Novel interface engineering of LDH-based materials on Mg alloy for efficient photocatalytic systems considering the geometrical linearity of condensed phosphates

This study presents a facile and rapid method for synthesizing novel Layered Double Hydroxide(LDH)nanoflakes,exploring their application as a photocatalyst,and investigating the influence of condensed phosphates'geometric linearity on their photocatalytic properties.Herein,the Mg O film,obtained by plasma electrolysis of AZ31 Mg alloys,was modified by growing an LDH film,which was further functionalized using cyclic sodium hexametaphosphate(CP)and linear sodium tripolyphosphate(LP).CP acted as an enhancer for flake spacing within the LDH structure,while LP changed flake dispersion and orientation.Consequently,CP@LDH demonstrated exceptional efficiency in heterogeneous photocatalysis,effectively degrading organic dyes like Methylene blue(MB),Congo red(CR),and Methyl orange(MO).The unique cyclic structure of CP likely enhances surface reactions and improves the catalyst's interaction with dye molecules.Furthermore,the condensed phosphate structure contributes to a higher surface area and reactivity in CP@LDH,leading to its superior photocatalytic performance compared to LP@LDH.Specifically,LP@LDH demonstrated notable degradation efficiencies of 93.02%,92.89%,and 88.81%for MB,MO,and CR respectively,over a 40 min duration.The highest degradation efficiencies were observed in the case of the CP@LDH sample,reporting 99.99%for MB,98.88%for CR,and 99.70%for MO.This underscores the potential of CP@LDH as a highly effective photocatalyst for organic dye degradation,offering promising prospects for environmental remediation and water detoxification applications.

Facile preparation and efficient MnxCoy porous nanosheets for the sustainable catalytic process of soot

The pursuit of high-performance is worth considerable effort in catalysis for energy efficiency and environmental sustainability. To develop redox catalysts with superior performance for soot combustion, a series of Mn_(x)Co_(y) oxides were synthesized using MgO template substitution.This method greatly improves the preparation and catalytic efficiency and is more in line with the current theme of green catalysts and sustainable development. The resulting Mn_(1)Co_(2.3) has a strong activation capability of gaseous oxygen due to a high concentration of Co^(3+) and Mn^(3+). The Mn doping enhanced the intrinsic activity by prompting oxygen vacancy formation and gaseous oxygen adsorption. The nanosheet morphology with abundant mesoporous significantly increased the solid–solid contact efficiency and improved the adsorption capability of gaseous reactants. The novel design of Mn_(1)Co_(2.3)oxide enhanced its catalytic performance through a synergistic effect of Mn doping and the porous nanosheet morphology, showing significant potential for the preparation of high-performance soot combustion catalysts.

An efficient and universal protoplast-based transient gene expression system for genome editing in Brassica crops

Protoplast-based transient gene expression system has been widely used in plant genome editing because of its simple operation and less time-consuming.In order to establish a universal protoplast-based transient transfection system for verifying activities of genome editing vectors containing targets in Brassica,we systematically optimized factors affecting protoplast isolation and transient gene expression.We established an efficient protoplast-based transient gene expression system(PTGE)in Chinese cabbage,achieving high protoplast yield of 4.9×10^(5)·g^(-1)FW,viability over 95%,and transfection efficiency of 76%.We showed for the first time that pretreatment of protoplasts with a hypotonic MMG could significantly enhance the transfection efficiency.Furthermore,protoplasts incubated at 37℃ for 6 min improved the transfection efficiency to 86%.We also demonstrated that PTGE worked well(more than 50%transfection efficiency)in multiple Brassica species including cabbage,Pak Choi,Chinese kale,and turnip.Finally,PTGE was used for validating the activities of CRISPR/Cas9 vectors containing targets in Chinese cabbage,cabbage,and pak choi,demonstrating the broad applicability of the established PTGE for genome editing in Brassica crops.

Fast,simple,efficient Agrobacterium rhizogenes-mediated transformation system to non-heading Chinese cabbage with transgenic roots

Non-heading Chinese cabbage, a variety of Brassica campestris, is an important vegetable crop in the Yangtze River Basin of China. However,the immaturity of its stable transformation system and its low transformation efficiency limit gene function research on non-heading Chinese cabbage. Agrobacterium rhizogenes-mediated(ARM) transgenic technology is a rapid and effective transformation method that has not yet been established for non-heading Chinese cabbage plants. Here, we optimized conventional ARM approaches(one-step and two-step transformation methods) suitable for living non-heading Chinese cabbage plants in nonsterile environments. Transgenic roots in composite non-heading Chinese cabbage plants were identified using phenotypic detection, fluorescence observation, and PCR analysis. The transformation efficiency of a two-step method on four five-day-old non-heading Chinese cabbage seedlings(Suzhouqing, Huangmeigui, Wuyueman, and Sijiu Caixin) was 43.33%-51.09%, whereas using the stout hypocotyl resulted in a transformation efficiency of 54.88% for the 30-day-old Sijiu Caixin.The one-step method outperformed the two-step method;the transformation efficiency of different varieties was above 60%, and both methods can be used to obtain transgenic roots for functional studies within one month. Finally, optimized ARM transformation methods can easily,quickly, and effectively produce composite non-heading Chinese cabbage plants with transgenic roots, providing a reliable foundation for gene function research and non-heading Chinese cabbage genetic improvement breeding.

Efficient cache replacement framework based on access hotness for spacecraft processors

A notable portion of cachelines in real-world workloads exhibits inner non-uniform access behaviors.However,modern cache management rarely considers this fine-grained feature,which impacts the effective cache capacity of contemporary high-performance spacecraft processors.To harness these non-uniform access behaviors,an efficient cache replacement framework featuring an auxiliary cache specifically designed to retain evicted hot data was proposed.This framework reconstructs the cache replacement policy,facilitating data migration between the main cache and the auxiliary cache.Unlike traditional cacheline-granularity policies,the approach excels at identifying and evicting infrequently used data,thereby optimizing cache utilization.The evaluation shows impressive performance improvement,especially on workloads with irregular access patterns.Benefiting from fine granularity,the proposal achieves superior storage efficiency compared with commonly used cache management schemes,providing a potential optimization opportunity for modern resource-constrained processors,such as spacecraft processors.Furthermore,the framework complements existing modern cache replacement policies and can be seamlessly integrated with minimal modifications,enhancing their overall efficacy.

"Three-in-One" Ecological Development and Efficient Utilization Model of Aggregates

Green mining and the formation of an effective and efficient development model have become key issues that aggregates enterprises around the world need to solve urgently.On the basis of analyzing the development status of aggregates industry in Xiluodu area,the paper studied the main problems faced in the construction of green aggregates mines at present,and proposed a"three-in-one"ecological,intelligent and efficient green mine construction model for"ecological development","green logistics"and"solid waste recycling"of aggregates.The study has certain theoretical value and practical significance for the construction of green aggregates mine in Xiluodu area.

Establishment of NaLuF_(4):15%Tb-based low dose X-PDT agent and its application on efficient antitumor therapy

X-ray excited photodynamic therapy(X-PDT)is the bravo answer of photodynamic therapy(PDT)for deep-seated tumors,as it employs X-ray as the irradiation source to overcome the limitation of light penetration depth.However,high X-ray irradiation dose caused organ lesions and side effects became the major barrier to X-PDT application.To address this issue,this work employed a classic-al co-precipitation reaction to synthesize NaLuF_(4):15%Tb^(3+)(NLF)with an average particle size of(23.48±0.91)nm,which was then coupled with the photosensitizer merocyanine 540(MC540)to form the X-PDT system NLF-MC540 with high production of singlet oxygen.The system could induce antitumor efficacy to about 24%in relative low dose X-ray irradiation range(0.1-0.3 Gy).In vivo,when NLF-MC540 irradiated by 0.1 Gy X-ray,the tumor inhibition percentage reached 89.5%±5.7%.The therapeutic mechanism of low dose X-PDT was found.A significant increase of neutrophils in serum was found on the third day after X-PDT.By immunohistochemical staining of tumor sections,the Ly6G^(+),CD8^(+),and CD11c^(+)cells infiltrated in the tumor microenvironment were studied.Utilizing the bilat-eral tumor model,the NLF-MC540 with 0.1 Gy X-ray irradiation could inhibit both the primary tumor and the distant tumor growth.De-tected by enzyme linked immunosorbent assay(ELISA),two cytokines IFN-γand TNF-αin serum were upregulated 7 and 6 times than negative control,respectively.Detected by enzyme linked immune spot assay(ELISPOT),the number of immune cells attributable to the IFN-γand TNF-αlevels in the group of low dose X-PDT were 14 and 6 times greater than that in the negative control group,respectively.Thus,it conclude that low dose X-PDT system could successfully upregulate the levels of immune cells,stimulate the secretion of cy-tokines(especially IFN-γand TNF-α),activate antitumor immunity,and finally inhibit colon tumor growth.

Low rank optimization for efficient deep learning:making a balance between compact architecture and fast training

Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.

Energy-Efficient Traffic Offloading for RSMA-Based Hybrid Satellite Terrestrial Networks with Deep Reinforcement Learning

As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access(RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.

Priority Based Energy Efficient MAC Protocol by Varying Data Ratefor Wireless Body Area Network

Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxygen level,body motion,and so on.They sense the data and communicate it to the Body Area Network(BAN)Coordinator.The main challenge for the WBAN is energy consumption.These issues can be addressed by implementing an effective Medium Access Control(MAC)protocol that reduces energy consumption and increases network lifetime.The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard.In our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the data.We gave priority to the highly critical data to get the Guarantee Tine Slots(GTS)in IEEE 802.15.4 standard superframe to achieve greater energy efficiency.The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity.As an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing MAC protocols,the MVDR performed very well with low energy intake,less interruption,and an enhanced packet-sharing ratio.

Low-Cost Insulation for Energy Efficient Buildings in Terai Region of Nepal

There is a huge amount of energy savings potential in public building sector that has yet to be realized.By prioritizing energy efficiency in its own buildings and thus promoting the development of required knowledge in terms of new technology and construction methods,the public sector will lead the way in efforts to increase the rate of renovations.The low-cost insulation strategies and a comparison of cost with existing insulation materials has been described in this study.We have repeatedly faced energy crises and will continue to do so in the future if appropriate action is not taken in a timely manner.Properly implementing energy-saving initiatives in for achieving thermal comfort in buildings as well as reducing the energy costs would undoubtedly inspire the residential sector,resulting in significant reductions in energy usage.Simulations were carried out to study insulation layers on various building components like exterior walls,floor and roofs,generating different scenarios for a building as a base model,which were then compared and analysed to verify the literature used to develop the cases.The proposed recommendations,which have been validated,are certain to increase building energy efficiency,achieve thermal comfort in low cost than what is currently being used.

基于改进EfficientNetB0模型的葡萄叶部病害识别方法

为了高效、准确地识别葡萄叶部病害,文中提出了LE-EfficientNet模型,在EfficientNetB0模型基础上,采用大核注意力(LKA)机制替换原模型部分MBConv模块中的压缩激励网络(SENet),接着利用跳跃连接在最后一层卷积层后面融入高效通道注意力机制(ECA),结合三种注意力机制让网络更高效地提取葡萄叶部病害的局部重要信息,并引用Adam优化器替换原模型的SGD优化器,提升了分类模型的泛化能力。在PlantVillage葡萄叶部病害数据集上训练,结果表明,LE-EfficientNet模型相比原模型准确率提升了1.58%,总体精度提升了1.62%,召回率提升了1.46%,F_(1)分数提升了1.53%,并且参数量仅有10.18 MB,比原模型参数量降低2.7 MB,与其他经典网络模型相比,性能评估指标均有不同程度的提升,该研究为葡萄叶部病害识别提供了新的参考与借鉴。

基于FACAM-Efficient Net的通信信号调制方式识别

针对在复杂电磁空间中,通信信号识别方法存在噪声干扰、识别率不足、网络模型复杂等问题,提出基于高阶累积量可视化时频图像的FACAM-Efficient Net信号调制方式识别方法,通过高阶累积量时频分析方法,将不同调制的通信信号转换成可视化时频图像,用作网络模型的训练和测试,根据可视化时频图像的图像特征,提出FACAM频域通道混合注意力机制,并引入FACAM改进Efficient Net的网络主体结构,更好地提取时频图像的频域和通道的特征。实验结果显示,本文提出的调制识别方法在低信噪比下有较好的识别效果。

基于改进E-EfficientNet的古陶瓷纹饰分类模型

为进一步提高古陶瓷纹饰分类精度,提出一种基于改进EfficientNet的古陶瓷纹饰分类模型。该模型通过引入高效率注意力机制(ECA)模块改进原主干网络EfficientNet-B0,有效捕获通道间的交互信息,利用跳跃连接在特征提取的最后一层加入ECA模块,获得古陶瓷纹饰注意力特征图,并利用迁移学习和Adam优化算法在古陶瓷纹饰数据集上进行实验验证。结果表明,改进后的E-EfficientNet模型在古陶瓷纹饰数据集上的识别准确率达到了99.26%,较改进前提高了2.48%;与同类轻量化模型ShuffleNet-V2和MobileNet-V3对比,识别准确率分别提高了2.10%和2.91%;与其他经典模型VGG、ResNet对比,不仅参数量大幅度减少,识别准确率均明显提高,可有效用于古陶瓷纹饰分类。

Surface Passivation Toward Efficient and Stable Perovskite Solar Cells

Although metal halide perovskites are increasingly popular for the next generation of efficient photovoltaic devices,the inevitable defects from the preparation process have become the notorious barrier to further improvement of performance,which increases non-radiative recombination and lowers the power conversion efficiency of solar cells.Surface passivation strategies have been affirmed as one of the most practical approaches to suppress these defects.Therefore,it is necessary to have a detailed review on the surface passivation to reveal the improvements of the devices.Herein,the mechanism and recent advances of surface passivation have been systematically summarized with respect to various passivation approaches,including the Lewis acid–base,the low-dimensional perovskite,inorganic molecules,and polymers.Finally,the review also offers the research trend and prospects of surface passivation.

Gene expression pattern of K transporter GhHAK5 gene of potassium efficient and in-efficient cotton cultivars based on morphological physiognomies as affected by potassium nutrition and reduced irrigation

Background Under K deficiency the uptake and distribution pattern in plant cells is mediated through different transport proteins and channels which were controlled by specific gene family.Therefore,a hydroponic experiment was conducted under control condition for testing the gene expression pattern of the K transporter under adequate and low K supply levels.After that,a 2-year field experiment was conducted to evaluate five selected cotton cultivars(four K-efficient cultivars,viz.,CIM-554,CYTO-124,FH-142,IUB-2013,and one K non-efficient,BH-212) screened from the initial hydroponics culture experiment and two levels of potassium(0 K_(2)O kg·ha^(-1) and 50 K_(2)O kg·ha^(-1)) were tested under reduced irrigation(50% available water content;50 AWC) and normal irrigation conditions(100% available water content;100 AWC).Result Results revealed that the transcript levels of GhHAK5aD in roots were significantly higher in K^(+) efficient cultivars than that in K^(+) non-efficient cultivars.The GhHAK5aD expression upon K^(+) deficiency was higher in roots but lower in shoots,indicating that GhHAK5aD could have a role in K^(+) uptake in roots,instead of transport of K^(+) from root to shoot.Similarly,under field conditions the cultivar FH-142 showed an increase of 22.3%,4.9%,2.4%,and 1.4% as compared with BH-212,IUB-2013,CYTO-124,and CIM-554,respectively,in seed cotton yield(SCY) with K application under reduced irrigation conditions.With applied K,the FH-142 showed an increase in net photosynthetic rate by 57.3% as compared with the rest of the cultivars under reduced irrigation over K control.However,the overall performance indicators of K-efficient cultivars like FH-142,CYTO-124,CIM-554,and IUB-2013 were better than BH-212(K in-efficient) under reduced irrigation conditions with applied K at 50 kg·ha^(-1).Fiber quality trait improved significantly with K application under water deficit.The increase in micronaire was 3.6%,4.7%,7.8%,3.4%,and 6.7% in BH-212,IUB-2013,CIM-554,CYTO-124,and FH-142,respectively,with K application at 50 kg·ha^(-1) over without K application under reduced irrigation conditions during the cotton growing season.Similarly,the cultivars FH-142 increased by 12% with K application under reduced irrigation as compared with other cultivars.The performance of K-efficient cultivars under reduced irrigation conditions was 30% better in SCY and quality traits with the application of K at 50 kg·ha^(-1) as compared with K-non-efficient cultivars.Similarly,water use efficiency(WUE)(40.1%) and potassium use efficiency(KUE)(20.2%) were also noted higher in case of FH-142 as compared with other cultivar with K application under reduced conditions.Conclusion Higher expression of GhHAK5aD gene was observed in K-efficient cultivars as compared with K-nonefficient cultivars in roots indicates that GhHAK5aD may be contributing to genotypic differences for K^(+) efficiency in cotton.K-efficient cotton cultivars can be used for the low-K environments and can also be recommended for general cultivars.

Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile communications.The difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing topology.In the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same time.Typically,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing system.With this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)technique.The presented COAER-UAVC technique establishes effective routes for communication between the UAVs.It is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from predators.Besides,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC system.The experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

Porous heterostructure of graphene/hexagonal boron nitride as an efficient electrocatalyst for hydrogen peroxide generation

Compared with the traditional heteroatom doping,employing heterostructure is a new modulating approach for carbon-based electrocatalysts.Herein,a facile ball milling-assisted route is proposed to synthesize porous carbon materials composed of abundant graphene/hexagonal boron nitride(G/h-BN)heterostructures.Metal Ni powder and nanoscale h-BN sheets are used as a catalytic substrate/hard template and“nucleation seed”for the formation of the heterostructure,respectively.As-prepared G/h-BN heterostructures exhibit enhanced electrocatalytic activity toward H_(2)O_(2) generation with 86%-95%selectivity at the range of 0.45-0.75 V versus reversible hydrogen electrode(RHE)and a positive onset potential of 0.79 versus RHE(defined at a ring current density of 0.3 mA cm^(-2))in the alkaline solution.In a flow cell,G/h-BN heterostructured electrocatalyst has a H_(2)O_(2) production rate of up to 762 mmol g_(catalyst)^(-1) h^(-1) and Faradaic efficiency of over 75%during 12 h testing,superior to the reported carbon-based electrocatalysts.The density functional theory simulation suggests that the B atoms at the interface of the G/h-BN heterostructure are the key active sites.This research provides a new route to activate carbon catalysts toward highly active and selective O_(2)-to-H_(2)O_(2) conversion.

FSE2R:An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocolin USN

The 3D Underwater Sensor Network(USNs)has become the most optimistic medium for tracking and monitoring underwater environment.Energy and collision are two most critical factors in USNs for both sparse and dense regions.Due to harsh ocean environment,it is a challenge to design a reliable energy efficient with collision free protocol.Diversity in link qualities may cause collision and frequent communication lead to energy loss;that effects the network performance.To overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing(FSE2R)is proposed.Our proposal’s key idea is based on computation of node distance from the sink,Residual Energy(RE)of each node and Signal to Interference Noise Ratio(SINR).The node distance from sink and RE is computed for reliable forwarder node selection and SINR is used for analysis of collision.The novel proposal compares with existing protocols like H2AB,DEEP,and E2LR to achieve Quality of Service(QoS)in terms of through-put,packet delivery ratio and energy consumption.The comparative analysis shows that FSE2R gives on an average 30%less energy consumption,24.62%better PDR and 48.31%less end-to-end delay compared to other protocols.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.