Helical single-lamellar crystals thermotropically formed in a synthetic nonracemic chiral main-chain polyester

Phase structures and transformation mechanisms of nonracemic chiral biological and synthetic polymers are fundamentally important topics in understanding their macroscopic responses in different environments. It has been known for many years that helical structures and morphologies can exist in low-ordered chiral liquid crystalline (LC) phases. However, when the chiral liquid crystals form highly ordered smectic liquid crystal phases, the helical morphology is suppressed due to the crystallization process. A double-twisted morphology has been observed in many liquid crystalline biopolymers such as dinoflaggellate chromosomes (in Prorocentrum micans) in an in vivo arrangement. Helical crystals grown from solution have been reported in the case of Bombyx mori silk fibroin crystals having the beta modification. This study describes a synthetic nonracemic chiral main-chain LC polyester that is able to thermotropically form helical single lamellar crystals. Flat single lamellar crystals can also be observed under the same crystallization condition. Moreover, flat and helical lamellae can coexist in one single lamellar crystal, within which one form can smoothly transform to the other. Both of these crystals possess the same structure, although translational symmetry is broken in the helical crystals. The polymer chain folding direction in both flat and helical lamellar crystals is determined to be identical, and it is always along the long axis of the lamellae. This finding provides an opportunity to study the chirality effect on phase structure, morphology, and transformation in condensed states of chiral materials. [S0163-1829(99)01042-5].

A Single Mutation at the Sheet Switch Region Results in Conformational Changes Favoring lambda 6 Light-Chain Fibrillogenesis

Systemic amyloid light-chain (LC) amyloidosis is a disease process characterized by the pathological deposition of monoclonal LCs in tissue. All LC subtypes are capable of fibril formation although lambda chains, particularly those belonging to the lambda 6 type, are overrepresented. Here, we report the thermodynamic and in vitro fibrillogenic properties of several mutants of the lambda 6 protein 6aJL2 in which Pro7 and/or His8 was substituted by Ser or Pro. The H8P and H8S mutants were almost as stable as the wildtype protein and were poorly fibrillogenic. In contrast, the P7S mutation decreased the thermodynamic stability of 6aJL2 and greatly enhanced its capacity to form amyloid-like fibrils in vitro. The crystal structure of the P7S mutant showed that the substitution induced both local and long-distance effects, such as the rearrangement of the V(L) (variable region of the light chain)-V(L) interface. This mutant crystallized in two orthorhombic polymorphs, P2(1)2(1)2(1) and C222(1). In the latter, a monomer that was not arranged in the typical Bence-Jones dimer was observed for the first time. Crystal-packing analysis of the C222(1) lattice showed the establishment of intermolecular beta-beta interactions that involved the N-terminus and beta-strand B and that these could be relevant in the mechanism of LC fibril formation. Our results strongly suggest that Pro7 is a key residue in the conformation of the N-terminal sheet switch motif and, through long-distance interactions, is also critically involved in the contacts that stabilized the V(L) interface in lambda 6 LCs. (C) 2009 Elsevier Ltd. All rights reserved.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

A single-centre cohort of patients with systemic light chain AL-amyloidosis treated with conventional chemotherapy or with high-dose chemotherapy and autologous stem cell transplantation.

BACKGROUND High-dose chemotherapy (HDCT) with autologous stem cell transplantation (ASCT) has been reported to confer better prognosis in systemic light chain AL-amyloidosis as compared with conventional chemotherapy. However, only limited data are available so far on treatment and outcome of AL-amyloidosis patients in Switzerland. METHODS Within a single-centre cohort of patients with biopsy confirmed AL-amyloidosis diagnosed between January 1995 and December 2012, we aimed to investigate treatment effects in patients treated with conventional chemotherapy versus HDCT with ASCT. RESULTS We identified 50 patients with AL-amyloidosis treated with conventional chemotherapy and 13 patients who received HDCT with ASCT. Clinical characteristics differed between the groups for the age of the patients (59 years for patients with ASCT/HDCT vs 69 years; p= 0.0006) and the troponin-T value (0.015 μg/l vs 0.08 μg/l; p = 0.0279). Patients with ASCT showed a trend towards better overall survival, with median survival not yet reached compared with 53 months in patients on conventional chemotherapy (p = 0.0651). CONCLUSION Our results suggest that light chain AL-amyloidosis patients considered fit to undergo HDCT and ASCT may have a better outcome than patients treated exclusively with conventional chemotherapy regimens; however, the better performance status of patients receiving HDCT may have added to this treatment effect.

Three functional luciferase domains in a single polypeptide chain

We report a unique case of a gene containing three homologous and contiguous repeat sequences, each of which, after excision, cloning, and expression in Escherichia coli, is shown to code for a peptide catalyzing the same reaction as the native protein, Gonyaulax polyedra luciferase (Mr = 137). This enzyme, which catalyzes the light-emitting oxidation of a linear tetrapyrrole (dinoflagellate luciferin), exhibits no sequence similarities to other luciferases in databases. Sequence analysis also reveals an unusual evolutionary feature of this gene: synonymous substitutions are strongly constrained in the central regions of each of the repeated coding sequences.

Calibration of the length of a chain of single gold atoms

Using a scanning tunnelling microscope or mechanically controllable break junction it has been shown that it is possible to control the formation of a wire made of single gold atoms. In these experiments an interatomic distance between atoms in the chain of ∼3.6 Å was reported which is not consistent with recent theoretical calculations. Here, using precise calibration procedures for both techniques, we measure the length of the atomic chains. Based on the distance between the peaks observed in the chain length histogram we find the mean value of the interatomic distance before chain rupture to be 2.5±0.2 Å. This value agrees with the theoretical calculations for the bond length. The discrepancy with the previous experimental measurements was due to the presence of He gas, that was used to promote the thermal contact, and which affects the value of the work function that is commonly used to calibrate distances in scanning tunnelling microscopy and mechanically controllable break junctions at low temperatures.

Locked nucleic acid (LNA) single nucleotide polymorphism (SNP) genotype analysis and validation using real-time PCR

With an increased emphasis on genotyping of single nucleotide polymorphisms (SNPs) in disease association studies, the genotyping platform of choice is constantly evolving. In addition, the development of more specific SNP assays and appropriate genotype validation applications is becoming increasingly critical to elucidate ambiguous genotypes. In this study, we have used SNP specific Locked Nucleic Acid (LNA) hybridization probes on a real-time PCR platform to genotype an association cohort and propose three criteria to address ambiguous genotypes. Based on the kinetic properties of PCR amplification, the three criteria address PCR amplification efficiency, the net fluorescent difference between maximal and minimal fluorescent signals and the beginning of the exponential growth phase of the reaction. Initially observed SNP allelic discrimination curves were confirmed by DNA sequencing (n = 50) and application of our three genotype criteria corroborated both sequencing and observed real-time PCR results. In addition, the tested Caucasian association cohort was in Hardy-Weinberg equilibrium and observed allele frequencies were very similar to two independently tested Caucasian association cohorts for the same tested SNP. We present here a novel approach to effectively determine ambiguous genotypes generated from a real-time PCR platform. Application of our three novel criteria provides an easy to use semi-automated genotype confirmation protocol.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Strategic supply chain management factors influencing agribusiness innovation utilization

Purpose – The purpose of this paper is to examine empirically, an industry development paradox, using embryonic literature in the area of strategic supply chain management, together with innovation management literature. This study seeks to understand how, forming strategic supply chain relationships, and developing strategic supply chain capability, influences beneficial supply chain outcomes expected from utilizing industry-led innovation, in the form of electronic business solutions using the internet, in the Australian beef industry. Findings should add valuable insights to both academics and practitioners in the fields of supply chain innovation management and strategic supply chain management, and expand knowledge to current literature. Design/methodology/approach – This is a quantitative study comparing innovative and non-innovative supply chain operatives in the Australian beef industry, through factor analysis and structural equation modeling using PAWS Statistical V18 and AMOS V18 to analyze survey data from 412 respondents from the Australian beef supply chain. Findings – Key findings are that both innovative and non-innovative supply chain operators attribute supply chain synchronization as only a minor indicator of strategic supply chain capability, contrary to the literature; and they also indicate strategic supply chain capability has a minor influence in achieving beneficial outcomes from utilizing industry-led innovation. These results suggest a lack of coordination between supply chain operatives in the industry. They also suggest a lack of understanding of the benefits of developing a strategic supply chain management competence, particularly in relation to innovation agendas, and provides valuable insights as to why an industry paradox exists in terms of the level of investment in industry-led innovation, vs the level of corresponding benefit achieved. Research limitations/implications – Results are not generalized due to the single agribusiness industry studied and the single research method employed. However, this provides opportunity for further agribusiness studies in this area and also studies using alternate methods, such as qualitative, in-depth analysis of these factors and their relationships, which may confirm results or produce different results. Further, this study empirically extends existing theoretical contributions and insights into the roles of strategic supply chain management and innovation management in improving supply chain and ultimately industry performance while providing practical insights to supply chain practitioners in this and other similar agribusiness industries. Practical implications – These findings confirm results from a 2007 research (Ketchen et al., 2007) which suggests supply chain practice and teachings need to take a strategic direction in the twenty-first century. To date, competence in supply chain management has built up from functional and process orientations rather than from a strategic perspective. This study confirms that there is a need for more generalists that can integrate with various disciplines, particularly those who can understand and implement strategic supply chain management. Social implications – Possible social implications accrue through the development of responsible government policy in terms of industry supply chains. Strategic supply chain management and supply chain innovation management have impacts to the social fabric of nations through the sustainability of their industries, especially agribusiness industries which deal with food safety and security. If supply chains are now the competitive weapon of nations then funding innovation and managing their supply chain competitiveness in global markets requires a strategic approach from everyone, not just the industry participants. Originality/value – This is original empirical research, seeking to add value to embryonic and important developing literature concerned with adopting a strategic approach to supply chain management. It also seeks to add to existing literature in the area of innovation management, particularly through greater understanding of the implications of nations developing industry-wide, industry-led innovation agendas, and their ramifications to industry supply chains.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Growth and characterization of pure and doped single crystals of $CuGeO_{3}$

Good quality single crystals of copper metagermanite, CuGeO3, are grown by flux technique. Growth is carried out at relatively low temperatures by using Bi2O3 along with CuO in an optimal flux ratio. Besides rendering the procedure simple, lower growth temperature reduces growth defect concentration. Single crystals of Cu1 - xCoxGeO3 and CuGe1 - yGayO3 are grown by the same method for different values of x and y to investigate the influence of in-chain and off-chain doping on spin-Peierls (SP) transition. Change in color, morphology and surface features as a result of doping are briefly discussed. Spin-Peierls transition of these crystals is studied by susceptibility measurements on a commercial SQUID magnetometer. Cationic substitution resulted in reduction of spin-Peierls transition temperature (T-SP) of CuGeO3. Substitution of magnetic impurity cobalt in-chain site caused more pronounced effects such as suppression of SP phase.

Influence of cobalt doping on superconducting transition in as-grown YBCO single crystals

The role of a charge buffer layer in the superconductivity of high-T-c materials is best studied by cationic substitutions. In this work, the chain copper in YBCO single crystals is substituted by Co3+ ion and consequent effect on superconducting transition temperature (T-c) studied. The T-c is measured using non-resonant Microwave Absorption technique, which is a highly sensitive and contactless method. It is seen that T-c of as-grown crystals is considerably enhanced by cobalt doping in low concentration regime. In contrast, higher T-c is achieved in undoped crystals only after extended oxygen anneal. When dopant concentration increases beyond an optimal value, T-c decreases and the system does not show superconductivity when cobalt content is high (x > 0.5 in YBa2Cu3-xCOxO7+/-delta). This behaviour consequent to cobalt substitution is discussed with reference to the apical oxygen model. Optimal cobalt doping can be thought of as an alternative to extended oxygen anneal in as-grown crystals of YBCO.

Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

Self-assembly of three new coordination complexes: Formation of 2-D square grid, 1-D chain and tape structures

Three distinct coordination complexes, viz., [Co(imi)(2)(tmb)(2)] (1) [where imi = imidazole], {[Ni(tmb)(2)(H2O)(3)]center dot 2H(2)O}(n) (2) and [Cu-2(mu-tmb)(4)(CH3OH)(2)] (3), have been synthesized hydrothermally by the reactions of metal acetates,2,4,6-trimethylbenzoic acid (Htmb) and with or without appropriate amine. The Ni analogue of 1 and the Co analogue of 2 have also been synthesized. X-ray single-crystal diffraction suggests that complex 1 represents discrete mononuclear species and complex 2 represents a 1D chain coordination polymer in which the Ni(H) ions are connected by the bridging water molecules. Complex 3 represents a neutral dinuclear complex. In 1, the central metal ions are associated by the carboxylate moiety and imidazole ligands, whereas the central metal atom is coordinated to the carboxylate moiety and the respective solvent molecules in 2 and 3. In 3, the four 2,4,6-trimethylbenzoate moieties act as a bridge connecting two copper (11) ions and the 0 atoms of methanol coord geometry, with the methanol molecule at the apical position. In all the three structures the central metal atom sits on a crystallographic inversion centre. In all the cases, the coordination entities are further organized via hydrogen bonding interactions to generate multifarious supramolecular networks. Complexes 1, 2 and 3 have also been characterized by spectroscopic (UV/Vis and IR) and thermal analysis (TGA). In addition, the complexes were found to exhibit antimicrobial activity. The magnetic susceptibility measurements, measured from 8 to 300 K, revealed antiferromagnetic interactions between the Co(II) ions in compound 1 and the Ni(II) ions in la, respectively.