendritic chromophores FZL1‐FZL4. A covalently or non‐covalently cross‐linked network is formed by DA reaction or π–π interaction after electric field poling orientation, which greatly improves the long‐term alignment stability of the materials. An electro‐optic coefficient up to 266 pm V−1 and glass transition temperature as high as 178 °C are achieved in cross‐linked film FZL1/FZL2, and 272–308 pm V−1 is achieved for self‐assembled films FZL1/FZL4 and FZL3/FZL4 due to high chromophore density (3.09–4.02 × 1020 molecules cm−3). Long‐term alignment stability tests show that after heating at 85 °C for over 500 h, 99.73% of the initial r33 value is maintained for poled crosslinked electro‐optic films 1:1 FZL1/FZL2. The poled self‐assembled electro‐optic films 1:1 FZL1/FZL4 and 1:1 FZL3/FZL4 can still maintain more than 97.11% and 98.23%, respectively, of the original electro‐optic coefficient after being placed at room temperature for 500 h. The excellent electro‐optic coefficient and stability of the material indicate the practical application prospects of organic electro‐optic materials.

Task generalization has been a long-standing challenge in Natural Language Processing (NLP). Recent research attempts to improve the task generalization ability of pre-trained language models by mapping NLP tasks into human-readable prompted forms. However, these approaches require laborious and inflexible manual collection of prompts, and different prompts on the same downstream task may receive unstable performance. We propose Unified Schema Prompt, a flexible and extensible prompting method, which automatically customizes the learnable prompts for each task according to the task input schema. It models the shared knowledge between tasks, while keeping the characteristics of different task schema, and thus enhances task generalization ability. The schema prompt takes the explicit data structure of each task to formulate prompts so that little human effort is involved. To test the task generalization ability of schema prompt at scale, we conduct schema prompt-based multitask pre-training on a wide variety of general NLP tasks. The framework achieves strong zero-shot and few-shot generalization performance on 16 unseen downstream tasks from 8 task types (e.g., QA, NLI, etc.). Furthermore, comprehensive analyses demonstrate the effectiveness of each component in the schema prompt, its flexibility in task compositionality, and its ability to improve performance under a full-data fine-tuning setting.

For transformer enterprises, energy consumption and environmental pollution mainly occur in the manufacturing process. The conventional manufacturing mode does not conform to the current green manufacturing mode. The green manufacturing mode requires enterprises to improve the transformer production technology, the utilization rate of materials and equipment, and the production efficiency and to achieve clean production through energy conservation and consumption reduction. The main objective of this research is to schedule the blanking of multiple transformer cores together rather than the conventional calculation conducted one by one. An optimization model of the silicon steel coil blanking is established, an evaluation method for blanking schemes is proposed, algorithms to solve the optimization model are analyzed in detail, and the solving processes and results are compared through a case study. Compared with the current manual calculation, this paper is of practical significance for transformer manufacturers to improve the production efficiency, reduce material waste, meet the personalized market demand characterized by multiple varieties and small batches, and achieve the green manufacturing of transformers.

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This “smart” SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor’s response. This can be explained by considering the aptamers’ conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule.

An adaptive evolutionary algorithm with two-stage local search is proposed to solve the multi-objective flexible job-shop scheduling problem (MOFJSP). Adaptivity and efficient solving ability are the two main features. An autonomous selection mechanism of crossover operator is designed, which divides individuals into different levels and selects the appropriate one according to the both sides' levels to improve the self-adaptation. In parameter setting, the autonomous determination and adjustment mechanism is proposed, and parameters are adjusted autonomously according to the job scale and iteration number, so as to reduce the complexity of parameter setting and further improve the adaptivity. For improving solving ability, two-stage local search mechanism is designed. The first stage is performed before the evolution operation, so that each individual has more good genes to participate in the following operation. The second stage is performed after the evolution operation to further search the optimal solutions. Finally, a large number of comparative numerical tests are carried out, compared with other excellent algorithms, the proposed algorithm has fewer parameters to be set and stronger solving ability.

Six nonlinear, optical chromophores, Z1–Z6, based on the bis(N,N-diethyl)aniline-derived donor and thiolated isophorone bridge, were designed and synthesized. The bis(N,N-diethyl)aniline-derived donor was applied in a chromophore with thiolated isophorone as an electron bridge for the first time. In particular, the bridge parts of chromophores Z2–Z6 were modified with different functional groups, including tert-butyltrimethylsilane and tert-butyl(methyl)diphenylsilane derivative: 1,3-bis(trifluoromethyl)benzene and alkylaniline cyanoacetate, respectively. Density functional theory calculations suggested this series of chromophores show much greater hyperpolarizability than traditional, nonlinear, optical chromophores due to strong electron donor ability. These chromophores, Z1–Z6, showed very high poling efficiencies due to the large steric hindrance and hyperpolarizability of the chromophores. A large poling efficiency (2.04 ± 0.08 nm2/V2) and r33 value (193 pm/V) were achieved for polymeric thin films doped with 25 wt% chromophore Z6 at 1310 nm.

We evaluated genetic diversity and structure of Echinococcus granulosus by analyzing the complete mitochondrial NADH dehydrogenase subunit 2 (ND2) gene in 51 isolates of E. granulosus sensu stricto metacestodes collected at three locations in this region. We detected 19 haplotypes, which formed a distinct clade with the standard sheep strain (G1). Hence, all 51 isolates were identified as E. granulosus sensu stricto (G1–G3). Genetic relationships among haplotypes were not associated with geographical divisions, and fixation indices (Fst) among sampling localities were low. Hence, regional populations of E. granulosus in the southwest China are not differentiated, as gene flow among them remains high. This information is important for formulating unified region-wide prevention and control measures. We found large negative Fu’s Fs and Tajima’s D values and a unimodal mismatch distribution, indicating that the population has undergone a demographic expansion. We observed high genetic diversity among the E. granulosus s. s. isolates, indicating that the parasite population in this important bioregion is genetically robust and likely to survive and spread. The data from this study will prove valuable for future studies focusing on improving diagnosis and prevention methods and developing robust control strategies.