Millimetric devices for nerve stimulation:a promising path towards miniaturization

Nerve stimulation is a rapidly developing field,demonstrating positive outcomes across several conditions.Despite potential benefits,current nerve stimulation devices are large,complicated,and are powered via implanted pulse generators.These facto rs necessitate invasive surgical implantation and limit potential applications.Reducing nerve stimulation devices to millimetric sizes would make these interventions less invasive and facilitate broader therapeutic applications.However,device miniaturization presents a serious engineering challenge.This review presents significant advancements from several groups that have overcome this challenge and developed millimetricsized nerve stimulation devices.These are based on antennas,mini-coils,magneto-electric and optoelectronic materials,or receive ultrasound power.We highlight key design elements,findings from pilot studies,and present several considerations for future applications of these devices.

Band structures of strained kagome lattices

Materials with kagome lattices have attracted significant research attention due to their nontrivial features in energy bands.We theoretically investigate the evolution of electronic band structures of kagome lattices in response to uniaxial strain using both a tight-binding model and an antidot model based on a periodic muffin-tin potential.It is found that the Dirac points move with applied strain.Furthermore,the flat band of unstrained kagome lattices is found to develop into a highly anisotropic shape under a stretching strain along y direction,forming a partially flat band with a region dispersionless along ky direction while dispersive along kx direction.Our results shed light on the possibility of engineering the electronic band structures of kagome materials by mechanical strain.

Application of machine learning in perovskite materials and devices:A review

Metal-halide hybrid perovskite materials are excellent candidates for solar cells and photoelectric devices.In recent years,machine learning(ML)techniques have developed rapidly in many fields and provided ideas for material discovery and design.ML can be applied to discover new materials quickly and effectively,with significant savings in resources and time compared with traditional experiments and density functional theory(DFT)calculations.In this review,we present the application of ML in per-ovskites and briefly review the recent works in the field of ML-assisted perovskite design.Firstly,the advantages of perovskites in solar cells and the merits of ML applied to perovskites are discussed.Secondly,the workflow of ML in perovskite design and some basic ML algorithms are introduced.Thirdly,the applications of ML in predicting various properties of perovskite materials and devices are reviewed.Finally,we propose some prospects for the future development of this field.The rapid devel-opment of ML technology will largely promote the process of materials science,and ML will become an increasingly popular method for predicting the target properties of materials and devices.

Evaluation of the Oxidation Reactivity and Behavior of Exhaust Soot Particles from Diesel Engines with Different Emission Levels

The aim of this study was to investigate the oxidation reactivity and behavior of exhaust particulate matter(PM)from diesel engines.PM samples from two diesel engines(1K,CY4102)with different emission levels were collected by a thermophoretic system and a quartz filter.The oxidation reactivity,oxidation behaviors,and physicochemical properties of the PM samples were analyzed using thermogravimetric analysis(TGA),high-resolution transmission electron microscopy(HRTEM),Fourier-transform infrared spectrometry(FTIR),and Raman spectroscopy.The results showed that there was a great difference in the oxidation reactivity of soot particles emitted by the two different diesel engines.A qualitative analysis of the factors influencing oxidation reactivity showed that the nanostructure,degree of graphitization,and relative concentration of aliphatic C—H functional groups were the most important factors,whereas no significant correlation was found between the primary particle size and activation energy of the diesel soot.Based on the oxidation behavior analysis,the diesel soot particles exhibited both internal and surface oxidation modes during the oxidation process.Surface oxidation was dominant during the initial stage,and as oxidation progressed,the mode gradually changed to internal oxidation.Internal oxidation mode of soot particles from the 1K engine was significantly higher than that of CY4102.

Impact of Safety-Maintenance Practices on the Overall Performance of an Industry

The study aims to evaluate how safety-maintenance practices affect the mechanical engineering industry’s overall performance in Ghana. The study used a descriptive survey design technique to ascertain the type of maintenance engineering that was practiced in Ghanaian mechanical engineering workshops at the time of the study. In the mechanical engineering workshops, respondents provided both qualitative and quantitative data using a variety of data collecting instruments, with the quantitative approach being more common. The study employed Kumasi, Tamale, and Accra’s mechanical engineering workshops as a case study. The number of mechanical engineering workshop enterprises that made up the sample size for the questionnaire administration was sixty (60), chosen at random from the AGI membership registry. Primary data was gathered using interview guides and questionnaires. To analyse the data, descriptive statistics were employed. According to the study’s findings, mechanical engineering companies combined different maintenance techniques in order to best fit their organisational culture and equipment. Preventive shut-down, with a mean score of 4.78 and RII = 0.98, placing first (1st) in the Likert rating order, is the most frequently used maintenance system by respondents. The maintenance procedures employed by mechanical engineering organisations were influenced not only by their equipment and organisational culture but also by other factors such as cost, personnel expertise and external partnerships.

Performance, Combustion and Emission Characteristics of Oxygenated Diesel in DI Engines: A Critical Review

The transition from non-renewable to renewable energy sources is a significant challenge of our time. In the fuel industry, oxygenated additives such as butanol are transforming conventional fuels into renewable biofuels. This technology has been utilized in reciprocating engines for decades. This paper reviews the viability of using an n-butanol blend as a short-term replacement for diesel by analyzing its physical and chemical properties, combustion, performance, and emission characteristics in compression ignition (CI) engines under various conditions, including variable load, speed, acceleration, and both stationary and transient cycles. N-Butanol exhibits higher viscosity, better lubricity, higher heating value, improved blend stability, enhanced cold-flow properties, and higher density. These factors influence spray formation, injection timing, atomization, and combustion characteristics. Its higher oxygen content improves the diffusion combustion stage and efficiency. Adding 5% and 10% n-butanol to diesel increases pressure and apparent heat release rate, slightly reduces temperature, and improves thermal efficiency, with mixed effects on CO and THC emissions and a notable decrease in particulate matter emissions. Fuel consumption increases, while the impact on NOx emissions varies. A 10% butanol blend is considered optimal for enhancing performance and reducing particulate emissions without significantly affecting NOx emissions. Blending up to 40% butanol with diesel does not require engine modifications or ECU recalibrations in engines calibrated for pure diesel. Due to its advantageous properties and performance, n-butanol is recommended as a superior alcohol-diesel blend than ethanol for short-term diesel replacement.

Engines of Advancement

Chinese investment contributes to the industrialisation of Africa.Hasnaine Yavarhoussen,CEO of Groupe Filatex,the leading private energy producer in Madagascar,travelled to Beijing on the occasion of the 2024 Summit of the Forum on China-Africa Cooperation(FOCAC).As a key economic player in Madagascar and the African continent,Groupe Filatex participated in this high-level forum as part of the official Malagasy economic delegation.

Construction Technology of Lightning Protection Devices in Building Electrical Installation Engineering

To better improve the electrical safety of buildings and fulfill the role of lightning protection and grounding,this article combines cases and discusses seven aspects of lightning protection devices’construction technology.These aspects include the lightning protection classification of buildings,air terminals,down conductors,grounding devices,division of lightning protection zones,and lightning electromagnetic pulse shielding.Through the introduction of this article,readers can gain a comprehensive understanding of the application and value of lightning protection grounding construction technology in building electrical installation projects.

A Study on How Urban Rail Operators Can Secure New Growth Engines for the Future Approach: The Case of Underground Urban Logistics System

Seoul Metro is Seoul’s leading metro company, transporting up to 3 billion people annually. However, future ridership is expected to plummet due to an aging and shrinking population with one of the fastest declining total fertility rates in the world. The COVID-19 pandemic in 2019 accelerated this phenomenon. On the contrary, the e-commerce and home delivery industries have developed significantly since COVID-19. Seoul’s current logistics infrastructure cannot handle it. Under the inflection point of declining passenger transportation demand and increasing urban logistics demand, urban rail operators need new growth engines. Therefore, it is necessary to consider the introduction of an UULS (underground urban logistics system) that transports parcels instead of passengers through urban railways. If the UULS becomes a reality, it can be expected to secure scarce logistics land in cities, protect the environment and prevent traffic congestion by operating eco-friendly mass urban transportation, and acquire new revenue sources for urban rail operators. The UULS’s B/C ratio is 1.32. The sensitivity analysis shows that the ratio is above 1 in most cases where the unit cost of transportation is not significantly reduced.

京津风沙源区NPP时空变化及其对治理工程实施的响应

利用遥感大数据对生态治理工程区域的净初级生产力和固碳能力进行长期动态监测可以实现对治理工程的实施效果的评价,同时为区域“碳中和”目标的实现及可持续发展提供有力支撑。利用Google Earth Engine(GEE)云计算平台,基于改进的CASA模型对京津风沙源治理工程区域的NPP进行计算。运用Sen斜率分析和MK趋势分析方法对2001—2020年间的NPP进行时空变化分析,并分析NPP对京津风沙源治理工程实施的响应。结果表明:1)在京津风沙源工程治理期间,京津风沙源区NPP总体呈波动上升趋势,平均增速为2.21 gC m^(-2)a^(-1),其中极显著增加区域占38.03%,说明京津风沙源治理工程对我国“碳中和”任务起到了积极作用,增加了区域的固碳能力;2)空间尺度上,京津风沙源区NPP和固碳量空间异质性较大,空间分布上主要呈现东部高,西部低的特点,其中,暖温带落叶阔叶林区域最高,温带荒漠区域最低;3)治理工程的实施所带来的NPP增长的速度在不同的区域并不一致,2001—2020年的NPP增速京津冀地区(4.74 gC m^(-2)a^(-1))>山西地区(4.52 gC m^(-2)a^(-1))>陕西地区(3.53 gC m^(-2)a^(-1))>内蒙古地区(1.55 gC m^(-2)a^(-1));4)生态工程实施所带来的生态环境的改善总体呈现先慢后快的特点,绝大部分区域后十年间的变化速率都显著大于前十年,而在生态环境较为恶劣、荒漠区域广布的内蒙古地区,生态环境的改善则具有一定的滞后性,2001—2010年NPP增速仅为0.04 gC m^(-2)a^(-1),直到2011年,NPP才开始有较为明显的增长,2011—2020年NPP增速为1.67 gC m^(-2)a^(-1)。风沙源治理工程需要长期坚持,才能取得更明显的成效。

Performance optimization on finite-time quantum Carnot engines and refrigerators based on spin-1/2 systems driven by a squeezed reservoir

We investigate the finite-time performance of a quantum endoreversible Carnot engine cycle and its inverse operation-Carnot refrigeration cycle,employing a spin-1/2 system as the working substance.The thermal machine is alternatively driven by a hot boson bath of inverse temperatureβ_(h)and a cold boson bath at inverse temperatureβ_(c)(>βh).While for the engine model the hot bath is constructed to be squeezed,in the refrigeration cycle the cold bath is established to be squeezed,with squeezing parameter r.We obtain the analytical expressions for both efficiency and power in heat engines and for coefficient of performance and cooling rate in refrigerators.We find that,in the high-temperature limit,the efficiency at maximum power is bounded by the analytical valueη_(+)=√sech(2r)(1-η_(C)),and the coefficient of performance at the maximum figure of merit is limited byε_(+)=√sech(2r)(1+ε_(C))/sech(2r)(1+ε_(C))-εC)-1,whereη_(C)=1-β_(h)/β_(c)andε_(C)=β_(h)/(β_(c)-β_(h))are the respective Carnot values of the engines and refrigerators.These analytical results are identical to those obtained from the Carnot engines based on harmonic systems,indicating that the efficiency at maximum power and coefficient at maximum figure of merit are independent of the working substance.

Predicting Future Cryptocurrency Prices Using Machine Learning Algorithms

Cryptocurrency price prediction has garnered significant attention due to the growing importance of digital assets in the financial landscape. This paper presents a comprehensive study on predicting future cryptocurrency prices using machine learning algorithms. Open-source historical data from various cryptocurrency exchanges is utilized. Interpolation techniques are employed to handle missing data, ensuring the completeness and reliability of the dataset. Four technical indicators are selected as features for prediction. The study explores the application of five machine learning algorithms to capture the complex patterns in the highly volatile cryptocurrency market. The findings demonstrate the strengths and limitations of the different approaches, highlighting the significance of feature engineering and algorithm selection in achieving accurate cryptocurrency price predictions. The research contributes valuable insights into the dynamic and rapidly evolving field of cryptocurrency price prediction, assisting investors and traders in making informed decisions amidst the challenges posed by the cryptocurrency market.

基于变化更新的中东欧国家森林覆盖制图

[目的]分析中东欧国家森林资源覆盖状况,了解中东欧各国林业的现实情形和独特优势,为中国与中东欧国家加强林业合作提供基础数据。[方法]基于Google Earth Engine(GEE)平台获取中东欧国家2020年生长季无云影像,利用随机森林算法对影像进行分类,应用连续变化检测和分类算法得到森林变化信息并更新初步分类结果,最终获得中东欧国家土地覆盖分类结果。利用欧盟统计局土地利用/覆盖区域框架调查(LUCAS)数据、目视解译数据以及联合国粮农组织统计数据(FAOSTAT)对本研究分类结果进行验证和评估,结合谷歌高分辨率影像对制图结果进行分析。[结果]本研究分类结果利用LUCAS数据和目视解译数据的森林类型用户精度分别为0.930和0.911,生产者精度分别为0.860和0.956,总体精度分别为0.810和0.881,整体上优于GlobeLand30 2020产品(森林类型用户精度分别为0.920和0.900,生产者精度分别为0.690和0.840,总体精度分别为0.700和0.832)。根据研究结果计算出中东欧国家总体森林覆盖率为39.6%,相比GlobeLand30 2020结果(34.4%),与FAOSTAT的森林覆盖率(40.0%)更接近。目视上看,本制图结果在细节刻画上比GlobeLand30 2020产品更丰富,更能准确反映森林分布特征。截至2020年,中东欧国家森林覆盖呈北部、东南地区和西南地区丰富密集,中部分布广泛且相对较少的特点,爱沙尼亚、拉脱维亚、斯洛文尼亚、黑山等国家森林分布茂密,波兰、匈牙利等国家森林分布较为稀少。[结论]针对中东欧国家森林覆盖应用需求,本研究提出基于产品变化更新的森林覆盖制图方法,生产了中东欧国家2020年森林覆盖产品。本研究方法可为大区域森林覆盖制图提供新的借鉴和参考,结果有助于宏观了解中东欧国家森林覆盖状况。

“产、学、研、品、用”融合教学模式探索 --以西安工业大学卓越机械工程师班为例

该文针对机械类卓越工程创新人才解决复杂工程问题能力培养的现状,进行机械类卓越工程师班专业课程“产、学、研、品、用”融合协同教学模式探索研究并提出改进措施。从教学理念、教学资源、教学方法和评价机制等几个方面进行改革。构建以“能力导向式培养”和“品商”素养为核心的机械类卓越工程师班专业课程教学模式和考核制度,进而提升卓越工程创新人才的解决复杂工程问题能力和综合素养。

长江经济带岩溶塌陷分布、成因及其对工程建设的影响

[研究目的]岩溶塌陷是长江经济带主要环境地质问题之一,开展长江经济带岩溶塌陷分布、成因及其对工程建设的影响研究,对长江经济带立体综合交通走廊建设和新型城镇化建设地质环境安全保障具有重要意义。[研究方法]本文系统梳理了长江经济带岩溶塌陷研究成果,从岩溶环境特征、岩溶塌陷的成因类型和机制、发育及分布规律、对工程建设的影响及防控措施几个方面进行论述。[研究结果]研究结果表明,长江经济带岩溶塌陷易发区面积约25.4万km^(2),有记录的岩溶塌陷灾害2146处,矿山疏干排水、抽水、工程施工等是这一地区岩溶塌陷的主要诱发因素。长江经济带岩溶塌陷具有以下发育分布规律:一是具有区域性和地带性的分布特征;二是发育地层一般为均匀状纯碳酸盐岩,沿断裂破碎带、褶皱轴部裂隙发育带、可溶岩与非可溶岩接触地带等岩溶洞隙密集发育带分布;三是多发生在岩溶地下水强径流带、河流两岸等地下水位变化幅度大、水动力条件易发生急剧变化的地段;四是多发生在人类工程活动强烈的地区,塌陷的规模取决于人类活动的性质和强度。为了降低岩溶塌陷对工程建设和安全运营影响,本文同时提出了相关建议和对策。[结论]长江经济带岩溶塌陷分布广、危害大,高易发区内线性工程、重要城市群等规划建设应对这一环境地质问题引起重视,该研究成果可为长江经济带国土空间规划、地质灾害防治提供基础支撑和理论依据。

国际科技竞争环境下高等工程教育改革大势:新工程教育十大革新理念

分析、总结世界科技飞速发展、国际竞争日趋激烈大势之下的高等工程教育创新思想与实践,以国际国内相关研究为基础,综合十大类工程教育特别是卓越工程教育改革重要理念,并以工程教育的机制创新、教育思想创新、教育方法创新3个部分分类归纳相应的工程人才培育理念,突出本土工程—社会问题导向和面向未知工程世界发展格局,强调多个具有时代特征的新理念,如基础科学与解决工程“瓶颈”问题紧密结合、高效产学研构造、跨学科工程原型创造等重要机制和运行思想理念,以及基于项目的学习、学生为中心的学习、工程教育平台设施开发等方法理念。这些创新理念对我国工程教育,特别是高等工程教育机构推进卓越工程师教育改革提供政策和研究参考。

职业教育现场工程师培养:何以可为与何以作为

面向先进制造业等重点领域的数字化、智能化职业场景,实施职业教育现场工程师专项培养,既是增强职业教育适应性、推进产业转型升级所需,亦是优化人才供给结构赋能制造强国建设、彰显职业教育类型特征所向,有其自身“可为”的逻辑遵循。在实践中,应当深化产教融合,打造基于专业群的现场工程师学院,推进数字赋能、创新基于学徒制的培养模式,实施专业认证、构建“专业认证+职业资格证书”的培养标准,强化关键能力、培育教师教学创新团队,加强专题研究、夯实现场工程师教育理论与实践根基,以实际“作为”贡献职教智慧与工程力量。

新工科背景下“超星学习通+奥尔堡PBL”模式在制药工程类课程教学中的改革与实践

新工业革命时代的制药产业正发生着日新月异的变革,高校对制药工程专业人才的培养目标要满足行业发展需求,加强具有工程创新能力的工程师培养。制药工程专业的工程类课程是连接理论素养与工程实践能力的桥梁,处于其课程体系的核心位置。为满足医药发展新业态对制药工程专业人才的需求,该研究根据制药专业工程类课程特点,围绕新工科建设内涵,从整合优化教学内容、改革创新教学方式、完善考核方式与评价体系三个层面进行基于“超星学习通+奥尔堡PBL”模式的制药工程类课程教学改革,发挥教师关键作用,拓展课程内涵,丰富教学活动,实现对学生实践能力和工程创新能力的培养,尽快完成由学生向制药工程师的转变以及高等院校与现代工厂的“对接”,达到全面提高制药工程人才培养的育人成效,对制药工程专业工程类课程教学发展起到借鉴作用。

智能时代人因科学研究的新范式取向及重点

本文首先提出了“人因科学”这一创新的学科群概念来表征工程心理学、人因工程、工效学、人机交互等相近领域。尽管这些领域的研究角度不一样,但是它们分享共同的研究理念、对象以及目的。我们近期的研究表明,人工智能(AI)新技术带来了一系列新的人因问题,而作为人因科学研究对象的人机关系呈现出从“人机交互”向“人智组队式合作”的跨时代演进。这些变化对人因科学研究提出了新问题和新挑战,需要我们重新审视基于非智能技术的人因科学研究范式和重点。在此背景下,本文梳理人因科学研究范式取向跨时代的演进,总结我们近5年所提出的一系列用于丰富人因科学研究范式的新概念模型和框架,其中包括人智协同认知系统、人智协同认知生态系统以及智能社会技术系统的模型和框架。本文进一步从人因科学研究范式取向的角度进一步提升这些概念模型和框架,提出智能时代人因科学研究的三种新范式取向,分析相应的应用意义,并展望今后的研究方向。同时,针对智能时代人因科学研究重点的跨时代转移新特征,本文从“人智交互”“智能人机界面”“人智组队合作”三个方面展望了今后人因科学的研究重点,揭示出人因科学新研究范式取向对未来研究重点的作用。我们认为,人因科学的研究范式取向和研究重点互为影响,互为促进,智能时代的人因科学研究需要多样化、创新的研究范式取向,从而进一步推动人因科学的发展。

矿物加工工程专业研究方法课程改革与实践

“研究方法”是矿物加工工程专业本科生的必修核心专业课,课程具有综合性和实践性强的特点,其目的是培养学生综合运用所学基础理论、专业知识分析和解决实际科学问题的能力,为从事矿物加工及相关行业的研究开发工作奠定基础。但在新工科背景下,矿物加工的研究领域不限于传统的矿产资源,而是扩展到非传统矿产资源、固废资源、二次资源等的选冶联合处理;同时研究方法、测试手段等也取得长足的进步;现有的研究方法教学内容设置与新时代卓越工程师培养要求存在较大差距。为适应矿物加工人才培养的新要求,构筑资源加工研究方法学科交叉知识新体系,并对教学方法和评价体系进行改革。