Using machine learning to identify primary features in choosing electric vehicles based on income levels

An electric vehicle is becoming one of the popular choices when choosing a vehicle.People are generally impressed with electric vehicles’zero-emission and smooth drives,while unstable battery duration keeps people away.This study tries to identify the primary factors that affect the likelihood of owning an electric vehicle based on different income levels.We divide the dataset into three subgroups by household income from$50,000 to$150,000 or low-medium income level,$150,000 to$250,000 or medium-high income level,and$250,000 or above,the high-income level.We considered several machine learning classifiers,and naive Bayes gave us a relatively higher accuracy than other algorithms in terms of overall accuracy and F1 scores.Based on the probability analysis,we found that for each of these groups,one-way commuting distance is the most important for all three income levels.

Spectral characteristic of laser-induced plasma in soil

The spectral characteristic of laser-induced plasma in soil was studied in this work,laser-induced breakdown spectroscopy was used to analyze the spectral characteristic of plasma under the condition of different time delays and irradianccs.Moreover,the time evolution characteristics of plasma temperature and electron density were discussed.Within the time delay range of 0-5μs,the spectral intensity of the characteristic lines of Si I:288.158 nm,Ti I:336.126 nm.Al I:394.400 nm and Fe I:438.354 nm of the four main elements in two kinds of national standard soil decayed exponentially with time.The average lifetime of the spectral lines was nearly 1.56μs.Under the condition of different time delays,the spectral intensity of Pb I:405.78 nm in soil increased linearly with laser energy.However,the slope between the spectral intensity and laser energy decreased exponentially with the increase in time delay,from 4.91 to 0.99 during 0-5μs.The plasma temperature was calculated by the Boltzmann plot method and the electron density was obtained by inversion of the full width at half maximum of the spectrum.The plasma temperature decreased from 8900 K to 7800 K and the electron density decreased from 1.5 x 1Ol7cm-3 to 7.8 x lO16cm-3 in the range of 0-5μs.

Lewis acid-doped transition metal dichalcogenides for ultraviolet–visible photodetectors

Ultraviolet photodetectors(UV PDs)are widely used in civilian,scientific,and military fields due to their high sensitivity and low false alarm rates.We present a temperature-dependent Lewis acid p-type doping method for transition metal dichalcogenides(TMDs),which can effectively be used to extend the optical response range.The p-type doping based on surface charge transfer involves the chemical adsorption of the Lewis acid SnCl_(4)as a light absorption layer on the surface of WS_(2),significantly enhancing its UV photodetection performance.Under 365 nm laser irradiation,WS_(2)PDs exhibit response speed of 24 ms/20 ms,responsivity of 660 mA/W,detectivity of 3.3×10^(11)Jones,and external quantum efficiency of 226%.Moreover,we successfully apply this doping method to other TMDs materials(such as MoS_(2),MoSe_(2),and WSe_(2))and fabricate WS_(2) lateral p–n heterojunction PDs.

基于微生物作为智能模板的电催化剂制备与应用研究进展

通过电催化实现可再生能源的存储与转化对于改善能源结构、保护生态环境、实现碳达峰和碳中和的国家战略具有重大意义。而开发低成本、高效的电催化剂成为全世界科学家共同面对的挑战。微生物在自然界中广泛存在,具有结构、组成和代谢丰富的特点,可以成为电催化剂的模板以及碳、磷、硫等非金属元素以及金属元素的来源,而且具有无毒、生产可重复性好、易于规模化等优点,已成为电催化剂制备的新趋势。对此,本文综述了微生物“智能”引导制备电催化剂的发展及在电催化析氢(HER)、电催化析氧(OER)、氧还原反应(ORR)、二氧化碳还原(CO_(2)RR)、锂电池(LBs)等领域的应用现状。希望有助于推动微生物代谢与催化剂微纳结构关系以及与催化反应的构效关系的深入理解,最后针对这类材料的问题挑战及其未来发展方向进行了探讨与展望。

Detection of heavy metals in water samples by laser-induced breakdown spectroscopy combined with annular groove graphite flakes

The use of laser-induced breakdown spectroscopy(LIBS) for the analysis of heavy metals in water samples is investigated. Some factors such as splashing, surface ripples, extinction of emitted intensity, and a shorter plasma lifetime will influence the results if the water sample is directly measured. In order to avoid these disadvantages and the ‘coffee-ring effect', hydrophilic graphite flakes with annular grooves were used for the first time to enrich and concentrate heavy metals in water samples before being analyzed by LIBS. The proposed method and procedure have been evaluated to concentrate and analyze cadmium, chromium, copper, nickel, lead,and zinc in a water sample. The correlation coefficients were all above 0.99. The detection limits of 0.029, 0.087, 0.012, 0.083, 0.125, and 0.049 mgl^(-1) for Cd, Cr, Cu, Ni, Pb, and Zn,respectively, were obtained in samples prepared in a laboratory. With this structure, the heavy metals homogeneously distribute in the annular groove and the relative standard deviations are all below 6%. This method is very convenient and suitable for online in situ analysis of heavy metals.

Online calibration of laser-induced breakdown spectroscopy for detection of heavy metals in water

In order to reduce the fluctuation of LIBS detection spectrum of liquid sample,the full-spectrum sum method and the internal standardization method is adopted,using an equal-RSD normalization algorithm to calibrate the detection spectrum.Experiment result shows that the full-spectrum sum method reduced the RSD of parallel samples of Cd and Cr to 9.4% and 11.06% from 28.32% and 31.93% respectively,yielded better overall calibration than the singleelement internal standardization approach,thereby suggesting that the former method is convenient and effective for online calibration of LIBS for detection of aqueous heavy metals.

Effect of Atorvastatin on Serum MMP-2,MMP-9 and TIMP-1 in Rabbits with Chronic Heart Failure

Objective： To observe the effects of atorvastatin on serum matrix metalloproteinase-2（MMP-2）, matrix metaUoproteinase-9（MMP-9）, and the tissue inhibitor of metalloproteinase-1（TIMP-1） in the development of chronic heart failure. To investigate the role of atorvastatin in the therapy of chronic heart failure and determine its possible mechanism of action. Methods： Thirty Japanese Big Ear rabbits were randomly selected and divided into 3 groups： sham-operated group（SO group）, heart failure control group（HC group） and heart failure atorvastatin therapy group（HA group）, with 6, 12 and 12 animals in the respective groups. Volume overloading was produced in the HC group and HA group animals by creating an aortic insufficiency, induced by damaging the aortic valve with a catheter introduced through the carotid artery. After 14 days, abdominal aorta constriction was performed in order to obtain a pressure overload. Six weeks later rabbits in the HA group were administered atorvastatin 3mg· Kg^-1·d^-1 for 4 weeks, at which time the experiment was terminated. Arterial blood was drawn and serum levels of MMP-2, MMP-9 and TIMP-1 were measured in all groups at the same time using an ELISA method. Results： Structural and functional indicators of chronic heart failure（CHF） were seen in both the HC and HA groups, but atorvastatin significantly reduced the observed effects. The serum concentrations of MMP-2, MMP-9 and TIMP-1 were at low levels in all three groups at the start of the study, with no difference between them（P 〈 0.05）. At the end of 6th week concentrations were significantly increased in the HC and HA groups compared with the SO group（P 〈 0.05）, but there were no differences between the HC group and HA group（P 〉 0.05）. The increased concentrations in HC group continued to the end of the experiment, but values in the HA group were all lower than those in the HC group by the end of the experiment（P 〈 0.05）. Conclusion： Serum concentrations of MMP-2, MMP-9 and TIMP-1 increase significantly during the course of CHF, paralleling the pathological progress of CHF. Atorvastatin benefits CHF, and the decreased serum levels of MMP-2, MMP-9 and TIMP-1 may be one of the drug＇ s mechanism of action.

Steering spatially separated dual sites on nano-TiO_(2)through SMSI and lattice matching for robust photocatalytic hydrogen evolution

Spatial isolation of different functional sites at the nanoscale in multifunctional catalysts for steering reaction sequence and paths remains a major challenge.Herein,we reported the spatial separation of dual-site Au and RuO_(2)on the nanosurface of TiO_(2)(Au/TiO_(2)/RuO_(2))through the strong metal-support interaction(SMSI)and the lattice matching(LM)for robust photocatalytic hydrogen evolution.The SMSI between Au and TiO_(2)induced the encapsulation of Au nanoparticles by an impermeable TiO_(x)overlayer,which can function as a physical separation barrier to the permeation of the second precursor.The LM between RuO_(2)and rutile-TiO_(2)can increase the stability of RuO_(2)/TiO_(2)interface and thus prevent the aggregation of dual-site Au and RuO_(2)in the calcination process of removing TiO_(x)overlayer of Au.The photocatalytic hydrogen production is used as a model reaction to evaluate the performance of spatially separated dual-site Au/TiO_(2)/RuO_(2)catalysts.The rate of hydrogen production of the Au/TiO_(2)/RuO_(2)is as high as 84μmol h^(−1)g^(−1)under solar light irradiation without sacrificial agents,which is 2.5 times higher than the reference Au/TiO_(2)and non-separated Au/RuO_(2)/TiO_(2)samples.Systematic characterizations verify that the spatially separated dual-site Au and RuO_(2)on the nanosurface of TiO_(2)can effectively separate the photo-generated carriers and lower the height of the Schottky barrier,respectively,under UV and visible light irradiation.This study provides new inspiration for the precise construction of different sites in multifunctional catalysts.

Characteristics of optical emission during laser-induced damage events of fused silica

Spontaneous optical emission properties of laser-produced plasma during laser damage events at input and exit surfaces of fused silica were retrieved and compared.We show that plasma at the input surface is much larger in size and exhibits significantly higher electron number density and excitation temperature,even when smaller laser energy was used.This effect was attributed to the stronger laser–plasma coupling at the input surface.In addition,a strong continuum background containing three peaks at 1.3eV,1.9eV,and 2.2eV was observed at the exit surface,and possible origins for this effect are also discussed.

Spatially selective p-type doping for constructing lateral WS_(2) p-n homojunction via low-energy nitrogen ion implantation

The construction of lateral p-n junctions is very important and challenging in two-dimensional(2D)semiconductor manufacturing process.Previous researches have demonstrated that vertical p-n junction can be prepared simply by vertical stacking of 2D materials.However,interface pollution and large area scalability are challenges that are difficult to overcome with vertical stacking technology.Constructing 2D lateral p-n homojunction is an effective strategy to address these issues.Spatially selective p-type doping of 2D semiconductors is expected to construct lateral p-n homojunction.In this work,we have developed a low-energy ion implantation system that reduces the implanted energy to 300 eV.Low-energy implantation can form a shallow implantation depth,which is more suitable for modulating the electrical and optical properties of 2D materials.Hence,we utilize low-energy ion implantation to directly dope nitrogen ions into few-layer WS_(2) and successfully realize a precise regulation for WS_(2) with its conductivity type transforming from n-type to bipolar or even p-type conduction.Furthermore,the universality of this method is demonstrated by extending it to other 2D semiconductors,including WSe_(2),SnS_(2) and MoS_(2).Based on this method,a lateral WS_(2) p-n homojunction is fabricated,which exhibits significant rectification characteristics.A photodetector based on p-n junction with photovoltaic effect is also prepared,and the open circuit voltage can reach to 0.39 V.This work provides an effective way for controllable doping of 2D semiconductors.

A novel spatio-temporal trajectory data-driven development approach for autonomous vehicles

Nowadays,autonomous driving has been attracted widespread attention from academia and industry.As we all know,deep learning is effective and essential for the development of AI components of Autonomous Vehicles(AVs).However,it is challenging to adopt multi-source heterogenous data in deep learning.Therefore,we propose a novel data-driven approach for the delivery of high-quality Spatio-Temporal Trajectory Data(STTD)to AVs,which can be deployed to assist the development of AI components with deep learning.The novelty of our work is that the meta-model of STTD is constructed based on the domain knowledge of autonomous driving.Our approach,including collection,preprocessing,storage and modeling of STTD as well as the training of AI components,helps to process and utilize huge amount of STTD efficiently.To further demonstrate the usability of our approach,a case study of vehicle behavior prediction using Long Short-Term Memory(LSTM)networks is discussed.Experimental results show that our approach facilitates the training process of AI components with the STTD.

A SLC31A1-MEK-DNMT1-miR-124 feedback loop contributes to pancreatic cancer progression

Although the role of copper (Cu) in promoting KRas- or BRaf-mutation driven cancers via activating MEK1/2 kinases is known, the mechanism by which the copper transporter SLC31A1 (CTR1) is upregulated in pancreatic cancer (PDAC, KRas mutation) is not defined. In this study, we provide evidence that MEK signal maintains a high level of SLC31A1 through silencing the expression of miR-124-3P (miR-124) via a novel MEK-DNMT1-miR-124 feedback loop in PDAC cells. Further, we reveal that miR-124 directly targets suppression of SLC31A1, and miR-124 introduction together with tetrathiomolybdate (TM) treatment hampered pancreatic cancer growth in vitro and in vivo. Our results demonstrate that a SLC31A1-MEK-DNMT1-miR-124 feedback loop is an important pathway to maintain copper absorption and promote pancreatic cancer progression, and we hope to provide a Cu-chelation as an adjuvant treatment strategy, to block the progression in Kras mutant PDAC patients.