Reusable Polyacrylonitrile-Sulfur Extractor of Heavy Metal Ions from Wastewater

Mercury, lead, and cadmium are among the most toxic and carcinogenic heavy metal ions (HMIs), posing serious threats to the sustainability of aquatic ecosystems and public health. There is an urgent need to remove these ions from water by a cheap but green process. Traditional methods have insufficient removal efficiency and reusability. Structurally robust, large surface-area adsorbents functionalized with high-selectivity affinity to HMIs are attractive filter materials. Here, an adsorbent prepared by vulcanization of polyacrylonitrile (PAN), a nitrogen-rich polymer, is reported, giving rise to PAN-S nanoparticles with cyclic π-conjugated backbone and electronic conductivity. PAN-S can be coated on ultra-robust melamine (ML) foam by simple dipping and drying. In agreement with hard/soft acid/base theory, N- and S-containing soft Lewis bases have strong binding to Hg²⁺, Pb²⁺, Cu²⁺, and Cd²⁺, with extraordinary capture efficiency and performance stability. Furthermore, the used filters, when collected and electrochemically biased in a recycling bath, can release the HMIs into the bath and electrodeposit on the counter-electrode as metallic Hg⁰, Pb⁰, Cu⁰, and Cd⁰, and the PAN-S@ML filter can then be reused at least 6 times as new. The electronically conductive PAN-S@ML filter can be fabricated cheaply and holds promise for scale-up applications.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

Progressive NO2 Sensors with Rapid Alarm and Persistent Memory-Type Responses for Wide-Range Sensing Using Antimony Triselenide Nanoflakes

Antimony triselenide (Sb₂Se₃) nanoflake-based nitrogen dioxide (NO₂) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb₂Se₃ nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO₂ gas concentrations from 0.1 to 100 ppm. These Sb₂Se₃ nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb₂Se₃ nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO₂ gas flow of only 1 ppm. As a result, the Sb₂Se₃ nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations.     

从废水到新能源:光催化燃料电池的优化与应用

随着经济的飞速发展,社会对能源的需求日益扩大,对工业废水的无害化处理也提出了更高的要求。光催化燃料电池 (photocatalytic fuel cell, PFC) 在燃料电池中引入半导体光催化材料作为电极,实现了有机污染物高效降解和同步对外产电的双重功能,在废水无害化与资源化利用方面具有潜在的应用价值。半导体光催化电极是PFC系统高效运行的核心组件,增强其可见光响应和光生载流子分离是提高PFC性能的关键策略。反应器结构设计和运行参数优化也有利于改善PFC性能。本文从PFC基本原理和应用入手,综述了PFC在环境污染物资源化处理中的研究进展,并详细阐述了提高PFC的污染控制性能和产电效率的优化手段,为进一步设计高效稳定的PFC系统并实现其在水污染控制和清洁能源生产中的应用提供理论指导。     

基于SONET/SDH的存储网络容灾技术分析

文章分析了存储网络（SAN）容灾技术，认为在某些企业中，数据是至关重要的资产之一，是业务系统运行的血脉．保护企业的重要数据是企业成功的关键因素。文章讨论了设计容灾技术解决方案应考虑的各种因素，并给出了基于SONET／SDH的存储网络技术的体系架构设计方案。     

连续波半主动雷达制导空空导弹截获跟踪距离计算

分析了连续波半主动雷达制导导弹导引头工作电磁环境和对武器系统攻击区的影响，建立了热噪声和杂波干扰环境下导引头截获距离方程，分析推导了直波泄漏干扰，地杂波干扰的计算公式，并在此基础上给出了导弹允许攻击区计算公式。     

生存能力技术及其实现案例研究

生存能力技术谋求增强系统在面临攻击、失效等灾难情况下仍能继续提供服务的能力。本文提出了以多样化分布式动态备份技术和主动漂移机制为手段，以被保护目标的机动性和隐蔽性为目的的生存能力技术模型。提出了多样化体系理论及其实现案例，基于该理论设计并实现了自适应TOM方法。最后通过模拟和测试探讨了生存能力的评价方法，并验证了本文的结果。     

VRPTW的扰动恢复及其TABU SEARCH算法

本文对带时间窗的车辆路线安排扰动恢复问题进行了讨论,分析了各种可能的扰动:增加减少客户,时间窗、客户需求及路线可行性的扰动,构造了扰动模型.利用禁忌搜索算法对问题进行求解,同时通过对模型参数重新设置,得到了多个满足要求的不同的解,这样使解更具有实际可行性和有效性.     

All-optical frequency multiplication/recovery based on a semiconductor optical amplifier ring cavity

A novel scheme for all-optical frequency multiplication/recovery based on a semiconductor optical amplifier ring cavity is proposed and investigated numerically. The results show, for a 2.5 GHz driving pulse train, it can be generated 5-25 GHz repetition rate pulse trains with low clock amplitude jitter, polarization independence and high peak power. Furthermore, the extraction of the clock signal from a pseudorandom bit sequence signal can be realized based on the proposed scheme.     

The Minimum PAPR Code for OFDM Systems

In this letter, a block code that minimizes the peak‐to‐average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals is proposed. It is shown that peak envelope power is invariant to cyclic shift and codeword inversion. The systematic encoding rule for the proposed code is composed of searching for a seed codeword, shifting the register elements, and determining codeword inversion. This eliminates the look‐up table for one‐to‐one correspondence between the source and the coded data. Computer simulation confirms that OFDM systems with the proposed code always have the minimum PAPR.