Deep eutectic solvents:Green multi-task agents for sustainable super green hydrogen technologies

While reliance on renewable energy resources has become a reality, there is still a need to deploy greener and more sustainable methods in order to achieve sustainable development goals. Indeed, green hydrogen is currently believed to be a reliable solution for global warming and the pollution challenges arising from fossil fuels, making it the resilient fuel of the future. However, the sustainability of green hydrogen technologies is yet to be achieved. In this context, generation of green hydrogen with the aid of deep eutectic solvents(DESs) as green mixtures has been demonstrated as a promising research area. This systematic review article covers green hydrogen generation through water splitting and biomass fermentation when DESs are utilized within the generation process. It also discusses the incorporation of DESs in fuel cell technologies. DESs can play a variety of roles such as solvent, electrolyte, or precursor;colloidal suspension and reaction medium;galvanic replacement, shape-controlling, decoration, or extractive agent;finally oxidant. These roles are relevant to several methods of green hydrogen generation, including electrocatalysis, photocatalysis, and fermentation. As such, it is of utmost importance to screen potential DES formulations and determine how they can function in and contribute throughout the green hydrogen mobility stages. The realization of super green hydrogen generation stands out as a pivotal milestone in our journey towards achieving a more sustainable form of development;DESs have great potential in making this milestone achievable. Overall, incorporating DESs in hydrogen generation constitutes a promising research area and offers potential scalability for green hydrogen production, storage,transport, and utilization.

Trend of Storm Surge Induced by Typical Landfall Super Typhoons During 1975–2021 in the Eastern China Sea

Climate change affects the activity of global and regional tropical cyclones(TCs).Among all TCs,typical super typhoons(STYs)are particularly devastating because they maintain their intensity when landing on the coast and thus cause casualties,economic losses,and environmental damage.Using a 3D tidal model,we reconstructed the typhoon(TY)wind field to simulate the storm surge induced by typical STYs.The TY activity was then analyzed using historical data.Results showed a downtrend of varying degrees in the annual frequency of STYs and TCs in the Western North Pacific(WNP)Basin,with a significant trend change observed for TCs from 1949 to 2021.A large difference in the interannual change in frequency was found between STYs and TCs in the WNP and Eastern China Sea(ECS).Along the coast of EC,the frequency of landfall TCs showed a weak downtrend,and the typical STYs showed reverse micro growth with peak activity in August.Zhejiang,Fujian,and Taiwan were highly vulnerable to the frontal hits of typical STYs.Affected by climate change,the average lifetime maximum intensity(LMI)locations and landfall locations of typical STYs in the ECS basin showed a significant poleward migration trend.In addition,the annual average LMI and accumulated cyclone energy showed an uptrend,indicating the increasing severity of the disaster risk.Affected by the typical STY activity in the ECS,the maximum storm surge area also showed poleward migration,and the coast of North China faced potential growth in high storm surge risks.

Preparation and Swelling Kinetic Analysis of Poly (HPMC-co-AA-co-AM) Super Absorbent Resin

Super absorbent resin(SAR)is prepared by aqueous high temperature polymerization using hydroxypropyl methylcellulose(HPMC)as monomer backbone material,acrylic acid(AA)and acrylamide(AM)as the graft copolymer monomer,potassium persulfate(KPS)as the initiator to generate free radicals,and N,N`-methylenebisacrylamide(MBA)as cross-linking agent for cross-linking reaction.Simutaneously,the influence of individual factors on the water absorption is investigated,and these factors are mainly AA,AM,KPS,MBA,HPMC,and reaction temperature.The optimized conditions are obtained by the experiment repeating for several times.The water absorption multiplicity and salt absorption multiplicity under the conditions are 782.4 and 132.5 g/g,respectivity.Furthermore,the effects of different temperatures and salt concentrations on its water absorption,as well as the swelling kinetics of SAR are studied.It is indicated the water-absorbing swelling process is mainly caused by the difference in water osmotic pressure and Na+concentration inside and outside the cross-linked molecular structure of the resin,which is not only consistent with the quasi-secondary kinetic model,but also with the Fick diffusion model.

Hollow Ni Mo-based nitride heterojunction with super-hydrophilic/aerophobic surface for efficient urea-assisted hydrogen production

Hydrogen evolution reaction(HER)and urea oxidation reaction(UOR)are key reactions of the watercycling associated catalytic process/device.The design of catalysts with a super-hydrophilic/aerophobic structure and optimized electron distribution holds great promise.Here,we have designed a threedimensional(3D)hollow Ni/NiMoN hierarchical structure with arrayed-sheet surface based on a onepot hydrothermal route for efficient urea-assisted HER based on a simple hydrothermal process.The Ni/NiMoN catalyst exhibits super-hydrophilic/aerophobic properties with a small droplet contact angle of 6.07°and an underwater bubble contact angle of 155.7°,thus facilitating an escape of bubbles from the electrodes.Density functional theory calculations and X-ray photoelectron spectroscopy results indicate the optimized electronic structure at the interface of Ni and NiMoN,which can promote the adsorption/desorption of reactants and intermediates.The virtues combining with a large specific surface area endow Ni/NiMoN with efficient catalytic activity of low potentials of 25 mV for HER and 1.33 V for UOR at10 mA cm^(-2).The coupled HER and UOR system demonstrates a low cell voltage of 1.42 V at 10 mA cm^(-2),which is approximately 209 mV lower than water electrolysis.

A Unified Model Fusing Region of Interest Detection and Super Resolution for Video Compression

High-resolution video transmission requires a substantial amount of bandwidth.In this paper,we present a novel video processing methodology that innovatively integrates region of interest(ROI)identification and super-resolution enhancement.Our method commences with the accurate detection of ROIs within video sequences,followed by the application of advanced super-resolution techniques to these areas,thereby preserving visual quality while economizing on data transmission.To validate and benchmark our approach,we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical applications.The proposed model architecture leverages the transformer network framework,guided by a carefully designed multi-task loss function,which facilitates concurrent learning and execution of both ROI identification and resolution enhancement tasks.This unified deep learning model exhibits remarkable performance in achieving super-resolution on our custom dataset.The implications of this research extend to optimizing low-bitrate video streaming scenarios.By selectively enhancing the resolution of critical regions in videos,our solution enables high-quality video delivery under constrained bandwidth conditions.Empirical results demonstrate a 15%reduction in transmission bandwidth compared to traditional super-resolution based compression methods,without any perceivable decline in visual quality.This work thus contributes to the advancement of video compression and enhancement technologies,offering an effective strategy for improving digital media delivery efficiency and user experience,especially in bandwidth-limited environments.The innovative integration of ROI identification and super-resolution presents promising avenues for future research and development in adaptive and intelligent video communication systems.

New direction for surgery:Super minimally invasive surgery

The top goal of modern medicine is treating disease without destroying organ structures and making patients as healthy as they were before their sickness.Minimally invasive surgery(MIS)has dominated the surgical realm because of its lesser invasiveness.However,changes in anatomical structures of the body and reconstruction of internal organs or different organs are common after traditional surgery or MIS,decreasing the quality of life of patients post-operation.Thus,I propose a new treatment mode,super MIS(SMIS),which is defined as“curing a disease or lesion which used to be treated by MIS while preserving the integrity of the organs”.In this study,I describe the origin,definition,operative channels,advantages,and future perspectives of SMIS.

双缸进化器:2024 KTM 1390 Super Duke R

在顶级的街车阵列,KTM的超级公爵1290 Super Duke绝对占有一席之地。掌控132kW最大功率,挥洒140N·m最大扭矩,驱动只有约200kg的重量,再得到优秀悬挂系统和先进电控系统的加持,驾驶这匹超级猛兽跑在公路上,简直如入无人之境!

A Super Computer For a Super City

It’s a gigantic construction site that stretches beyond the horizon. Blue and red heavy-duty trucks in endless lines trundle about beneath a gaggle of cranes hoisting steel. And all the while enormous ultramodern buildings,bearing the names of the largest local and international companies,rise from the earth.

基于Super C Band的可调增益掺铒光纤放大器设计

随着网络业务流量的增长,通信业务对密集波分复用(DWDM)的性能要求越来越高。为了提高传输效率,传输频谱逐渐向C+L Band传输扩展,Super C Band传输应运而生,但目前与之对应的掺铒光纤放大器(EDFA)相关研究较少。针对这一问题,文章提出了一种针对Super C Band传输的EDFA结构,基于Giles模型,分析了EDFA在Super C Band的特性,利用多级泵浦机制,设计了一种可以在Super C Band范围内进行放大的EDFA。结果表明,在-9.3 dBm入光时,该EDFA可以实现26 dB的平坦增益,16.7 dBm的输出功率,此时噪声指数小于5 dB,Ripple小于0.1 dB。并且根据需要,在入光处于-15.0~-3.5 dBm范围内时,通过调节泵浦功率与可调衰减器,均能够实现7~26 dB的可调增益。该EDFA可应用于5G传输和数据中心之间光纤通信等场合。

Atmospheric and oceanic responses to Super Typhoon Mangkhut in the South China Sea:a coupled CROCO-WRF simulation

The South China Sea(SCS)is the largest marginal sea in the Northwest Pacific Ocean,and it encounters frequent typhoons.The atmosphere and ocean will create significant thermal and dynamic responses during the intense disturbance caused by typhoons.However,these responses have not been thoroughly investigated owing to the complicated marine environment.According to the satellite data,the SCS Basin was observed to have a strong sea surface temperature(SST)response to Typhoon Mangkhut,resulting in widespread SST cooling.A coupled model was used to investigate the atmospheric and oceanic responses to Typhoon Mangkhut.Best-track data,satellite SST,and ARGO measurements show that the coupled WRF-CROCO simulation displays better track,intensity,SST,temperature,and salinity profiles than those of the WRF-only simulation.Results show that the typhoon induced rightward intensifications in wind speed,ocean current,and SST.The following are some remarkable atmosphere and ocean responses:(1)the SST below the inner-core region is cooled by 1℃,resulting in a 37%-44%decrease in wet enthalpy,and the central pressure is increased by~9 hPa.Therefore,the changes in SST below the innercore region of the SCS Basin have a significant impact on air-sea fluxes under high-wind conditions;(2)the ocean boundary layer analysis shows that near-inertial oscillations on the right side of the typhoon track and a strong inertial current up to~2.28 m/s in the upper ocean were observed,which resonated with the local wind and flow field on the right side and induced strong SST cooling;(3)a decrease in SST decreased the moist static energy of the typhoon boundary layer,thereby weakening the typhoon’s intensity.The difference in equivalent potential temperature and sea surface pressure have a good correlation,indicating that the influence of moist static energy on typhoon intensity cannot be overlooked.

基于Super Learner集成学习模型对脑卒中的预测研究

使用索马里医院提供的脑卒中患者数据集,通过四分位距(interquartile range, IQR)方法和合成少数类过采样技术(synthetic minority oversampling technique, SMOTE)算法进行数据预处理,采用特征工程中的嵌入式方法对数据集进行特征分析,确定脑卒中诱发因素.以随机森林(random forest, RF)、极端梯度提升(extreme gradient boosting, XGB)和自适应提升(adaptive boosting, AdB)算法为第一层,高斯朴素贝叶斯(Gaussian naive bayes, GaNB)和支持向量机(support vector machine, SVM)为第二层,逻辑回归(logistic regression, LR)为元学习器构建超级学习者(super learner, SL)集成学习模型.仿真实验结果表明,相较于6种基础算法,SL模型预测效果最优,可为脑卒中的预测分析提供新的选择.

Super 304H钢在模拟烟气腐蚀环境中持久性能与组织演变研究

奥氏体钢在锅炉关键部位服役过程中面临烟气/煤灰腐蚀+应力协同作用的挑战,存在一定的安全隐患。在静态空气及烟气/煤灰腐蚀环境下,通过模拟实验台对Super 304H钢进行温度为650℃、应力为200~300 MPa的持久实验,研究腐蚀环境对其持久性能及组织演变的影响。结果表明:相较于空气环境,腐蚀条件下Super 304H钢持久寿命下降幅度可达83%,且随着持久应力的降低合金寿命下降更明显;烟气/煤灰腐蚀导致合金表面连续的腐蚀产物出现开裂、剥落,基体发生内硫化,在拉应力的共同作用下试样内部出现沿晶开裂等蠕变损伤;基体表面由于合金元素的损失,在高温下发生再结晶,并在实验结束后发生马氏体转变,腐蚀-应力环境中合金表面腐蚀产物的开裂、剥落,内硫化物的形成,表层再结晶细晶区的增厚和晶界损伤的加剧共同促进了Super 304H钢的持久断裂。烟气/煤灰腐蚀环境通过影响Super 304H钢腐蚀过程,恶化合金基体组织影响其持久性能。

ON A SUPER POLYHARMONIC PROPERTY OF A HIGHER-ORDER FRACTIONAL LAPLACIAN

Let 0<α<2,p≥1,m∈ℕ_(+).Consider the positive solution u of the PDE(-△)^(α/2+m)u(x)=u^(p)(x) in R^(n).(0.1) In[1](Transactions of the American Mathematical Society,2021),Cao,Dai and Qin showed that,under the condition u∈Lα,(0.1)possesses a super polyharmonic property (-△)^(k+α/2)u≥0 for k=0,1,⋯,m−1.In this paper,we show another kind of super polyharmonic property(−Δ)^(k)u>0 for k=1,⋯,m−1,under the conditions and(−Δ)^(m)u≥0.Both kinds of super polyharmonic properties can lead to an equivalence between(0.1)and the integral equation u(x)=∫_(R^(n))u^(p)(y)/|x-y|^(n-2m-α)dy.One can classify solutions to(0.1)following the work of[2]and[3]by Chen,Li,Ou.

比较Super Bond黏结夹板与石英纤维夹板固定在松动下前牙中的固定效果

目的比较Super Bond黏结夹板与石英纤维夹板固定在松动下前牙中的固定效果。方法将2021年1-12月在本院口腔科治疗的106例下前牙松动患者随机分为两组,每组53例,对照组使用石英纤维夹板固定,观察组使用Super Bond黏结夹板固定,对比两组的牙周夹板松动率、牙周指标、牙石指数、主观感受。结果两组治疗后1个月、3个月、6个月的牙周夹板松动率相当(P>0.05);治疗后3个月PD、AL、SBI、PLI相比,两组均相当(P>0.05);治疗后1个月、3个月的牙石指数+、++、+++相比,观察组均低于对照组(P<0.05);观察组治疗后3个月的美观度、舒适度评分高于对照组(P<0.05),但两组切割功能评分相当(P>0.05)。结论Super Bond黏结夹板与石英纤维夹板固定下前牙的效果相当,但Super Bond黏结夹板的牙石发生率低,美观度及舒适度更好。

Deep Learned Singular Residual Network for Super Resolution Reconstruction

Single image super resolution(SISR)techniques produce images of high resolution(HR)as output from input images of low resolution(LR).Motivated by the effectiveness of deep learning methods,we provide a framework based on deep learning to achieve super resolution(SR)by utilizing deep singular-residual neural network(DSRNN)in training phase.Residuals are obtained from the difference between HR and LR images to generate LR-residual example pairs.Singular value decomposition(SVD)is applied to each LR-residual image pair to decompose into subbands of low and high frequency components.Later,DSRNN is trained on these subbands through input and output channels by optimizing the weights and biases of the network.With fewer layers in DSRNN,the influence of exploding gradients is reduced.This speeds up the learning process and also improves accuracy by using skip connections.The trained DSRNN parameters yield residuals to recover the HR subbands in the testing phase.Experimental analysis shows that the proposed method results in superior performance to existingmethods in terms of subjective quality.Extensive testing results on popular benchmark datasets such as set5,set14,and urban100 for a scaling factor of 4 show the effectiveness of the proposed method across different qualitative evaluation metrics.

Meta-Learning Multi-Scale Radiology Medical Image Super-Resolution

High-resolution medical images have important medical value,but are difficult to obtain directly.Limited by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is often not high.Therefore,many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical images.However,current super-resolution algorithms only work on a single scale,and multiple networks need to be trained when super-resolution images of different scales are needed.This definitely raises the cost of acquiring high-resolution medical images.Thus,we propose a multi-scale superresolution algorithm using meta-learning.The algorithm combines a metalearning approach with an enhanced depth of residual super-resolution network to design a meta-upscale module.The meta-upscale module utilizes the weight prediction property of meta-learning and is able to perform the super-resolution task of medical images at any scale.Meanwhile,we design a non-integer mapping relation for super-resolution,which allows the network to be trained under non-integer magnification requirements.Compared to the state-of-the-art single-image super-resolution algorithm on computed tomography images of the pelvic region.The meta-learning multiscale superresolution algorithm obtained a surpassing of about 2%at a smaller model volume.Testing on different parts proves the high generalizability of our algorithm.Multi-scale super-resolution algorithms using meta-learning can compensate for hardware device defects and reduce secondary harm to patients while obtaining high-resolution medical images.It can be of great use in imaging related fields.

T92/Super304H异种钢焊接接头服役前后力学变化及其寿命评估

火电机组中过热器,再热器等部件需应用到异种钢焊接接头来满足不同环境的需求,这要求材料具有更高的耐高温腐蚀性能、屈服极限以及抗拉强度,而服役造成的老化会很大程度影响焊接件的性能,进而影响其寿命。为了研究服役对于异种钢焊接接头T92/Super304H的力学性能的影响。通过在610℃高温状态下,对已服役和未服役的焊接接头进行了不同加载速率的拉伸试验,获得了应力应变曲线及拟合曲线,通过扫描电子显微镜(SEM)分析了断口形貌。在相同温度下,对试样加载不同应力进行蠕变试验,获得了焊接接头的本构方程和蠕变寿命预测模型,分析了其断裂原因。结果表明:已服役和未服役的焊接接头高温拉伸时断裂均发生在T92侧(T92热影响区),试样有明显的颈缩;材料的初始应力值越大,蠕变寿命越短;随着初始应力水平的增加,蠕变应变速率变化加快;寿命预测拟合曲线和实际的蠕变试验一致。

格芯和Microchip宣布Microchip 28 nm SuperFlash嵌入式闪存解决方案投产

格芯(Global Foundries)与Microchip Technology Inc.(美国微芯科技公司)及其旗下子公司Silicon Storage Technology(SST)共同宣布,采用GF 28SLPe制程的SST ESF3第三代嵌入式SuperFlash技术NVM解决方案即将投产。在实施SST广泛部署的ESF3 SuperFlash技术方面,格芯确立了新的行业基准。该实施方案具有以下功能和优势:成本最低的28 nm HKMG ESF3解决方案,仅增加了10个掩模,包括真正的5 V IO CMOS器件;SST ESF3位单元尺寸小于0.05平方微米,极具竞争力;工作温度额定值为-40~125℃;读取访问时间为25 ns、编程时间为10μs、擦除时间为4 ms;超过100000次编程/擦除循环的耐用性;不影响使用GF 28SLPe平台合格IP的设计流程(EG流程);可立即提供4~32 Mb的现成宏程序;可从SST或GF获得定制宏设计支持。

New Superionic Memory Devices Can Provide Clues to the Human Memory Structure and to Consciousness

Since the work of Penrose and Hameroff the possibility is discussed that the location of human memory and consciousness could be connected with tubulin microtubules. If one would use superionic nano-materials rolled up to microtubules with an electrolyte inside the formed channels mediating fast ionic exchange of protons respectively lithium ions, it seems to be possible to write into such materials whole image arrays (pictures) under the action of the complex electromagnetic spectrum that composes these images. The same material and architecture may be recommended for super-computers. Especially microtubules with a protofilament number of 13 are the most important to note. We connected such microtubules before with Fibonacci nets composed of 13 sub-cells that were helically rolled up to deliver suitable channels. Our recent Fibonacci analysis of Wadsley-Roth shear phases such as niobium tungsten oxide , exhibiting channels for ultra-fast lithium-ion diffusion, suggests to use these materials, besides super-battery main application, in form of nanorods or microtubules as effectively working superionic memory devices for computers that work ultra-fast with the complex effectiveness of human brains. Finally, we pose the question, whether dark matter, ever connected with ultrafast movement of ordinary matter, may be responsible for synchronization between interactions of human brains and consciousness.

韩泰轮胎成为兰博基尼Super Trofeo挑战赛独家轮胎合作伙伴

日前,全球知名轮胎公司韩泰轮胎与著名跑车制造商兰博基尼的Squadra Corse赛事运动部门联手,从2023赛季开始,韩泰成为兰博基尼Super Trofeo挑战赛的官方技术合作伙伴和独家轮胎供应商。著名的兰博基尼Super Trofeo挑战赛包括欧洲、北美和亚洲三个洲际系列赛。其中亚洲系列赛休赛三年后的强势回归,赛程中包括9月8~10日的上海站比赛,将为中国赛车迷献上一场极速盛宴。