Tradition and Innovation in Classical Sociology: Tenth Anniversary Report of JCS

Perhaps the very idea of ‘classical sociology’ is a contradiction in terms; sociology was originally that social science peculiarly concerned with the study of the processes of modernization and the condition of modernity, that is, with the critical examination of ‘post-traditional’ developments and hence ‘post-classical’ forms of social organization. Its concerns have broadened subsequently, but the focus of sociology remains on the exploration of the nature and development of social structure and social action in the post-traditional world. In the nineteenth century, sociologists invented new concepts and experimented with new methods to study the emergence of unprecedented social phenomena and the rise of a type of society that was variously called ‘modern society’, ‘industrial society’, and ‘capitalist society’. In the twentieth century, there was a further elaboration of key sociological concepts, and it became increasingly popular to proclaim the rise of yet another form of society, described as ‘post-industrial society’, ‘late modern society’, ‘post-modern society’, or ‘network society’. In the current century, the idea of globalization has swept everything before it, leading to the notion that ‘society’ has now been replaced by flows and networks of people, objects, and ideas. With the transition from traditional to modern societies, the integrative power of Gemeinschaft began to compete with the systemic power of Gesellschaft; with the transition from modern to late modern societies, the local horizons of our Lebenswelt appear to be increasingly shaped by the deterritorialized networks of the Weltgesellschaft. If we are ‘post-traditional’, surely we are also ‘post-classical’. It is hardly surprising, therefore, that many contemporary sociologists have some difficulty accepting the very idea of classical sociology

Evaluating osteological ageing from digital data

YesAge at death estimation of human skeletal remains is one of the key issues in constructing a biological profile both in forensic and archaeological contexts. The traditional adult osteological methods evaluate macroscopically the morphological changes that occur with increasing age of specific skeletal indicators, such as the cranial sutures, the pubic bone, the auricular surface of the ilium and the sternal end of the ribs. Technologies such as CT and laser scanning are becoming more widely used in anthropology, and several new methods have been developed. This review focuses on how the osteological age-related changes have been evaluated in digital data. Firstly, the 3D virtual copies of the bones have been used to mimic the appearance of the dry bones and the application of the traditional methods. Secondly, the information directly extrapolated from CT scan has been used to qualitatively or quantitatively assess the changes of the trabecular bones, the thickness of the cortical bones, and to perform morphometric analyses. Lastly, the most innovative approach has been the mathematical quantification of the changes of the pelvic joints, calculating the complexity of the surface. The importance of new updated reference datasets, created thanks to the use of CT scanning in forensic settings, is also discussed.CV was supported from the Danish Council for Independent Research (DFF – 4005-00102B – FTP

Photosynthesis in C3-C4 intermediate Moricandia species.

Evolution of C4 photosynthesis is not distributed evenly in the plant kingdom. Particularly interesting is the situation in the Brassicaceae, because the family contains no C4 species, but several C3-C4 intermediates, mainly in the genus Moricandia Investigation of leaf anatomy, gas exchange parameters, the metabolome, and the transcriptome of two C3-C4 intermediate Moricandia species, M. arvensis and M. suffruticosa, and their close C3 relative M. moricandioides enabled us to unravel the specific C3-C4 characteristics in these Moricandia lines. Reduced CO2 compensation points in these lines were accompanied by anatomical adjustments, such as centripetal concentration of organelles in the bundle sheath, and metabolic adjustments, such as the balancing of C and N metabolism between mesophyll and bundle sheath cells by multiple pathways. Evolution from C3 to C3-C4 intermediacy was probably facilitated first by loss of one copy of the glycine decarboxylase P-protein, followed by dominant activity of a bundle sheath-specific element in its promoter. In contrast to recent models, installation of the C3-C4 pathway was not accompanied by enhanced activity of the C4 cycle. Our results indicate that metabolic limitations connected to N metabolism or anatomical limitations connected to vein density could have constrained evolution of C4 in Moricandia

Inconsistent boundaries

Research on this paper was supported by a grant from the Marsden Fund, Royal Society of New Zealand.Mereotopology is a theory of connected parts. The existence of boundaries, as parts of everyday objects, is basic to any such theory; but in classical mereotopology, there is a problem: if boundaries exist, then either distinct entities cannot be in contact, or else space is not topologically connected (Varzi in Noûs 31:26–58, 1997). In this paper we urge that this problem can be met with a paraconsistent mereotopology, and sketch the details of one such approach. The resulting theory focuses attention on the role of empty parts, in delivering a balanced and bounded metaphysics of naive space.PostprintPeer reviewe

Viral Hepatitis and Rapid Diagnostic Test Based Screening for HBsAg in HIV-infected Patients in Rural Tanzania.

\ud \ud Co-infection with hepatitis B virus (HBV) is highly prevalent in people living with HIV in Sub-Saharan Africa. Screening for HBV surface antigen (HBsAg) before initiation of combination antiretroviral therapy (cART) is recommended. However, it is not part of diagnostic routines in HIV programs in many resource-limited countries although patients could benefit from optimized antiretroviral therapy covering both infections. Screening could be facilitated by rapid diagnostic tests for HBsAg. Operating experience with these point of care devices in HIV-positive patients in Sub-Saharan Africa is largely lacking. We determined the prevalence of HBV and Hepatitis C virus (HCV) infection as well as the diagnostic accuracy of the rapid test device Determine HBsAg in an HIV cohort in rural Tanzania. Prospectively collected blood samples from adult, HIV-1 positive and antiretroviral treatment-naïve patients in the Kilombero and Ulanga antiretroviral cohort (KIULARCO) in rural Tanzania were analyzed at the point of care with Determine HBsAg, a reference HBsAg EIA and an anti-HCV EIA. Samples of 272 patients were included. Median age was 38 years (interquartile range [IQR] 32-47), 169/272 (63%) subjects were females and median CD4+ count was 250 cells/µL (IQR 97-439). HBsAg was detected in 25/272 (9.2%, 95% confidence interval [CI] 6.2-13.0%) subjects. Of these, 7/25 (28%) were positive for HBeAg. Sensitivity of Determine HBsAg was rated at 96% (95% CI 82.8-99.6%) and specificity at 100% (95% CI, 98.9-100%). Antibodies to HCV (anti-HCV) were found in 10/272 (3.7%, 95% CI 2.0-6.4%) of patients. This study reports a high prevalence of HBV in HIV-positive patients in a rural Tanzanian setting. The rapid diagnostic test Determine HBsAg is an accurate assay for screening for HBsAg in HIV-1 infected patients at the point of care and may further help to guide cART in Sub-Saharan Africa

Multiomics resolution of molecular events during a day in the life of Chlamydomonas.

The unicellular green alga Chlamydomonas reinhardtii displays metabolic flexibility in response to a changing environment. We analyzed expression patterns of its three genomes in cells grown under light-dark cycles. Nearly 85% of transcribed genes show differential expression, with different sets of transcripts being up-regulated over the course of the day to coordinate cellular growth before undergoing cell division. Parallel measurements of select metabolites and pigments, physiological parameters, and a subset of proteins allow us to infer metabolic events and to evaluate the impact of the transcriptome on the proteome. Among the findings are the observations that Chlamydomonas exhibits lower respiratory activity at night compared with the day; multiple fermentation pathways, some oxygen-sensitive, are expressed at night in aerated cultures; we propose that the ferredoxin, FDX9, is potentially the electron donor to hydrogenases. The light stress-responsive genes PSBS, LHCSR1, and LHCSR3 show an acute response to lights-on at dawn under abrupt dark-to-light transitions, while LHCSR3 genes also exhibit a later, second burst in expression in the middle of the day dependent on light intensity. Each response to light (acute and sustained) can be selectively activated under specific conditions. Our expression dataset, complemented with coexpression networks and metabolite profiling, should constitute an excellent resource for the algal and plant communities

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Young neutron stars with soft gamma ray emission and anomalous X-ray pulsar

The observational properties of Soft Gamma Repeaters and Ano\-malous X-ray Pulsars (SGR/AXP) indicate to necessity of the energy source different from a rotational energy of a neutron star. The model, where the source of the energy is connected with a magnetic field dissipation in a highly magnetized neutron star (magnetar) is analyzed. Some observational inconsistencies are indicated for this interpretation. The alternative energy source, connected with the nuclear energy of superheavy nuclei stored in the nonequilibrium layer of low mass neutron star is discussed.Comment: 29 pages, 13 figures, Springer International Publishing Switzerland 2016 A.W. Alsabti, P. Murdin (eds.), Handbook of Supernova

Evolutionary Analysis of Mitogenomes from Parasitic and Free-Living Flatworms

Copyright: © 2015 Solà et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article

Time-resolved X-ray Scattering of Excited State Structure and Dynamics

Ultrafast gas-phase X-ray scattering using X-ray free-electron lasers (XFELs) has enabled the measurement of molecular structures and dynamics in excited states with atomic spatial and femtosecond time resolution. This chapter reviews important recent advances in the X-ray scattering of excited states. In particular, details will be given of additional observables such as the orientation of optical transition dipoles within the molecular frame, the excited state molecular electron densities, and rate constants for chemical kinetics. In excited states, the structures of medium sized molecules (up to eight non-hydrogenic atoms) have been determined with high precision in the non-hydrogenic atom–atom distances. Effects arising from the redistribution of electron density upon optical excitation are observed and confirmed by high-level calculations, allowing for the observation of ultrafast excited state charge transfer reactions. Fragmentation of molecules is readily observed, and is identifiable from a characteristic decrease in the X-ray scattering signal at small scattering angles. Furthermore, the structures of transient radical fragments have been measured