NMR studies of phase transition in ammonium hydrogen bischloroacetate, NH4H(CH2ClCOOO)2

Proton second moment (M2) and spin-lattice relaxation time (T1) of Ammonium Hydrogen Bischloroacetate (ABCA) have been measured in the range 77-350 K. A value of 6.5 G2 has been observed for the second moment at room temperature, which is typical of NH4+ reorientation and also a second moment transition in the range 170-145 K indicates the freezing of NH4+ motion. The NMR signal disappears dicontinuously at 128 K. Proton spin-lattice relaxation time (T1) Vs temperature, yielded only one sharp miniumum of 1.9 msec which is again typical of NH4+ reorientation. A slope change at 250 K is also observed, prbably due to CH2 motion. Further, the FID signal disappears at 128 K. Thus the Tc appears to be 128 K (of two reported values 120 K and 128 K). Activation energies have been calculated and the mechanism of the phase transition is discussed.

Effect of Load on Dry Sliding Wear of Aluminum-Silicon Alloys

Aluminum-silicon alloy pins were slid against steel disks under nominally dry condition at a speed of 0.6 m s-1. Each pin was slid at a constant load for 5 min, the load being increased in suitable steps from 2 to 65 N. The results show the wear to increase almost monotonically with load, to be sensitive to the presence of silicon in the alloy, and to be insensitive to actual silicon content. The monotonic nature of wear rate-load characteristic suggests that one dominant wear mechanism prevails over the load range studied. Morphological studies of the pin surface and the debris support this contention and point to delamination as being the dominant mode of wear.

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum

Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

Deeply superficial digital media engagement? The case of Twitter and Movember 2013

Using activity generated with Twitter during Movember 2013, we interrogate the natures of superficiality running through what can be defined as a highly successful public health engagement intervention. Indeed, Movember arguably has not just been successful in one year in terms of raising funds for the causes it is concerned with, it has done this year-on-year since 2004. We tracked the keyword 'movember' (without the hash symbol) using an in-house installation of YourTwapperkeeper hosted on a NECTAR server. Data collection ran from 01 October - 04 December 2013, covering the ramp-up and wind-down periods of the event. We collected a total of 1,313,426 tweets from 759,345 unique users.

Buckled nano rod - a two state system: quantum effects on its dynamics

We consider a suspended elastic rod under longitudinal compression. The compression can be used to adjust potential energy for transverse displacements from the harmonic to the double well regime. The two minima in potential energy curve describe two possible buckled states. Using transition state theory (TST) we have calculated the rate of conversion from one state to other. If the strain epsilon = 4 epsilon c the simple TST rate diverges. We suggest a method to correct this divergence for quantum calculations. We also find that zero point energy contributions can be quite large so that single mode calculations can lead to large errors in the rate.

From Selective-ID to Full-ID IBS without Random Oracles

Since its induction, the selective-identity (sID) model for identity-based cryptosystems and its relationship with various other notions of security has been extensively studied. As a result, it is a general consensus that the sID model is much weaker than the full-identity (ID) model. In this paper, we study the sID model for the particular case of identity-based signatures (IBS). The main focus is on the problem of constructing an ID-secure IBS given an sID-secure IBS without using random oracles-the so-called standard model-and with reasonable security degradation. We accomplish this by devising a generic construction which uses as black-box: i) a chameleon hash function and ii) a weakly-secure public-key signature. We argue that the resulting IBS is ID-secure but with a tightness gap of O(q(s)), where q(s) is the upper bound on the number of signature queries that the adversary is allowed to make. To the best of our knowledge, this is the first attempt at such a generic construction.

Efficient Dictionary for Salted Password Analysis

User authentication is essential for accessing computing resources, network resources, email accounts, online portals etc. To authenticate a user, system stores user credentials (user id and password pair) in system. It has been an interested field problem to discover user password from a system and similarly protecting them against any such possible attack. In this work we show that passwords are still vulnerable to hash chain based and efficient dictionary attacks. Human generated passwords use some identifiable patterns. We have analysed a sample of 19 million passwords, of different lengths, available online and studied the distribution of the symbols in the password strings. We show that the distribution of symbols in user passwords is affected by the native language of the user. From symbol distributions we can build smart and efficient dictionaries, which are smaller in size and their coverage of plausible passwords from Key-space is large. These smart dictionaries make dictionary based attacks practical.

Universal Hashing for Information-Theoretic Security

The information-theoretic approach to security entails harnessing the correlated randomness available in nature to establish security. It uses tools from information theory and coding and yields provable security, even against an adversary with unbounded computational power. However, the feasibility of this approach in practice depends on the development of efficiently implementable schemes. In this paper, we review a special class of practical schemes for information-theoretic security that are based on 2-universal hash families. Specific cases of secret key agreement and wiretap coding are considered, and general themes are identified. The scheme presented for wiretap coding is modular and can be implemented easily by including an extra preprocessing layer over the existing transmission codes.

Mollusks taken by Beam Trawl in the vicinity of Gray's Reef National Marine Sanctuary on the Continental Shelf off Georgia, Southeastern U.S.

Mollusks were sorted from samples of shell hash (obtained as bycatch during NOAA-sponsored studies of larval and juvenile fish distribution), and analyzed to gain qualitative insights on species composition, distribution and habitat affinities of the molluscan fauna on the continental shelf off Georgia. Samples came from beam trawls at 37 stations located in the immediate vicinity and offshore of the Gray’s Reef National Marine Sanctuary (GRNMS) at depths of 4.9 to 103 m. Two hundred sixty-three (263) taxa of mollusks (~58% as dead shells only) were collected, and nearly all (~99%) were identified to the species level. Ninety-seven of these taxa appeared in samples from one or more of the four stations established near the corners of the GRNMS. Samples were highly variable in terms of appearance, volume and species composition of mollusks, reflecting the extreme patchiness of benthic habitats within this region of the continental shelf. With very few exceptions, the mollusks were generally characteristic of either the Carolinian or Caribbean faunal provinces. The Georgia continental shelf, however, was outside the previously reported ranges for at least 16 of the species reported here. Most of these extralimital species were known previously from the East Coast of Florida, and represented northerly range extensions of 1-5° Latitude (110-560 km). One species represented a more significant range extension from the Bahamas and the southern Caribbean, and two represented southerly range extensions, known previously from only as close as off North Carolina. The high incidence of range extensions found in this study and the potential for discovery of additional species are discussed in the context of the diversity and patchiness of benthic habitats on the continental shelf of the region, and the sensitivity of species recruitment to variability in Gulf Stream patterns and global climate change. (PDF contains 52 pages)

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

A preliminary study on methods for retaining data quality problems in automatically generated test data

Data in an organisation often contains business secrets that organisations do not want to release. However, there are occasions when it is necessary for an organisation to release its data such as when outsourcing work or using the cloud for Data Quality (DQ) related tasks like data cleansing. Currently, there is no mechanism that allows organisations to release their data for DQ tasks while ensuring that it is suitably protected from releasing business related secrets. The aim of this paper is therefore to present our current progress on determining which methods are able to modify secret data and retain DQ problems. So far we have identified the ways in which data swapping and the SHA-2 hash function alterations methods can be used to preserve missing data, incorrectly formatted values, and domain violations DQ problems while minimising the risk of disclosing secrets. © (2012) by the AIS/ICIS Administrative Office All rights reserved.

分组密码的分析与设计

分组密码作为现代密码学的一个重要组成部分，是目前最重要和流行的一种数据加密技术，有着非常广泛的应用。此外，近年来分组密码或其组件还经常作为基础模块用于构造Hash函数，MAC算法等。因此对分组密码安全性的分析以及设计安全高效的分组密码算法，在理论研究及实际应用中都有着非常重要的意义。本文的研究内容主要包括两个方面：对现有常用分组密码的安全性分析，以及分组密码及其组件的设计。这两个方面是密不可分，相互融合的。通常都是利用算法存在的弱点或算法设计特点，提出新的密码分析算法。而在算法设计过程中，正是从密码分析获取经验，掌握设计算法的技巧和避免可能存在的缺陷。 本文首先对分组密码分析方法作了大量的调查和研究，在此基础上分析了一些国内外常用和有影响的分组密码，得到了一系列有价值的分析结果。并在密码分析工作的经验基础上，结合现有密码设计理论，在分组密码及其组件的设计方面做了比较深入的研究。本文的主要成果包括： (1) DES算法的分析。DES算法是迄今最重要的分组密码算法之一，目前在一些金融领域，DES和Triple-DES仍被广泛使用着。本文考察了DES算法针对Boomerang攻击和Rectangle攻击的安全性。通过利用DES算法各轮的最优差分路径及其概率，分别给出了这两种攻击方法对DES的攻击算法。 (2) Rijndael算法的分析。Rijndael算法是高级加密标准AES的原型。本文针对大分组Rijndael算法的各个不同版本，利用算法行移位和列混淆变换的一些密码特性，改进了原有的不可能差分攻击结果，极大的降低了攻击的数据和时间复杂度。同时还分别构造了一些新的更长轮的不可能差分路径，利用这些路径给出了一系列对大分组Rijndael算法的改进的不可能差分攻击，这些结果是目前已知的对该算法的最好攻击结果。 (3) SMS4算法的分析。SMS4算法是中国公布的用于无线局域网产品保护的算法。本文首先构造了SMS4算法的一类5轮循环差分特征，利用该特征分别给出了对16轮SMS4算法的矩阵攻击和对21轮SMS4算法的差分分析。随后考察了SMS4算法抵抗差分故障攻击的能力，基于字节故障模型，结合实验指出需要32次故障诱导来恢复全部密钥。后续的工作又进一步将结果改进为只需要进行一次故障诱导再结合2^{44}次密钥搜索即可恢复全部密钥。 (4) CLEFIA密码算法的分析。CLEFIA算法是索尼公司于2007年提出的用于产品版权保护和认证的分组密码算法。针对CLEFIA算法，本文构造了一条概率为1的5轮截断差分特征，再结合其扩散矩阵的密码特性构造了一条3轮线性逼近。随后利用这两条路径组成的8轮差分-线性区分器，给出了对10轮CLEFIA算法的有效的差分-线性攻击。 (5) 分组密码结构的设计及其应用。本文提出了两种新的分组密码结构，并指出了其与原有结构相比的优势，同时分别评估了这两种结构针对差分分析和线性分析等常用密码分析方法的安全性。基于这两个密码结构，结合部分密码组件的设计和测试工作，本文还完成了两个分组密码算法的概要设计，并简要评估了它们的实现效率及针对现有的几种主要密码分析方法的安全性。