“五一”小长假终究还是过去了，电量不足的小伙伴们，带上你的小马达，跟我一起充充“电”吧！ 第一站：电池诞生记 1 ） 1746 年：莱顿瓶 莱顿大学的马森布罗克用一支枪管悬在空中，用起电机与枪管连着，另用一根铜线从枪管中引出，浸入一个盛有水的玻璃瓶中，一个助手一只手握着玻璃瓶，马森布罗克在一旁使劲摇动起电机。这时他的助手不小心将另一只手与枪管碰上， 随后 猛然感到一次强烈的电击，喊了起来。马森布罗克由此得出结论：把带电体放在玻璃瓶内可以把电保存下来 ， 后来人们就把这个蓄电的瓶子称作“ 莱顿瓶 ” ，这个实验称为 “ 莱顿瓶实验 ” 。 2 ） 1786 年：“生物电” 意大利 解剖学家伽伐尼在做青蛙解剖时，两手分别拿着不同的金属器械，无意中同时碰在青蛙的大腿上，青蛙腿部的肌肉立刻抽搐了一下，仿佛受到电流的刺激，而只用一种金属器械去触动 青蛙 ，却并无此种反应。伽伐尼认为，出现这种现象是因为动物躯体内部产生的一种电，他称之为“ 生物电 ” 。 3 ） 1799 年：伏特电堆 意大利物理学家伏特把一块锌板和一块银板浸在 盐水 里，发现连接两块金属的导 线中有电流通过。于是，他就把许多锌片与银片之间垫上浸透盐水的绒布或纸片，平叠起来。用手触摸两端时，会感到强烈的电流刺激。伏特用这种方法成功的制成了世界上第一个电池──“ 伏特电堆 ” 。 4 ） 1836 年：丹尼尔电池 英国的 丹尼尔 对“ 伏特电堆 ” 进行了改良。他使用 稀硫酸 作电解液，解决了电池极化问题，制造出第一个不极化，能保持 平衡 电流的锌─ 铜电池，又称 “ 丹尼尔电池 ” 。 5 ） 1860 年：蓄电池 法国的普朗泰发明出用铅做电极的电池。当电池使用一段使电压下降时，可以给它通以反向电流，使电池电压回升。因为这种电池能充电，可以反复使用，所以称它为“ 蓄电池 ” 。 电池已经诞生了 200多年，现在仍然在前进。无论是过去还是现在，电池的目标都没有改变：随时随地让人享受电能的巨大恩惠。 如何预测电池的剩余电量？如何提高电池性能？英国学者为你解惑 ~ 第二站：好文推荐 VRLA 电池系统中分析孔隙几何形状及识别方块效应的高级预测机制 An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System Alessandro Mariani 1 , Kary Thanapalan 1 , Peter Stevenson 2 , Jonathan Williams 1 1. Faculty of Computing, Engineering and Science , University of South Wales , Pontypridd , UK 2. Yuasa Battery (UK) Ltd , Rassau Industrial Estate , Ebbw Vale , UK 收录信息： Alessandro Mariani, Kary Thanapalan, Peter Stevenson etc. An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System . International Journal of Automation and Computing , 2017,14(1): 21-32. 全文链接： 1） Springer Link: https://link.springer.com/article/10.1007/s11633-016-1040-0 2） IJAC 官网： http://www.ijac.net/EN/abstract/abstract1855.shtml 文章概要： 本文提出一种高级预测机制，用于 阀控密封铅酸（ VRLA ）电池 系统中的孔隙几何形状分析以及方块效应识别。本研究首先构建了一个数学模型来识别 VRLA 电池的剩余电量，而后通过电化学阻抗技术得出实验数据，用以验证该模型。最后，基于数据分析，得出低性能电池中发生扩散限制的原因。通过本研究可知，电极大小及孔分布将影响电池在充电及放电时的电化及电解过程。 关键词 ： Positive active material, crystal structure, valve regulated lead acid (VRLA) batteries, modelling, estimation and recovery techniques. 作者简介 ： Alessandro Mariani received the B. Eng. degree from University of Glamorgan, UK in 2010. He is currently a Ph.D. degree candidate at University of South Wales, UK. His research interests include lead acid battery technology and electrochemical performance analysis. ORCID iD: 0000-0001-5810-2681 Kary Thanapalan received the B.Eng. degree in control engineering from City University London, UK. Later he received the Ph.D. degree in aerospace control systems from the University of Liverpool, UK . He is currently working as a senior researcher in the faculty of computing, engineering and sciences, University of South Wales, UK, and a leading researcher in the fields of energy and renewable energy and control and automation engineering. His research interests include control system design, renewable energy and optimization analysis. ORCID iD: 0000-0001-6398-4340 Peter Stevenson received the M. Sc. degree in chemistry from the University of Cambridge, UK in 1979. He is currently working as senior technical co-ordinator at the Yuasa Battery (Europe) Ltd. His research interests include lead acid and lithium battery technology. ORCID iD: 0000-0003-3894-2207 Jonathan Williams received the M. Eng. degree in mechatronic engineering and has since worked with numerous industrial companies and specialist materials companies at the University of South Wales, UK . He is currently working as a CAPSE director at the University of South Wales, UK, and a leading researcher in the development of new innovative energy storage system and solutions. His research interests include power system engineering and lithium based energy storage. 部分内容整理自网络，参见： http://tech.qq.com/a/20090524/000025.htm http://baike.so.com/doc/1207846-1277666.html IJAC International Journal of Automation and Computing IJAC的出版服务不会止于论文发表。在论文发表后，IJAC也在积极地通过多种方式帮助作者提升研究成果的影响力，“IJAC推文”是其中一种方式，即通过互联网，以研究简介、实验视频等内容和形式，来帮助作者推广出版作品。 IJAC官方微信平台带您开启一场不一样的学术之旅，这里有最新会议资讯、研究成果、科普常识、美图美文，还有热情活泼而又不失严肃认真的阳光小编！ IJAC官方网站： 1) http://link.springer.com/journal/11633 2) http://www.ijac.net 新浪微博：IJAC-国际自动化与计算杂志 官方微信：IJAC Twitter: IJAC_Journal Linked in(领英): Int. J. of Automation and Computing
Introduction to MagnetochemistryDavid Young Cytoclonal Pharmaceutics Inc. Introduction Magnetochemistry is the study of the magnetic properties of materials. By magnetic properties we mean not only whether a material will make a good bar magnet, but whether it will be attracted or repelled by a magnet. This includes synthesis, analysis and understanding. This short description is meant to give a basic understanding before you delve into a more complex treatment. Magnetism arises from moving charges, such as an electric current in a coil of wire. In a material which does not have a current present, there are still magnetic interactions. Atoms are made of charged particles (protons and electrons) which are moving constantly. The processes which create magnetic fields in an atom are Nuclear spin. Some nuclei, such as a hydrogen atom, have a net spin which creates a magnetic field. Electron spin. An electron has two intrinsic spin states (similar to a top spinning) which we call up and down or alpha and beta. Electron orbital motion. There is a magnetic field due to the electron moving around the nucleus. Each of these magnetic fields interact with one another and with external magnetic fields. However, some of these interactions are strong and others are negligible. Measurement of interactions with nuclear spins are used to analyze compounds in nuclear magnetic resonance (NMR) and electron spin resonance (ESR) spectroscopy. In most other situations, interaction with nuclear spins is a very minor effect. Interactions between the intrinsic spin of one electron and the intrinsic spin of another electron are strongest for very heavy elements such as the actinides. This is called spin-spin coupling. For these elements this coupling can shift the electron orbital energy levels. The interaction between an electron's intrinsic spin and it's orbital motion is called spin-orbit coupling. Spin-orbit coupling has a significant effect on the energy levels of the orbitals in many inorganic compounds. Macroscopic effects, such as the attraction of a piece of iron to a bar magnet are primarily due to the number of unpaired electrons in the compound and their arrangement. The various possible cases are called magnetic states of matter. Magnetic States of Matter Diamagnetic - A diamagnetic compound has all of it's electron spins paired giving a net spin of zero. Diamagnetic compounds are weakly repelled by a magnet. Paramagnet - A paramagnetic compound will have some electrons with unpaired spins. Paramagnetic compounds are attracted by a magnet. Ferromagnet - In a ferromagnetic substance there are unpaired electron spins, which are held in alignment by a process known as ferromagnetic coupling. Ferromagnetic compounds, such as iron, are strongly attracted to magnets. Ferrimagnet - Ferrimagnetic compounds have unpaired electron spins, which are held in an pattern with some up and some down. This is known as ferrimagnetic coupling. In a ferrimagnetic compound, there are more spins held in one direction, so the compound is attracted to a magnet. Antiferromagnetic - When unpaired electrons are held in an alignment with an equal number of spins in each direction, the substance is strongly repelled by a magnet. This is referred to as an antiferromagnet. Superconductor - Superconductors are repelled by magnetic fields because the magnetic field is excluded from passing through them. This property of superconductors, called the Meissner effect, is used to test for the presence of a superconducting state. The underlying theory of how superconductivity arises is still a matter of much research and debate at the time of this writing. It does appear that the mechanism behind the magnetic properties of superconductors is significantly different from the other classes of compounds discussed here. For these reasons, superconductors will not be discussed further here. Interaction with an External Magnetic Field A magnetic field is given the symbol H which is a vector since the field has both a direction and a magnitude. For this discussion we will consider only interactions in one dimension making H and many other quantities we will define scalars. This gives us results for a homogeneous magnetic field and is a very good approximation for the way that most magnetic property measurements are performed. The magnitude of the magnetic field is usually given in units of gauss (G) or tesla (T) where 1 tesla = 10000 gauss. When a material is placed in a magnetic field, the magnetic field inside the material will be the sum of the external magnetic field and the magnetic field generated by the material itself. The magnetic field in a material is called the magnetic induction and given the symbol B. The formula for this is B = H + 4 Pi M where B = magnetic induction H = external magnetic field Pi = 3.14159 M = magnetization ( a property of the material ) For mathematical and experimental convenience this equation if often written as B = 1 + 4 Pi M = 1 + 4 Pi Xv - ------ H H where Xv = M/H = volume magnetic susceptibility The volume magnetic susceptibility is so named because B, H and M are defined per unit volume. However this results in Xv being unitless. It is convenient to use the magnetic susceptibility instead of the magnetization because the magnetic susceptibility is independent of the magnitude of the external magnetic field, H, for diamagnetic and paramagnetic materials. Many studies are done using Xg, magnetic susceptibility per gram, which is Xv divided by the density. This gives units of cm cubed per gram. Another useful form is Xm, molar magnetic susceptibility, which is Xg times the molecular weight. This gives units of cm cubed per mole. Another measure of magnetic interaction that is often used is an effective magnetic moment, mu, where mu = 2.828 ( Xm T ) 1/2 where mu = effective magnetic moment Xm = molar magnetic susceptibility T = temperature The numeric factor puts mu in units of Bohr magnetons (BM). Where one BM equals 9.274 x 10^-24 joules per tesla. The effective magnetic moment is a convenient measure of a material's magnetic properties because it is independent of temperature as well as external field strength for diamagnetic and paramagnetic materials. This said, we would now like to examine how the magnetization, magnetic susceptibility and effective magnetic moment depend on molecular structure. Diamagnetism Diamagnetism can be described by electrons forming circular currents, orbiting the nucleus, in the presence of a magnetic field. As such, a diamagnetic contribution can be calculated for any atom. However, the magnitude of the diamagnetic contribution is so much smaller than the magnitude of paramagnetic and other effects that it is usually ignored for any other type of materials. In this orbital model, the diamagnetic susceptibility from a given electron is proportional to the square of it's mean distance from the nucleus. Thus larger atoms are expected to have a larger diamagnetic interaction than smaller atoms. Often, the contributions for common atoms are tabulated along with corrections for multiple bonds. Thus a magnetic susceptibility can be predicted merely by adding together the contributions from all of the atoms and bonds in the molecule. For an example of these scheme, see Drago. For a more complete treatment, see Selwood. Paramagnetism The structural feature most prominent in determining paramagnetic behavior is the number of unpaired electrons in the compound. A spin only formula for the magnetic moment of a paramagnetic compound is mu = g { S ( S + 1 ) } 1/2 where mu = effective magnetic moment g = 2.0023 S = 1/2 for one unpaired electron 1 for two unpaired electrons 3/2 for three unpaired electrons, etc. This equation is sometimes written with g=2. This does not introduce a significant error since this simple spin only treatment is a decent approximation but is often not accurate even to two significant digits. An equation which takes into account both spin and orbital motion of the electrons is mu = { 4 S ( S + 1 ) + L ( L + 1 ) } 1/2 where mu = effective magnetic moment S = 1/2 for one unpaired electron, 1 for two, etc. L = total orbital angular momentum This equation is derived for atoms. It is applicable only to molecules with very high symmetry where the energies of the orbitals containing unpaired electrons are degenerate. A discussion of the calculation of L can be found in any introductory quantum mechanics text or in the chapter on quantum mechanics in many physical chemistry texts. If the splitting of orbital energy levels is large relative to k T ( k is the Boltzman constant ) then the applicable formula is mu = g { J ( J + 1 ) } 1/2 where g = 1 + S ( S + 1 ) - L ( L + 1 ) + J ( J + 1 ) --------------------------------------- 2 J ( J + 1 ) where J = S + L This formula is usually used for the lanthanide and actinide elements. For more accurate treatment of these elements, a diamagnetic contribution can be added to this as described by Selwood. If the splitting of orbital energy levels is comparable in magnitude to k T then the expression for magnetic properties must incorporate a Boltzman distribution. This is often the case with high spin transition metal complexes. The worst case, where this procedure is absolutely imperative, is the description of spin cross overs such as exhibited by some iron coordination compounds. Examples of this type of treatment are given in both the Drago and Selwood texts. For all of the cases of paramagnetic behavior the spin only formula is often used as a first rough approximation. If the only purpose for measuring the magnetic susceptibility is to determine the number of unpaired electrons this is often all that is done. Ferromagnetism, Antiferromagnetism and Ferrimagnetism The advantage of using effective magnetic moments for describing paramagnetic behavior is that it is a measure of the materials magnetic behavior which is not dependent upon either the temperature or the magnitude of the external field. It is not possible to set up such a convention for ferromagnetic, antiferromagnetic and ferrimagnetic materials. All three of these classes of materials can be considered a special case of paramagnetic behavior. The description of paramagnetic behavior is based on the assumption that every molecule behaves independently. The materials discussed here result from a situation in which the direction of the magnetic field produced by one molecule is affected by the direction of the magnetic field produced by an adjacent molecule, in other words their behavior is coupled. If this occurs in a way in which the magnetic fields all tend to align in the same direction, a ferromagnetic material results and the phenomenon is called ferromagnetic coupling. Antiferromagnetic coupling gives an equal number of magnetic fields in opposite directions. Ferrimagnetic coupling gives magnetic fields in two opposite orientations with more in one direction than in the other. With a few exceptions, the magnetic moments are not aligned through out the entire material. Typically regions, called domains, will form with different orientations. The existence of domains of coupled molecules gives rise to a number of types of behavior as described in the following paragraphs. The tendency of molecules to align themselves to one another enhances the magnetization of the material due to the presence of an external magnetic field. This is why ferromagnetic and ferrimagnetic materials can have magnetic susceptibilities several orders of magnitude large than paramagnetic materials. This also gives rise to the fact that the magnetic susceptibility of these materials is not independent of the magnitude of the external magnetic field as was the case for diamagnetic and paramagnetic materials. For a ferromagnetic material, the actual field acting on a given magnetic dipole ( unpaired electron ) is designated Ht and given by an equation similar to the equation for magnetic induction given above. Ht = H + Nw M where Ht = magnetic field felt by an electron H = external magnetic field Nw = molecular field constant, approximately 10000 M = magnetization This equation is used because it allows a mathematical treatment of a ferromagnetic substance similar to that used for paramagnetic substances. In this form the molecular field constant, Nw, is typically defined empirically in order to take the ferromagnetic coupling into account. To obtain the molecular field constant in a rigorous way would require a quantum mechanical calculation that takes into account the elements, their arrangement in the solid, kinetic energy of the electrons, coulombic attraction of electrons to the nucleus and repulsion with other electrons as well as spin interactions. What is most often done is a computer simulation using the Ising model, which is not truly rigorous but is based on quantum mechanics. This is a spin only quantum mechanical treatment assuming that the values of neighboring spins can be replaced by their average over time. For more explanation, see Morrish. Vibrational motion of the molecules, which increases with temperature, can disrupt the domain structure. Thus the magnetic properties of all three of these types of materials are strongest at low temperatures. At sufficiently high temperatures, no domain structure is able to form so all of these materials become paramagnetic at high temperatures. The temperature at which paramagnetic behavior is seen called the Curie temperature for ferromagnetic and ferrimagnetic materials and called the Neel temperature for antiferromagnetic materials. This is why a temperature independent effective magnetic moment cannot be defined for these materials. The alignment of the magnetic moments of the domains may give the material a net magnetic moment even in the absence of an external field. This gives a permanent magnet, such as a bar magnet. A material with no net moment prior to being exposed to an external magnetic field may retain a net moment after being exposed to an external magnetic field. This is how cassette and video tapes and computer disks store information. The magnitude of this memory effect can be quantified by plotting magnetization vs field strength as the external field intensity is varied from one polarity to the other and back again. A strong memory effect will be indicated by a wide hysteresis loop. Over a period of time magnetic domains tend to return to a random orientation. This makes the kinetics of this relaxation process another factor in the magnetic behavior of these materials. This is also responsible for the limited life span of magnetically stored music, video and computer data. Variation with Temperature The source of variation of magnetic properties with temperature is the disruption of the alignment of molecular magnetic moments due to the thermal motion of the atoms. As such, it should come as no surprise that diamagnetic behavior shows no variation with temperature. Paramagnetism As temperature increases, the magnetic susceptibility of a paramagnetic substance decreases. In some paramagnetic compounds the magnetic susceptibility is inversely proportional to the temperature. These are called normal paramagnets and have magnetic properties arising primarily due to the presence of permanent magnetic dipoles. This is referred to as the Curie Law and is expressed in mathematical form as X = C / T where C = Na g 2 b 2 ------- 4 k where X = magnetic susceptibility C = the Curie constant T = temperature Na = Avogadro's number g = the electron g factor b = the Bohr magneton k = the Boltzman constant In most paramagnetic compounds, an inverse relationship is observed, but the extrapolation to zero temperature does not obey the Curie Law. These compounds obey the Curie-Weiss Law which is X = C --------- T - theta where theta is a constant referred to as the Weiss constant. The Weiss constant can have a large range of values from -70 K to 3000 K. Most often it is positive. Ferromagnetism ferrimagnetism Ferromagnetic and ferrimagnetic compounds also show a decrease in magnetic susceptibility with increasing temperature. However, a plot of magnetic susceptibility vs. temperature shows a different line shape for these compounds than for paramagnetic compounds. This plot would have a positive curvature for paramagnetic compounds and a negative curvature for ferromagnetic compounds. A rough sketch of the shapes of these curves is as follows When a critical temperature ( called the Curie temperature ) is reached, the curvature of the plot changes. At the Curie temperature, ferromagnetic and ferrimagnetic compounds become paramagnetic. Curie temperatures range from 16 C for Gd to 1131 C for Co. For ferromagnetic substances a universal temperature curve can be constructed, meaning that all substances with the same total spin follow the same curve. This is done by plotting M(T)/M(0) vs T/Tc where M(T) is the magnetization at a given temperature, M(0) is the magnetization at absolute zero, T is the temperature and Tc is the Curie temperature. For more information, see Morrish. Antiferromagnetism Antiferromagnetic compounds show an increase in magnetic susceptibility until their critical temperature, called the Neel temperature, is reached. Above the Neel temperature these compounds also become paramagnetic. Neel temperature range from 1.66 K for MnCl 2 *4H 2 O to 953 K for alpha-Fe 2 O 3 . As with ferromagnetic substances, a universal temperature curve can be constructed that all substances with the same number of unpaired electrons follow. This is done by plotting X(T)/X(Tn) vs T/Tn where X(T) is the magnetic susceptibility at a given temperature, X(Tn) is the magnetic susceptibility at the Neel temperature, T is the temperature and Tn is the Neel temperature. For more information, see Morrish. Further Information Magnetochemistry is most often the realm of inorganic chemists so there should be a short discussion in any basic inorganic text. An old but good book on many aspects of magnetochemistry is P. W. Selwood Magnetochemistry Interscience (1956) Another good text is A. H. Morrish The Physical Principles of Magnetism John Wiley Sons (1965) There are chapters on magnetochemistry in R. S. Drago Physical Methods For Chemists Saunders College and Harcourt Brace Jovanovich (1992) L. Solymar, D. Walsh Lectures on the Electrical Properties of Materials Oxford (1993) A mathematical treatment can be found in D. L. Goodstein States of Matter Dover (1985) Solid state properties are covered in A. R. West Solid State Chemistry and its Applications John Wiley Sons (1992) A book describing more sophisticated simulation techniques is M. H. Krieger Constitutions of Matter University of Chicago Press (1996)
Analysis of the GaAs GaAsBi material system for heterojunction bipolar transistors 共6页。 摘要： This paper reports on the simulation of a double heterojunction bipolar transistor using the novel GaAs/GaAsBi material system. Published material parameters were used to simulate the device performance using an analytic drift-diffusion device model. DC and RF parameters were calculated as a function of emitter current density, base thickness and doping, and emitter stripe width and doping. Current gain is predicted to be between 102 and 103 at a current density of 105 A/cm2 and a bismuth concentration of 1.5%–3%. RF performance was calculated to range from10 to 30GHz for fT and from100 to 120 GHz for fmax at a current density of 105 A/cm2, base thickness of 100–200 nm, and emitter stripe width of 0.1–1 μm. 下载地址： http://www.pipipan.com/file/22096698
ENCODE experiments http://genome.ucsc.edu/ENCODE/protocols/dataStandards/ChIP_DNase_FAIRE_DNAme_v2_2010.pdf Requirements for a DNase-seq and FAIRE-seq experiments Following an analysis of deeply sequenced DNase-seq and FAIRE-seq datasets, we suggest the following requirements. Controls Deeply sequenced reference samples such as input DNA exhibit uneven coverage. For example, peaks in promoters have been observed in some input samples, perhaps as the result of endogenous nuclease activity, or sonication and solubility biases (Auerbach et al., 2009, Giresi, et al., 2007). These promoter peaks likely represent real open chromatin and therefore should not be excluded from analysis. Other reasons for uneven input signals are copy number variation, and under-representation of repetitive DNA sequence in the reference genome. However, the impact of uneven coverage in input chromatin is limited. Advances in computational methods to correct for such features are being incorporated into the analysis. For example, using reads that are not in peaks, the DNase/FAIRE-seq data itself can be used to identify regions that exhibit copy number variations in samples. In addition, the true signals from FAIRE and DNase exhibit a unique structure that differs greatly from the type of signal produced by uneven input coverage. While it is always preferable to have deeply sequenced matched input for each sample, for DNase and FAIRE experiments, input sequencing from every cell type is not required. Sequencing Depth. Since DNase and FAIRE data represent a continuum of the degree to which chromatin is “open”, achieving true saturation may not be practical, or even definable. However, a decision must be made regarding adequate level of coverage. We propose that the optimal depth of sequencing be guided by our ability to identify regions that were also identified by other methods such as tiled arrays (Giresi 2009, Giresi et al., 2007, Sabo et al., 2006, Crawford et al., 2006), qPCR (Boyle et al., Cell 2008), or Southern blots (Sabo et al., 2006). For DNase and FAIRE this is typically 20-50 million reads. In general, it is best to sequence replicates to a similar depth. We have found that similar sequence depth matters most for replicates on the lower end of the recommended read depth. Number of Replicates. By definition, at least two biological replicates are necessary to ensure that the experiment is reproducible. Experiments completed to date indicate that there will not be a significant gain in information beyond two biological replicates, when they are in reasonable agreement. For DNase, we recommend that at least 80% of the top 50,000 peaks in one replicate are detected in the top 100,000 peaks in the second replicate, and vice-versa. For FAIRE, we recommend that at least 50% of the top 50,000 peaks in one replicate are detected in the top 200,000 peaks in the second replicate, and vice-versa. Scoring. ChIP, DNase, FAIRE, DNAme standards July 2011 1 Similar to ChIP-seq, a variety of peak calling methods can be used to score peak intensity, including Fseq (Boyle et al., Bioinformatics 2008), Hotspot, and others. The following suggestions can be used to identify a statistical significant cutoff by one of the following methods. 1) Fitting the data to a gamma distribution to calculate p-values, and contiguous regions where p-values were below a 0.05 threshold can be considered significant. 2) Irreproducible discovery rate (IDR) analysis described in section IIb above. ================= ENCODE - Wikipedia, the free encyclopedia en.wikipedia.org/wiki/ENCODE The primary assays used in ENCODE are ChIP-seq, DNase I Hypersensitivity, RNA-seq, and assays of DNA methylation. ======================== Cell, tissue or DNA sample: Cell line or tissue used as the source of experimental material. cell Tier Description Lineage Tissue Karyotype Sex Documents Vendor ID Term ID Label HEEpiC 3 esophageal epithelial cells endoderm epithelium U Stam ScienCell 2700 HEEpiC http://main.genome-browser.bx.psu.edu/cgi-bin/hgEncodeVocab?ra=encode%2Fcv.raterm=%22HEEpiC%22
Materials science of chitin: Arthropods have adapted to every habitat on earth, adaptive material Building block: Organic matric, Inorganic nano-particles, Cuticle Homogenization, porous media, topological distribution X-ray wide angle diffraction, lobster Hierarchical modeling of stiffness starting from ab initio
Maximum Principle Stress Theory - According to this theory failure will occur when the maximum principal stress in a system reaches the value of the maximum stress at elastic limit in simple tension. This theory is approximately correct for cast iron and brittle materials generally. Source: http://www.roymech.co.uk/Useful_Tabl...cs/stress.html Von Mises Stress (Distortion Energy Theory) - This theory proposes that the total strain energy can be separated into two components: the volumetric (hydrostatic) strain energy and the shape (distortion or shear) strain energy. It is proposed that yield occurs when the distortion component exceeds that at the yield point for a simple tensile test. Source: http://en.wikipedia.org/wiki/Yield_(engineering ) More information on Von Mises Stress can be found here . General information on solid mechanics can be found here . The beauty of Von Mises stress is that in the real world "everything" fails by shear. That's why it has emerged as the favorite failure theory. Having said that, the world of material failure is highly stochastic - subject to statistical variation. So as good as the theory is, you still need significant factors of safety if you don't want your project to come crashing down. You find Von Mises stress from the principle stresses by using a big ol gnarly equation or three. It is always a smaller value than maximum principle stress (by definition) BUT it is aligned in the direction that has to support the maximum shear load. This can be very helpful in design.
统计学读物推荐 http://bona.ustc.edu.cn/yonglee/go.php/archiver/3/2009/1/5/ 一、统计学基础部分 1、《统计学》 David Freedman等著，魏宗舒，施锡铨等译 中国统计出版社 据说是统计思想讲得最好的一本书，读了部分章节，受益很多。整本书几乎没有公式，但是讲到了统计思想的精髓。 2、《Mind on statistics(英文版）》 机械工业出版社 只需要高中的数学水平，统计的扫盲书。有一句话影响很深： Mathematics as to statistics is something like hammer, nails, wood as to a house, it's just the material and tools but not the house itself。 3、《Mathematical Statistics and Data Analysis（英文版.第二版）》 机械工业出版社 看了就发现和国内的数理统计树有明显的不同。这本书理念很好，讲了很多新的东西，把很热门的Bootstrap方法和传统统计在一起讲了。Amazon上有书评。 4、《Business Statistics a decision making approach（影印版）》 中国统计出版社 在实务中很实用的东西，虽然往往为数理统计的老师所不屑 5、《Understanding Statistics in the behavioral science（影印版）》 中国统计出版社 和上面那本是一个系列的。老外的书都挺有意思的 6、《探索性数据分析》中国统计出版社 和第一本是一个系列的。大家好好看看陈希儒老先生做的序，可以说是对中国数理统计的一种反思。 二、回归部分 1、《应用线性回归》 中国统计出版社 还是著名的蓝皮书系列，有一定的深度，道理讲得挺透的。看看里面对于偏回归系数的说明，绝对是大开眼界啊！非常精彩的书 2、《Regression Analysis by example (3rd Ed影印版)》 这是偶第一本从头到底读完的原版统计书，太好看了。那张虚拟变量写得比小说都吸引人。没什么推导，甚至说“假定你有统计软件可以算出结果”，主要就是将分 析，怎么看图，怎么看结果。看完才觉得回归真得很好玩 3、《Logistics回归模型——方法与应用》 王济川 郭志刚 高等教育出版社 不多的国内的经典统计教材。两位都是社会学出身，不重推导重应用。每章都有详细的SAS和SPSS程序和输出的分析。两位估计洋墨水喝得比较多，中文写的书，但是明显老外写书的风格 三、多元 1、《应用多元分析（第二版）》 王学民 上海财经大学出版社 现在好像就是用的这本书，但是请注意，这本书的亮点不是推导，而是后面和SAS结合的部分，以及其中的一些想法（比如P99 n对假设检验的影响，绝对是统计的感觉，不是推推公式就能感觉到的）。这是一本国内很好的多元统计教材。 2、《Analyzing Multivariate Data（英文版）》 Lattin等著 机械工业出版社 这本书有很多直观的感觉和解释，非常有意思。对数学要求不高，证明也不够好，但的确是“统计书”，不是数学书。 3、《Applied Multivariate Statistical Analysis (5th Ed影印版)》 Johnson Wichem 著 中国统计出版社 个人认为是国内能买到的最好的多元统计书了。Amazon 上有人评论，评价很高的。不过据王学民老师说，这本书的证明还是有不太清楚，老外实务可以，证明实在不咋的，呵呵 四、时间序列 1、《商务和经济预测中的时间序列模型》 弗朗西斯著 Amazon 上五星推荐的书，讲了很多很新的东西也非常实用。我看完才知道，原来时间序列不知有AR(1) MA(1)啊，哈 2、《Forecasting and Time Series an applied approach(third edition)》 Bowerman Connell 著 本书的主讲Box-Jenkins(ARIMA)方法，附上了SAS和Minitab程序 五、抽样 1、《抽样技术》 科克伦著 张尧庭译 绝对是该领域最权威，最经典的书了。王学民老师说：这本书不是那么好懂的，数学系的人，就算看得懂每个公式，未必能懂它的意思（不是数学系的人，还是别看了吧）。 2、《Sampling: Design and Analysis（影印版)》 Lohr著 中国统计出版社 讲了很多很新的方法，无应答，非抽样误差，再抽样，都有讨论。也很不好懂，当时偶是和《Advance Microeconomic Theory》一起看的，后者被许多人认为是梦魇，但是和前者一比，好懂多了。主要还是理念上的差距。我们的统计思想和数据感觉有待加强啊 六、软件及其他 1、《SAS软件与应用统计分析》 王吉利 张尧庭 主编 好书啊！！！！ 2、《SAS V8基础教程》 汪嘉冈编 中国统计出版社 主要讲编程，没怎么讲统计。如果想加强SAS编程可以考虑。 3、《SPSS11统计分析教程（基础篇）（高级篇）》 张文彤 北京希望出版社 当初第一次看这本书，发现怎么几乎都看不懂，尤其是高级篇，现在终于搞清楚了：） 4、《金融市场的统计分析》 张尧庭著 广西师范大学出版社 张老师到底是大家，薄薄的一本书，言简意赅，把主要的金融模型都讲清楚了。看完会发现，分析金融单单数学模型还是纸上谈兵，必须加上统计模型和统计方法才能真正应用。本书用的多元统计（代数知识）比较深。
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2010, Proceedings of the 36th International MATADOR Conference , 6 , Pages 227-230 Modeling of hard turning: effect of tool geometry on cutting force Z.Y. Shi, Z.Q. Liu, C.M. Cao Abstract. Hard machining for manufacturing dies and molds offers various advantages, but the productivity is often limited, mainly by tool life. This study investigates the influence of cutting tool geometry on the cutting forces by utilizing finite element simulations (FEM). A set of cutting conditions in numerical FEM were conducted by using four different shaped cutting tools and axial force, radial force and tangential force were found. The results of this research help to explain the conclusion that for cylindrical control, the equation of the actual geometry of the S-shaped inserts involved in cutting is a sphere; that of C-shaped, D-shaped and Tshaped inserts involved in cutting is an ellipsoid with different lengths of short-half axis. Keywords : tool geometry, material flow stress, short-half-axial, cutting force FULL TEXT
这是bioconductor 2010 会议的培训教程相关的文件。内容几乎涵盖了主流生物信息操作的所有内容： http://www.bioconductor.org/help/course-materials/2010/BioC2010/ －－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－ Introduction to R Introduction to R First Steps with R Getting Started with Lattice Install command: source(http://bioconductor.org/course-packages/install-HTSTrack.R) Efficient R Programming Efficient R Programming Efficient R Programming Exercises Install command: source(http://bioconductor.org/course-packages/install-EfficientR.R) Transcript centric annotations and high-throughput sequencing Using the GenomicFeatures package Genomic Features and Sequences in Bioconductor Install command: source(http://bioconductor.org/course-packages/install-HTSTrack.R) Bioconductor tools for input and quality assessment of high-throughput sequence data Four exercises using Bioconductor Sequence Infrastructure Exercises: Reading and Manipulating Short Reads Exercises: An Introduction to Rsamtools Exercises: A Simple ChIP-Seq Workflow Exercises: A Simple RNA-seq Use Case Install command: source(http://bioconductor.org/course-packages/install-HTSTrack.R) Analyzing and Visualizing ChIP-seq Data Some Basic Analysis of ChIP-Seq Data Analysis of genome-scale count data in Bioconductor Robinson_McCarthy_BioC2010.zip Gene centric annotations Using Annotations in Bioconductor Install command: source(http://bioconductor.org/course-packages/install-HTSTrack.R) Analyzing flow cytometry data in Bioconductor Brief Intro to R for Flow Packages Users Analyzing flow cytometry data in Bioconductor Flow cytometry analysis Lab Flow cytometry analysis Lab Solutions Automated Gating and Metaclustering for Flow Cytometry Data Automated Gating and Metaclustering for Flow Cytometry Data (white paper)
Zhang electronegativity(27): How predicts raw material for InN nanocrystals? Changzheng et al. presented an effective synthetic protocol to produce high quality InN nanocrystals using indium iodide (InI 3 ) . There has been a question: Is it possible for high-quality InN to be synthesized from indium halides? The positive answer will be found in the present work using InI 3 . Concerning the four kinds of indium halides, InF 3 , InCl 3 , InBr 3 , and InI 3 ,.InI 3 has a stronger covalent ability than the other three. As is known, when two atoms form a chemical bond, the greater the difference between the electronegativity values for the two atoms, the more ionic the chemical bond between them (Zhang, 1982) According to Zhang electronegativitymodel which is based on the quantum mechanical electron configurations, n*(I z /R) ½ /r c 2 , both the effective principle quantum number, n*,and the covalent radius, r c, for halogens are increasedin the order: FClBrI .The polarizability of the anion will be ralated to its softness, that is, to the deformability of its electron cloud. Both increasing n* and r c will cause this cloud to be lessunder the influence of the nuclear charge of the anion and more easily influenced by the charge on thecation. Soconcerning the four kinds of indium halides, InI 3 is more covalent than the other three. Soit ispossible for high-quality InN to be synthesized from indium halides (InI 3 ) . Wu. Changzheng, Li. Tanwei, Lei. Lanyu, Hu. Shuangquan, Liu. Yi and Xie. Yi, New J. Chem., 2005, 29, 1610. Y. Zhang,1982, Inorg Chem., 1982, 21, 3886;3889. Y. Zhang,, in Introduction to Modern Inorganic Chemistry ( Eds: K. M. Mackay, R. A. Mackay, W. Henderson , ) 6thed., Nelson Thornes, United Kingdom,2002, pp 53-54).
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