Modelling the temperature, maturity and moisture content in a drying concrete block

In this paper we continue work from a previous Study Group in developing a model for the maturation of concrete. The model requires equations describing the temperature, moisture content and maturity (or amount of cement that has reacted with the water). Non-dimensionalisation is used to simplify the model and provide simple analytical solutions which are valid for early time maturation. A numerical scheme is also developed and simulations carried out for maturation over one day and then two months. For the longer simulation we also investigate the effect of building the block in a single pour or two stages

Progress in Hodgkin lymphoma: a population-based study on patients diagnosed in Sweden from 1973-2009.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.In recent decades, attention has focused on reducing long-term, treatment-related morbidity and mortality in Hodgkin lymphoma (HL). In the present study, we looked for trends in relative survival for all patients diagnosed with HL in Sweden from 1973-2009 (N = 6949; 3985 men and 2964 women; median age, 45 years) and followed up for death until the end of 2010. Patients were categorized into 6 age groups and 5 calendar periods (1973-1979, 1980-1986, 1987-1994, 1994-2000, and 2001-2009). Relative survival improved in all age groups, with the greatest improvement in patients 51-65 years of age (P < .0005). A plateau in relative survival was observed in patients below 65 years of age during the last calendar period, suggesting a reduced long-term, treatment-related mortality. The 10-year relative survival for patients diagnosed in 2000-2009 was 0.95, 0.96, 0.93, 0.80, and 0.44 for the age groups 0-18, 19-35, 36-50, 51-65, and 66-80, respectively. Therefore, despite progress, age at diagnosis remains an important prognostic factor (P < .0005). Advances in therapy for patients with limited and advanced-stage HL have contributed to an increasing cure rate. In addition, our findings support that long-term mortality of HL therapy has decreased. Elderly HL patients still do poorly, and targeted treatment options associated with fewer side effects will advance the clinical HL field.Swedish Cancer Society CAN 2009/1203 Stockholm County Council Karolinska Institutet SLL 20090201 Karolinska Institutet Foundations 2009Fobi007

The C-Type Lectin of the Aggrecan G3 Domain Activates Complement

Excessive complement activation contributes to joint diseases such as rheumatoid arthritis and osteoarthritis during which cartilage proteins are fragmented and released into the synovial fluid. Some of these proteins and fragments activate complement, which may sustain inflammation. The G3 domain of large cartilage proteoglycan aggrecan interacts with other extracellular matrix proteins, fibulins and tenascins, via its C-type lectin domain (CLD) and has important functions in matrix organization. Fragments containing G3 domain are released during normal aggrecan turnover, but increasingly so in disease. We now show that the aggrecan CLD part of the G3 domain activates the classical and to a lesser extent the alternative pathway of complement, via binding of C1q and C3, respectively. The complement control protein (CCP) domain adjacent to the CLD showed no effect on complement initiation. The binding of C1q to G3 depended on ionic interactions and was decreased in D2267N mutant G3. However, the observed complement activation was attenuated due to binding of complement inhibitor factor H to CLD and CCP domains. This was most apparent at the level of deposition of terminal complement components. Taken together our observations indicate aggrecan CLD as one factor involved in the sustained inflammation of the joint

Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance.

An adaptive framework for building intelligent measurement systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making intelligent decisions related to the presence of anomalies in the surveillance data with the help of statistical analysis, computational intelligent and machine learning. Computational intelligence can also be effectively utilised for identifying the main contributing features in detecting anomalous data points within the surveillance data. The experimental results have demonstrated that a reasonable performance is achieved in terms of inferential accuracy and data processing speed

Toward Human-Carnivore Coexistence: Understanding Tolerance for Tigers in Bangladesh

Fostering local community tolerance for endangered carnivores, such as tigers (Panthera tigris), is a core component of many conservation strategies. Identification of antecedents of tolerance will facilitate the development of effective tolerance-building conservation action and secure local community support for, and involvement in, conservation initiatives. We use a stated preference approach for measuring tolerance, based on the ‘Wildlife Stakeholder Acceptance Capacity’ concept, to explore villagers’ tolerance levels for tigers in the Bangladesh Sundarbans, an area where, at the time of the research, human-tiger conflict was severe. We apply structural equation modeling to test an a priori defined theoretical model of tolerance and identify the experiential and psychological basis of tolerance in this community. Our results indicate that beliefs about tigers and about the perceived current tiger population trend are predictors of tolerance for tigers. Positive beliefs about tigers and a belief that the tiger population is not currently increasing are both associated with greater stated tolerance for the species. Contrary to commonly-held notions, negative experiences with tigers do not directly affect tolerance levels; instead, their effect is mediated by villagers’ beliefs about tigers and risk perceptions concerning human-tiger conflict incidents. These findings highlight a need to explore and understand the socio-psychological factors that encourage tolerance towards endangered species. Our research also demonstrates the applicability of this approach to tolerance research to a wide range of socio-economic and cultural contexts and reveals its capacity to enhance carnivore conservation efforts worldwide

Pionic contribution to relativistic Fermi Liquid parameters

We calculate pionic contribution to the relativistic Fermi Liquid parameters (RFLPs) using Chiral Effective Lagrangian. The RFLPs so determined are then used to calculate chemical potential, exchange and nuclear symmetry energies due to $\pi$$N$ interaction. We also evaluate two loop ring diagrams involving $\sigma$, $\omega$ and $\pi$ meson exchanges and compare results with what one obtains from the relativistic Fermi Liquid theory (RFLT).Comment: 6 pages, 2 figures, Published in Canadian Journal of Physics, vol. 88, issue 8, pp. 585-59

Cellular mechanisms by which proinsulin C-peptide prevents insulin-induced neointima formation in human saphenous vein

AIMS/HYPOTHESIS: Endothelial cells (ECs) and smooth muscle cells (SMCs) play key roles in the development of intimal hyperplasia in saphenous vein (SV) bypass grafts. In diabetic patients, insulin administration controls hyperglycaemia but cardiovascular complications remain. Insulin is synthesised as a pro-peptide, from which C-peptide is cleaved and released into the circulation with insulin; exogenous insulin lacks C-peptide. Here we investigate modulation of human SV neointima formation and SV-EC and SV-SMC function by insulin and C-peptide. METHODS: Effects of insulin and C-peptide on neointima formation (organ cultures), EC and SMC proliferation (cell counting), EC migration (scratch wound), SMC migration (Boyden chamber) and signalling (immunoblotting) were examined. A real-time RT-PCR array identified insulin-responsive genes, and results were confirmed by real-time RT-PCR. Targeted gene silencing (siRNA) was used to assess functional relevance. RESULTS: Insulin (100 nmol/l) augmented SV neointimal thickening (70% increase, 14 days), SMC proliferation (55% increase, 7 days) and migration (150% increase, 6 h); effects were abrogated by 10 nmol/l C-peptide. C-peptide did not affect insulin-induced Akt or extracellular signal-regulated kinase signalling (15 min), but array data and gene silencing implicated sterol regulatory element binding transcription factor 1 (SREBF1). Insulin (1-100 nmol/l) did not modify EC proliferation or migration, whereas 10 nmol/l C-peptide stimulated EC proliferation by 40% (5 days). CONCLUSIONS/INTERPRETATION: Our data support a causative role for insulin in human SV neointima formation with a novel counter-regulatory effect of proinsulin C-peptide. Thus, C-peptide can limit the detrimental effects of insulin on SMC function. Co-supplementing insulin therapy with C-peptide could improve therapy in insulin-treated patients

Spectroscopic Studies of the Iron and Manganese Reconstituted Tyrosyl Radical in Bacillus Cereus Ribonucleotide Reductase R2 Protein

Ribonucleotide reductase (RNR) catalyzes the rate limiting step in DNA synthesis where ribonucleotides are reduced to the corresponding deoxyribonucleotides. Class Ib RNRs consist of two homodimeric subunits: R1E, which houses the active site; and R2F, which contains a metallo cofactor and a tyrosyl radical that initiates the ribonucleotide reduction reaction. We studied the R2F subunit of B. cereus reconstituted with iron or alternatively with manganese ions, then subsequently reacted with molecular oxygen to generate two tyrosyl-radicals. The two similar X-band EPR spectra did not change significantly over 4 to 50 K. From the 285 GHz EPR spectrum of the iron form, a g1-value of 2.0090 for the tyrosyl radical was extracted. This g1-value is similar to that observed in class Ia E. coli R2 and class Ib R2Fs with iron-oxygen cluster, suggesting the absence of hydrogen bond to the phenoxyl group. This was confirmed by resonance Raman spectroscopy, where the stretching vibration associated to the radical (C-O, ν7a = 1500 cm−1) was found to be insensitive to deuterium-oxide exchange. Additionally, the 18O-sensitive Fe-O-Fe symmetric stretching (483 cm−1) of the metallo-cofactor was also insensitive to deuterium-oxide exchange indicating no hydrogen bonding to the di-iron-oxygen cluster, and thus, different from mouse R2 with a hydrogen bonded cluster. The HF-EPR spectrum of the manganese reconstituted RNR R2F gave a g1-value of ∼2.0094. The tyrosyl radical microwave power saturation behavior of the iron-oxygen cluster form was as observed in class Ia R2, with diamagnetic di-ferric cluster ground state, while the properties of the manganese reconstituted form indicated a magnetic ground state of the manganese-cluster. The recent activity measurements (Crona et al., (2011) J Biol Chem 286: 33053–33060) indicates that both the manganese and iron reconstituted RNR R2F could be functional. The manganese form might be very important, as it has 8 times higher activity

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model