Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Diabetes on the Labour Force Participation, Savings and Retirement Income of Workers Aged 45-64 Years in Australia

Background Diabetes is a debilitating and costly condition. The costs of reduced labour force participation due to diabetes can have severe economic impacts on individuals by reducing their living standards during working and retirement years. Methods A purpose-built microsimulation model of Australians aged 45-64 years in 2010, Health&WealthMOD2030, was used to estimate the lost savings at age 65 due to premature exit from the labour force because of diabetes. Regression models were used to examine the differences between the projected savings and retirement incomes of people at age 65 for those currently working full or part time with no chronic health condition, full or part time with diabetes, and people not in the labour force due to diabetes. Results All Australians aged 45-65 years who are employed full time in 2010 will have accumulated some savings at age 65; whereas only 90.5% of those who are out of the labour force due to diabetes will have done so. By the time they reach age 65, those who retire from the labour force early due to diabetes have a median projected savings of less than $35,000. This is far lower than the median value of total savings for those who remained in the labour force full time with no chronic condition, projected to have $638,000 at age 65. Conclusions Not only does premature retirement due to diabetes limit the immediate income available to individuals with this condition, but it also reduces their long-term financial capacity by reducing their accumulated savings and the income these savings could generate in retirement. Policies designed to support the labour force participation of those with diabetes, or interventions to prevent the onset of the disease itself, should be a priority to preserve living standards comparable with others who do not suffer from this condition.
DF directed multipath equalization

This paper addresses the problem of equalizing a (narrow-band) multipath channel using data from an array of sensors. By exploiting the structure inherent in the data, it is shown that the number of multipath rays that can be uniquely identified is on the order of the number of data samples collected, rather than the number of sensors as in most direction finding applications. Two equalization algorithms are presented, both based on a frequency domain representation of the data and the availability of array calibration data. The performance of these algorithms is compared with that of several other recently developed equalization techniques, and is shown to be superior provided the calibration data is reasonably accurate. <<ETX>>
Regulation of macrophage function in tumors: the multifaceted role of NF- B

1Centre for Cancer and Inflammation, Institute of Cancer, Barts and the London School of Medicine and Dentistry, London, United Kingdom; 2Laboratory of Human Innate Immunity, Singapore Immunology Network, Biomedical Sciences Institutes, Agency for Science, Technology & Research, Singapore; 3Istituto Clinico Humanitas, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, and DiSCAFF, University of Piemonte Orientale A Avogadro, Novara, Italy; and 4Academic Unit of Pathology, University of Sheffield Medical School, Sheffield, United Kingdom
‘Fuller’ or ‘extended’ working lives? Critical perspectives on changing transitions from work to retirement

ABSTRACT Research on older workers and retirement has yet to adjust fully to an environment influenced by a combination of demographic change, technological developments and economic recession. A key dimension to the changing relationship between ageing and work is the tension between policies to extend working life and the increasingly fragmented nature of late working life, with the emergence of varied transitions, including: bridge employment, second/third careers, part-time working, early retirement and other variations. These developments indicate both the challenge of conceptualising new forms of work-ending, and – in policy terms – the extent to which these can successfully accommodate longer working lives. The paper provides a critical perspective to the policy of extending working life and the narrative which underpins this approach. The paper argues that retirement has become a ‘contested’ institution in the 21st century, fragmented across different pathways and transitions affecting people in their fifties and sixties. The paper argues the case for improving work quality and security as a precondition for supporting policies for encouraging working in later life. An essential requirement for this will include linking debates on extending working life with technological developments and changes affecting the workplace, creating differentiated paths to retirement and labour force exit, enhancing the provision of training and continuing education, and re-thinking the idea of the ‘older worker’.
Compressive Sensing Based Fingerprinter Positioning with MCA-based Pre-processing

The sparse nature of location finding in the spatial domain makes it possible to exploit the compressive sensing (CS) theory for wireless location. CS-based location algorithm can largely reduce the number of measurements while achieve a high level of localization accuracy, which makes the CS-based solution very attractive for indoor positioning. In this paper, a novel CS-based fingerprinting location algorithm with minor component analysis (MCA) is proposed by us. MCA theory is firstly introduced into CS to solve the coherence of Received Signal Strength (RSS) measurements in wireless location scenario. MCA-based pre-processing can better satisfy the restricted isometry property (RIP) condition by finding the minor components of RSS measurements. Analytical studies and simulations are provided to indicate that the proposed novel method using MAC significantly outperforms that with orthogonalization pre-processing, and also has lower complexity.
Agile modelling of cellular signalling a simple illustration of the rule-based approach

The purpose of this note is to demonstrate the flexibility of a structured and rulebased approach to modelling cellular signalling. Although the approach is especially useful when the biological system of interest is highly combinatorial, we will use an example that the intuition can grasp comfortably. Specifically we shall: start with a basic motive of reversible covalent modification [1]; obtain a rule-based version of the Huang-Ferell model of a protein activation cascade [2]; and finally, rewire our cascade to illustrate how easy it is to do so. Simple as this cascade is, it already generates about six hundred different species, and would be tedious to specify by traditional reaction-based methods, and even more so to modify. In fact one of the major advantages of the approach we advocate is to avoid the combinatorial explosion of traditional approaches. A more complex example which illustrates this point in spectacular fashion can be found in Ref. [3]. There one also considers the causal analysis of models, a topic which the present note will not discuss. Other approaches using process-algebraic languages [4–8] could do well in principle but for the fact that they require the enumeration of all possible internal states of a process. Those based on a binary model of communication need to encode more in the processes internal states, which makes the problem more acute. Rule-based languages such as Kappa [9] -which we use here, or the BioNetGen language [10] describe biological interactions in a more natural and intuitive way and as such are also at a clear practical advantage.
Using multiple interdependency to separate functional from phylogenetic correlations in protein alignments

MOTIVATION Multiple sequence alignments of homologous proteins are useful for inferring their phylogenetic history and to reveal functionally important regions in the proteins. Functional constraints may lead to co-variation of two or more amino acids in the sequence, such that a substitution at one site is accompanied by compensatory substitutions at another site. It is not sufficient to find the statistical correlations between sites in the alignment because these may be the result of several undetermined causes. In particular, phylogenetic clustering will lead to many strong correlations. RESULTS A procedure is developed to detect statistical correlations stemming from functional interaction by removing the strong phylogenetic signal that leads to the correlations of each site with many others in the sequence. Our method relies upon the accuracy of the alignment but it does not require any assumptions about the phylogeny or the substitution process. The effectiveness of the method was verified using computer simulations and then applied to predict functional interactions between amino acids in the Pfam database of alignments.
Characterization of γδ T Cells from Zebrafish Provides Insights into Their Important Role in Adaptive Humoral Immunity

γδ T cells represent an evolutionarily primitive T cell subset characterized by distinct T cell receptors (TCRs) and innate and adaptive immune functions. However, the presence of this T cell subset in ancient vertebrates remains unclear. In this study, γδ T cells from a zebrafish (Danio rerio) model were subjected to molecular and cellular characterizations. The constant regions of zebrafish TCR-γ (DrTRGC) and δ (DrTRDC) were initially identified. Zebrafish γδ T cells accounted for 7.7–20.5% of the total lymphocytes in spleen, head kidney, peripheral blood, skin, gill, and intestine tissues. They possess typical morphological features of lymphocytes with a surface phenotype of γ+δ+CD4−CD8+. Zebrafish γδ T cells functionally showed a potent phagocytic ability to both soluble and particulate antigens. They can also act as an antigen-presenting cell to initiate antigen (KLH)-specific CD4+ TKLH cell activation and to induce B cell proliferation and IgM production. Particularly, zebrafish γδ T cells also play a critical role in antigen-specific IgZ production in intestinal mucus. These findings demonstrated that γδ T cells had been originated as early as teleost fish, which providing valuable insights into the evolutionary history of T cell subset. It is anticipated that this study would be used as a guide to develop a zebrafish model for the cross-species investigation of γδ T cell biology.
Reissner-Nordstrom black hole in noncommutative spaces

We investigate the behaviour of a non-commutative radiating Reissner-Nordstrom(Re-No)black hole. We find some interesting results : a). the existence of a minimal non-zero mass to which the black hole can shrink. b). a finite maximum temperature that the black hole can reach before cooling down to absolute zero. c) compared to the neutral black holes the effect of charge is to increase the minimal non-zero mass and lower the maximum temperature. d) the absence of any curvature singularity. We also derive some essential thermodynamic quantities from which we study the stability of the black hole. Finally we find an upper bound for the non-commutativity parameter $\theta$.
Suzaku Observations of M 82 X-1 : Detection of a Curved Hard X-Ray Spectrum

A report is presented on Suzaku observations of the ultra-luminous X-ray source X-1 in the starburst galaxy M 82, made three times in 2005 October for an exposure of � 30 ks each. The XIS signals from a region of radius 3 0 around the nucleus defined a 2–10 keV flux of 2.1 � 10 � 11 erg s � 1 cm � 2 attributable to point sources. The 3.2–10 keV spectrum was slightly more convex than a power-law with a photon index of 1.7. In all observations, the HXD also detected signals from M 82 up to � 20 keV, at a 12–20 keV flux of 4.4 � 10 � 12 erg s � 1 cm � 2 . The HXD spectrum was steeper than that of the XIS. The XIS and HXD spectra can be jointly reproduced by a cutoff power-law model, or similar curved models. Of the detected wide-band signals, 1= 3t o 2=3 are attributable to X-1, while the remainder to other discrete sources in M 82. Regardless of the modeling of these contaminants, the spectrum attributable to X-1 is more curved than a power-law, with a bolometric luminosity of (1.5–3) � 10 40 erg s � 1 . These results are interpreted as Comptonized emission from a black hole of 100–200 solar masses, radiating roughly at the Eddington luminosity.
Rescue of the reeler phenotype in the dentate gyrus by wild‐type coculture is mediated by lipoprotein receptors for reelin and disabled 1

Reelin is a positional signal for the lamination of the dentate gyrus. In the reeler mutant lacking Reelin, granule cells are scattered all over the dentate gyrus. We have recently shown that the reeler phenotype of the dentate gyrus can be rescued in vitro by coculturing reeler hippocampal slices with slices from wild‐type hippocampus. Here we studied whether Reelin from other brain regions can similarly induce this rescue effect and whether it is mediated via the Reelin receptors apolipoprotein E receptor 2 (ApoER2) and very‐low‐density lipoprotein receptor (VLDLR). We found that coculturing reeler hippocampal slices with slices from wild‐type olfactory bulb, cerebellum, and neocortex rescued the reeler phenotype as seen before with hippocampal slices, provided that the Reelin‐synthesizing cells of these regions were placed near the marginal zone of the reeler hippocampal slice. However, coculturing wild‐type hippocampal slices with hippocampal slices from mutants deficient in ApoER2 and VLDLR did not rescue the reeler‐like phenotype in these cultures. Similarly, no rescue of the reeler‐like phenotype was observed in slices from mutants lacking Disabled 1 (Dab1), an adapter protein downstream of Reelin receptors. Conversely, reeler hippocampal slices were rescued by coculturing them with slices from Dab1−/− mutants or ApoER2−/−/VLDLR−/− mice. These findings show that Reelin from other brain regions can substitute for the loss of hippocampal Reelin and that rescue of the reeler phenotype observed in our coculture studies is mediated via lipoprotein receptors for Reelin and Dab1. J. Comp. Neurol. 495:1–9, 2006. © 2006 Wiley‐Liss, Inc.
Comparison analysis of data mining methodology and student performance improvement influence factors in small data set

Based on Programme for International Student Assessment survey, Indonesia student performance was on the lower position compared to other participated countries. Nevertheless, the actual reason of someone's performance in studying is hard to predict. Therefore, we need to limit the research's scope for finding more specific influencing factors. In this study, a group of students who have the same learning method, teacher, course, and also facility in a learning environment is observed to find significant influencing factors. We develop a questionnaire with various factors that are related to students' characteristic. It is administered to students of Junior High School Muhammadiyah 2 Depok Sleman in the same year. Consequently, data gathered is in small size. In order to yield maximum accuracy in small dataset, SMOTE is used to generate new data synthetically hence instance number is increasing. Besides several approaches were analyzed by using combination of preprocessing and variation feature selections. The result of this research shows that attribute subset selection by Classifier Subset Evaluator (CSE) yields the best result based on Naive Bayes accuracy and variance. Various significant factors influencing studying performance of tested students were also found including blood type, who student live with, father's education, mother's education, kind of activity done in spare time and favorite course.
NNLO corrections to event shapes in e+e− annihilation

We compute the next-to-next-to-leading order (NNLO) QCD corrections to the six most important event shape variables related to three-particle final states in electron- positron annihilation. The corrections are sizeable for all variables, however their magni- tude is substantially different for different observables. We observe that the NNLO correc- tions yield a considerably better agreement between theory and experimental data both in shape and normalisation of the event shape distributions. The renormalisation scale de- pendence of the theoretical prediction is substantially reduced compared to the previously existing NLO results. Our results will allow a precise determination of the strong coupling constant from event shape data collected at LEP.
Passport options with stochastic volatility

A passport option is a call option on the profits of a trading account. In this article, the robustness of passport option pricing is investigated by incorporating stochastic volatility. The key feature of a passport option is the holders' optimal strategy. It is known that in the case of exponential Brownian motion the strategy is to be long if the trading account is below zero and short if the account is above zero. Here this result is extended to models with stochastic volatility where the volatility is defined via an autonomous SDE. It is shown that if the Brownian motions driving the underlying asset and the volatility are independent then the form of the optimal strategy remains unchanged. This means that the strategy is robust to misspecification of the underlying model. A second aim of this article is to investigate some of the biases which become apparent in a stochastic volatility regime. Using an analytic approximation, comparisons are obtained for passport option prices using the exponential Brownian motion model and some well-known stochastic volatility models. This is illustrated with numerical examples. One conclusion is that if volatility and price are uncorrelated, then prices are sometimes lower in a model with stochastic volatility than in a model with constant volatility.
Network coding capacity: A functional dependence bound

Explicit characterization and computation of the multi-source network coding capacity region (or even bounds) is long standing open problem. In fact, finding the capacity region requires determination of the set of all entropic vectors Γ*, which is known to be an extremely hard problem. On the other hand, calculating the explicitly known linear programming bound is very hard in practice due to an exponential growth in complexity as a function of network size. We give a new, easily computable outer bound, based on characterization of all functional dependencies in networks. We also show that the proposed bound is tighter than some known bounds.
Mutual Information Minimization for Under-Determined Blind Source Separation

An important step of sparse representation technique for under-determined BSS (Blind Source Separation) is the estimation of the mixing matrix. In this paper, a new method to estimate the mixing matrix is proposed. The objective is to find the mixing matrix to minimize the mutual information of the estimated sources. An algorithm for the learning of the mixing matrix is proposed by the natural gradient. Simulation results of speech separation demonstrate the effectiveness o f our method.
Caracterización de la dimensión ambiental incluida en los informes de sostenibilidad de las empresas colombianas pertenecientes al CECODES. (Characterization of the Environmental Dimension included in the sustainability reports of Colombian companies belonging to CECODES).

En las dos últimas décadas, los Informes de Sostenibilidad o Responsabilidad Social Empresarial - RSE se han configurado como una herramienta importante para la gestión empresarial. Esta investigación desarrolla una caracterización de la dimensión ambiental incluida en los informes de sostenibilidad de las empresas pertenecientes al Consejo Empresarial Colombiano para el Desarrollo sostenible - CECODES, mediante la identificación de la estructura planteada en la Guía G4 del Global Reporting Initiative - GRI y la comparación de ésta con la propuesta de cada uno de estos reportes, con el fin de detectar diferencias y determinar tendencias y características relevantes. La metodología utilizada en la investigación es de enfoque cualitativo con un alcance descriptivo. Entre los resultados más importantes encontrados en la investigación se tiene que las empresas de la muestra no aplican a cabalidad la dimensión ambiental incluida en la Guía G4 y no se observaron tendencias semejantes entre ellas.
A Nuclear Calcium-Sensing Pathway Is Critical for Gene Regulation and Salt Stress Tolerance in Arabidopsis

Salt stress is an important environmental factor that significantly limits crop productivity worldwide. Studies on responses of plants to salt stress in recent years have identified novel signaling pathways and have been at the forefront of plant stress biology and plant biology in general. Thus far, research on salt stress in plants has been focused on cytoplasmic signaling pathways. In this study, we discovered a nuclear calcium-sensing and signaling pathway that is critical for salt stress tolerance in the reference plant Arabidopsis. Through a forward genetic screen, we found a nuclear-localized calcium-binding protein, RSA1 (SHORT ROOT IN SALT MEDIUM 1), which is required for salt tolerance, and identified its interacting partner, RITF1, a bHLH transcription factor. We show that RSA1 and RITF1 regulate the transcription of several genes involved in the detoxification of reactive oxygen species generated by salt stress and that they also regulate the SOS1 gene that encodes a plasma membrane Na+/H+ antiporter essential for salt tolerance. Together, our results suggest the existence of a novel nuclear calcium-sensing and -signaling pathway that is important for gene regulation and salt stress tolerance.
Effective connectivity of the multiplication network: A functional MRI and multivariate granger causality mapping study

Developmental neuropsychology and functional neuroimaging evidence indicates that simple and complex mental calculation is subserved by a fronto‐parietal network. However, the effective connectivity (connection direction and strength) among regions within the fronto‐parietal network is still unexplored. Combining event‐related fMRI and multivariate Granger Causality Mapping (GCM), we administered a multiplication verification task to healthy participants asking them to solve single and double‐digit multiplications. The goals of our study were first, to identify the effective connectivity of the multiplication network, and second, to compare the effective connectivity patterns between a low and a high arithmetical competence (AC) group. The manipulation of multiplication difficulty revealed a fronto‐parietal network encompassing bilateral intraparietal sulcus (IPS), left pre‐supplementary motor area (PreSMA), left precentral gyrus (PreCG), and right dorsolateral prefrontal cortex (DLPFC). The network was driven by an intraparietal IPS‐IPS circuit hosting a representation of numerical quantity intertwined with a fronto‐parietal DLPFC‐IPS circuit engaged in temporary storage and updating of arithmetic operations. Both circuits received additional inputs from the PreCG and PreSMA playing more of a supportive role in mental calculation. The high AC group compared to the low AC group displayed a greater activation in the right IPS and based its calculation more on a feedback driven intraparietal IPS‐IPS circuit, whereas the low competence group more on a feedback driven fronto‐parietal DLPFC‐IPS circuit. This study provides first evidence that multivariate GCM is a sensitive approach to investigate effective connectivity of mental processes involved in mental calculation and to compare group level performances for different populations. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.