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随着中国乡村振兴战略的持续推进，乡村地区对能源的多元化需求及服务质量提出了更高的要求。电-热多能系统（electric heating multi-energy system,EHMES）能够有效改善乡村地区的用能结构，促进清洁能源消纳。针对乡村地区中存在的灵活性资源，首先，构建包含光伏、风电、小水电、沼气热电联产机组、地源热泵、储能装置、柔性负荷等在内的乡村电-热多能系统优化模型。其次，考虑系统各等式约束及不等式约束，以系统运行总成本最低为目标函数，在Matlab环境下采用Yalmip工具箱和CPLEX求解器对所建立的模型进行求解。最后，以南方某省乡村电-热多能系统为例，分析模型在2种不同场景下的运行情况。算例结果表明，柔性负荷在降低系统运行成本、削峰填谷、促进清洁能源消纳方面具有显著效果。

近几十年来，在信息通信技术（ICT）快速进步的推动下，信息化对社会运行和人类生活方方面面的影响正在日益深化。文章基于数字化、网络化和智能化的发展水平，对信息化发展历程进行了回顾，并提出数字孪生阶段之后将是数字智驱和数字超越阶段。随着信息化上升为未来网络演进的最主要驱动力，文章提出了网算协同、接入协同、光电协同和智能化4个网络演进特征，并强调了光通信在其中的关键作用和挑战。

第四代移动通信技术（4G）的长期演进技术（LTE）受国内1 785~1 805 MHz专网频段制约，轨道交通对于双网冗余配置和专门业务必须保证稳定的最低带宽要求，这使得LTE-Metro（LTE-M）综合承载系统的服务能力受到很大限制。针对上述问题，文章提出了对4G基站、核心网和车载终端适配器单元（TAU）进行升级，加入第五代移动通信技术（5G）公网非独立（NSA）基站的方案，利用4G专网作为列车自动运行通信控制（CBTC）系统业务的主网络，5G网络作为承载CBTC系统的辅网络，5G基站承载轨道交通专网的大带宽业务，实现了4G专网与5G公网融合以承载通信系统的大带宽需求。

文章首先介绍了硅光非线性效应在数字光子回路中的应用和研究价值,接着简要介绍了硅基纳米波导中的光力效应和热光效应,最后较详细地阐述了光力效应在路径非对称光传输中的应用,以及利用热光效应实现的光顺序路由传输和光学编码。

运营商迫切需要通过网络固移融合化解全业务竞争压力,而为应对成本、带宽和生存性等接入域固移融合的挑战,中国联通在ITU-T（国际电信联盟-电信组织）推动了G.metro建议。针对G.metro需求,文章提出了一种固移融合接入网架构,基于NFV（网络功能虚拟化）实现固移处理资源共享,基于波分复用环路和PON（无源光网络）的结合平衡固、移接入差异,以满足接入域简单和低成本的要求。

针对光纤通信领域技术热点Tbit/s高速光传输开展研究,分析了其关键的信道内复用技术。基于频谱效率、性能和可实现性,在对Nyquist波分复用、正交频分复用和Super-Nyquist三种技术进行比较后给出了对信道内复用技术的具体选择,并提出具有指导意义的Tbit/s高速光传输商用技术解决方案。

基于对OTN（光传送网络）技术发展方向的分析,指出SDN（软件定义网络）技术会直接或间接影响OTN未来五大发展方向中的三项,具体体现在软件定义传送平面、软件定义控制平面、IP与光跨层协同融合和光网络资源虚拟化四大方面。研究表明,OTN的SDN化将是超100Gbit/s时代的重要发展趋势。

全业务竞争压力使得运营商迫切需要实现网络的FMC（固移融合）。中国联通在ITU-T推动G.metro建议,以应对接入域FMC面临的带宽、生存性和成本等挑战。针对G.metro需求,提出一种具有自愈功能的新型WDM（波分复用）接入环,并进行了性能和生存性验证。结果表明,该接入环成本低、可靠性高。

文章从理论和实验两方面论述了一种新颖的基于无源光波导的级联二阶非线性效应型全光波长转换 （ AOWC）技术 ,采用 5 0 mm长的周期域反转 Li Nb O3 （ PPLN）光波导 ,实现了在 1 .5 5 μm波段的超过 70 nm的波长转换带宽 ,并验证了其多波长信道同时转换的能力 .

全光波长转换器 （ AOWC）是未来 DWDM网络中关键性器件之一 ,文章介绍了DWDM网中几种 AOWC的实现方法、原理和进展情况 ,还简单介绍了波长转换器在DWDM网中的最优化放置问题

全光码型转换器可以提高光网络的有效性和灵活性,是未来光网络中不可缺少的一部分。文章提出了一种基于半导体光放大器（SOA）中瞬时交叉相位调制（T-XPM）效应和光带通滤波器的开关键控（OOK）到光频移键控（OFSK）的高速全光码型转换方案。该方案结构简单,易于实现。在实验上实现了40 Gbit/s的OOK到OFSK的全光码型转换,并对其转换特性进行了实验研究。

SDH光接收模块具有高速高增益的特点，电路板设计的好坏是模块的性能指标能否实现的关键环节之一。为此，本文结合光接收模块的制作，从多个方面对高速板设计技术进行了详细的分析。并在充分运用高速板设计方法的基础上研制出高灵敏度小型化SDH光接收模块。

分析了半导体光放大器交叉增益调制的基本原理 ,并利用该机制进行了 2 .5Gbit/s的非归零码光脉冲的波长转换 .向上波长转换间隔大于 1 4nm.最后 ,对转换信号测量了接收机入纤功率和误码率的关系曲线、光眼图、消光比和光信噪比等参数 ,结果发现转换信号眼图清晰 ,张开度大 ,消光比大于 1 0 d B,光信噪比大于 30 d B.实验表明采用半导体光放大器的交叉增益调制可以较理想地实现 2 .5Gbit/s的非归零码的全光波长转换

Objective To analyze the application value of full process nursing management in patients with lumbar disc herniation(LDH). Methods A total of 60 LDH patients who underwent minimally invasive surgery in our hospital from January 2022 to May 2023 were selected and divided into the study group and the control groupaccording to the random number table method, with 30 cases in each group. The control group was given routine nursing, while the observation group was given full-process nursing management. The compliance of two groups of patients with medical compliance after nursing, as well as their psychological status (Self Rating Anxiety Scale, Self Rating Depression Scale scores) and functional status (Oswestry Dysfunction Index score) before and after nursing were compared between the two groups. Results The total score of compliance behavior after nursing in the study group [(22. 99±3. 59) points] was significantly higher than that in the control group [(19. 33±3. 06) points], and the difference was statistically significant (P<0. 05). Compared with before nursing, the scores of self-rating anxiety scale, self-rating depression scale and Oswestry dysfunction index in the two groups were significantly decreased after nursing, and the scores of self-rating anxiety scale. self-rating depression scale and Oswestry dysfunction index in the study group [(46. 25±4. 11), (51. 12±4. 70),(16. 68±2. 82) points were significantly lower than those in the control group [(49. 25± 28),(53. 88±4. 46),(20. 15±3. 07) points]. The differences were statistically significant (P<0. 05). Conclusion The full-process of nursing management for LDH patients can improve their compliance behavior, improve their bad psychology and promote postoperative functional rehabilitation. [ABSTRACT FROM AUTHOR]

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This paper proposed a coordinated edge-to-edge architecture for an emergency response scenario assisted by unmanned aerial vehicles (UAVs), taking into consideration the frequent occurrence of natural disasters globally. The architecture incorporated a coordinator and aimed to minimize the overall system cost by considering factors such as latency, energy consumption, and loaded balancing among UAVs. And it utilized an improved deep reinforcement learning algorithm called advanced proximal policy optimization (APPO) to optimize the offloading process. Compared to binary offloading, partial offloading of tasks could effectively reduce the overall system cost. The APPO algorithm enabled users to determine suitable offloading ratios and allocate tasks to UAVs based on different task scenarios. Simulation and experimental results demonstrate a reduction of approximately 50% in the overall system cost compared to full local processing, and about 14% compared to the advanced A2C algorithm, showing the superiority of the proposed strategy in this specific scenario. [ABSTRACT FROM AUTHOR]

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Arsenic is a carcinogen and a causative agent of cardiovascular and peripheral vascular disease, neurological disorders, diabetes mellitus and various forms of cancer. Objective: Used Bioinformatics methods such as GO database and KEGG database to evaluate the differentially expressed genes in GEO database data. Methods; Functional enrichment, functional annotation analysis and survival analysis of the differential genes were performed by using bioinformatics analysis software. Results; Used protein-protein interaction network (PPI) software on Gvtoscape to analyze 179 differential genes. A total of 126 genes were found to be acting on protein targets, and 10 of them were key genes, respectively; PSMB3, HSP70\, HSPE\, STIPX, HSPD1, HSP70, DNAJBIB,/7SP90A41.1, I1SP A9H, TCP I; Conclusion; The core genes mainly act on protein processing in endoplasmic reticulum pathway. Il provides a new research direction for the potential biomarkers and biological mechanisms of arsenic induced liver injury. [ABSTRACT FROM AUTHOR]

Neural network models are vulnerable to adversarial sample attacks. Aiming at the problem that current defense methods focus on improving the model structure or the model only uses the adversarial training method which leads to a single type of defense and impairs the model’s classification ability and inefficiency, the method of combining the adversarial training and the feature mixture to train the siamese neural network model (SS-ResNet18) is proposed.The method mixes the training set sample data by linear interpolation, builds a siamese network model using the residual attention module, and inputs PGD antagonistic samples and normal samples into different branches of the network for training. The input features are interchanged in the feature space between neighboring sample parts to enhance the network’s immunity to interference, combining the adversarial loss and the classification loss as the overall loss function of the network and smoothing it with labels. Experimented on CIFAR-10 and SVHN datasets, the method shows excellent defense performance under white-box attack, and the success rate of the model’s defense against antagonistic samples, such as PGD, JSMA, etc., under black-box attack is more than 80%; at the same time, the SS-ResNet18 model time spent is only one-half of the one-half of the subspace antagonistic training method. The experimental results show that the SS-ResNet18 model can defend against a variety of adversarial sample attacks, and is robust and less time-consuming to train compared to existing defense methods. [ABSTRACT FROM AUTHOR]

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