Implementing Swedish Models of Social Work in a Russian Context

The economic and social changes taking place in Russia in recent decades have implied a restructuring of the Russian society. Among other things, Russian leaders have expressed a need for the reorientation of social development. In the 1990’s, cooperation was initiated on a number of social work and social welfare projects with international support, a process further speeded up during President Jeltsin’s state visit to Sweden in 1997. Discussions between the Swedish International Development Cooperation Agency (Sida) and the Russian authorities dealing with welfare issues started from the assumption that Russian professional social work was weak and needed to be strengthened. In the 1990's Sida was also given a stronger general mandate to work with other former Soviet countries in Eastern Europe, for example the Baltic States. The Russian-Swedish discussions resulted in projects aiming to raise social work competencies in public authorities, managements and among social workers in Russia. One of the areas chosen for these projects was Saint Petersburg, where several projects aiming to develop new models for social work were launched. The point of departure has been to transfer and adjust Swedish models of social work to the Russian context. The Stockholm University Department of Social Work became responsible for a number of such projects and besides using academic teachers also involved a number of practitioners, such as social workers in disablement services and reformatory staff who could meet and match Russian authorities and partners.

Integration of Truncated Distributions in Exponential Family with Simulation Models of Logistics and Supply Chain Management

Truncated distributions of the exponential family have great influence in the simulation models. This paper discusses the truncated Weibull distribution specifically. The truncation of the distribution is achieved by the Maximum Likelihood Estimation method or combined with the expectation and variance expressions. After the fitting of distribution, the goodness-of-fit tests (the Chi-Square test and the Kolmogorov-Smirnov test) are executed to rule out the rejected hypotheses. Finally the distributions are integrated in various simulation models, e. g. shipment consolidation model, to compare the influence of truncated and original versions of Weibull distribution on the model.

The cannabinoid CB2 receptor-selective phytocannabinoid beta-caryophyllene exerts analgesic effects in mouse models of inflammatory and neuropathic pain

The widespread plant volatile beta-caryophyllene (BCP) was recently identified as a natural selective agonist of the peripherally expressed cannabinoid receptor 2 (CB2). It is found in relatively high concentrations in many spices and food plants. A number of studies have shown that CB2 is critically involved in the modulation of inflammatory and neuropathic pain responses. In this study, we have investigated the analgesic effects of BCP in animal models of inflammatory and neuropathic pain. We demonstrate that orally administered BCP reduced inflammatory (late phase) pain responses in the formalin test in a CB2 receptor-dependent manner, while it had no effect on acute (early phase) responses. In a neuropathic pain model the chronic oral administration of BCP attenuated thermal hyperalgesia and mechanical allodynia, and reduced spinal neuroinflammation. Importantly, we found no signs of tolerance to the anti-hyperalgesic effects of BCP after prolonged treatment. Oral BCP was more effective than the subcutaneously injected synthetic CB2 agonist JWH-133. Thus, the natural plant product BCP may be highly effective in the treatment of long lasting, debilitating pain states. Our results have important implications for the role of dietary factors in the development and modulation of chronic pain conditions.

Differential effects of intranasal vaccination with recombinant NcPDI in different mouse models of Neospora caninum infection

In this study, mice were vaccinated intranasally with recombinant N. caninum protein disulphide isomerase (NcPDI) emulsified in cholera toxin (CT) or cholera toxin subunit B (CTB) from Vibrio cholerae. The effects of vaccination were assessed in the murine nonpregnant model and the foetal infection model, respectively. In the nonpregnant mice, previous results were confirmed, in that intranasal vaccination with recNcPDI in CT was highly protective, and low cerebral parasite loads were noted upon real-time PCR analysis. Protection was accompanied by an IgG1-biased anti-NcPDI response upon infection and significantly increased expression of Th2 (IL-4/IL-10) and IL-17 transcripts in spleen compared with corresponding values in mice treated with CT only. However, vaccination with recNcPDI in CT did not induce significant protection in dams and their offspring. In the dams, increased splenic Th1 (IFN-γ/IL-12) and Th17 mRNA expressions was detected. No protection was noted in the groups vaccinated with recNcPDI emulsified in CTB. Thus, vaccination with recNcPDI in CT in nonpregnant mice followed by challenge infection induced a protective Th2-biased immune response, while in the pregnant mouse model, the same vaccine formulation resulted in a Th1-biased inflammatory response and failed to protect dams and their progeny.

Theoretical models of planetary system formation: mass vs. semi-major axis

Context. Planet formation models have been developed during the past years to try to reproduce what has been observed of both the solar system and the extrasolar planets. Some of these models have partially succeeded, but they focus on massive planets and, for the sake of simplicity, exclude planets belonging to planetary systems. However, more and more planets are now found in planetary systems. This tendency, which is a result of radial velocity, transit, and direct imaging surveys, seems to be even more pronounced for low-mass planets. These new observations require improving planet formation models, including new physics, and considering the formation of systems. Aims: In a recent series of papers, we have presented some improvements in the physics of our models, focussing in particular on the internal structure of forming planets, and on the computation of the excitation state of planetesimals and their resulting accretion rate. In this paper, we focus on the concurrent effect of the formation of more than one planet in the same protoplanetary disc and show the effect, in terms of architecture and composition of this multiplicity. Methods: We used an N-body calculation including collision detection to compute the orbital evolution of a planetary system. Moreover, we describe the effect of competition for accretion of gas and solids, as well as the effect of gravitational interactions between planets. Results: We show that the masses and semi-major axes of planets are modified by both the effect of competition and gravitational interactions. We also present the effect of the assumed number of forming planets in the same system (a free parameter of the model), as well as the effect of the inclination and eccentricity damping. We find that the fraction of ejected planets increases from nearly 0 to 8% as we change the number of embryos we seed the system with from 2 to 20 planetary embryos. Moreover, our calculations show that, when considering planets more massive than ~5 M⊕, simulations with 10 or 20 planetary embryos statistically give the same results in terms of mass function and period distribution.

The structure of the asteroid 4 Vesta as revealed by models of planet-scale collisions

Asteroid 4Vesta seems to be a major intact protoplanet, with a surface composition similar to that of the HED (howardite-eucrite-diogenite) meteorites. The southern hemisphere is dominated by a giant impact scar, but previous impact models have failed to reproduce the observed topography. The recent discovery that Vesta's southern hemisphere is dominated by two overlapping basins provides an opportunity to model Vesta's topography more accurately. Here we report three-dimensional simulations of Vesta's global evolution under two overlapping planet-scale collisions. We closely reproduce its observed shape, and provide maps of impact excavation and ejecta deposition. Spiral patterns observed in the younger basin Rheasilvia, about one billion years old, are attributed to Coriolis forces during crater collapse. Surface materials exposed in the north come from a depth of about 20kilometres, according to our models, whereas materials exposed inside the southern double-excavation come from depths of about 60-100kilometres. If Vesta began as a layered, completely differentiated protoplanet, then our model predicts large areas of pure diogenites and olivine-rich rocks. These are not seen, possibly implying that the outer 100kilometres or so of Vesta is composed mainly of a basaltic crust (eucrites) with ultramafic intrusions (diogenites).

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Family models of independence/interdependence and their intergenerational similarity in Germany, Turkey, and India

Family change theory suggests three ideal-typical family models characterized by different combinations of emotional and material interdependencies in the family. Its major proposition is that in economically developing countries with a collectivistic background a family model of emotional interdependence emerges from a family model of complete interdependence. The current study aims to identify and compare patterns of family-related value orientations related to family change theory across three cultures and two generations. Overall, N = 919 dyads of mothers and their adolescent children from Germany, Turkey, and India participated in the study. Three clusters were identified representing the family models of independence, interdependence, and emotional interdependence, respectively. Especially the identification of an emotionally interdependent value pattern using a person-oriented approach is an important step in the empirical validation of family change theory. The preference for the three family models differed across as well as within cultures and generations according to theoretical predictions. Dyadic analyses pointed to substantial intergenerational similarities and also to differences in family models, reflecting both cultural continuity as well as change in family-related value orientations.

Values of children and family models of adolescents: An eleven-culture study

Starting from Kagitcibasi's (2007) conceptualization of family models, this study compared N = 2961 adolescents' values across eleven cultures and explored whether patterns of values were related to the three proposed family models through cluster analyses. Three clusters with value profiles corresponding to the family models of interdependence, emotional interdependence, and independence were identified on the cultural as well as on the individual level. Furthermore, individual-level clusters corresponded to culture-level clusters in terms of individual cluster membership. The results largely support Kagitcibasi's proposition of changing family models and demonstrate their representation as individual-level value profiles across cultures.

THE MECHANISM OF TUMORIGENESIS IN THE IMMORTALIZED HUMAN PANCREATIC CELL LINES: CELL CULTURE MODELS OF HUMAN PANCREATIC CANCER

The mechanism of tumorigenesis in the immortalized human pancreatic cell lines: cell culture models of human pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer in the world. The most common genetic lesions identified in PDAC include activation of K-ras (90%) and Her2 (70%), loss of p16 (95%) and p14 (40%), inactivation p53 (50-75%) and Smad4 (55%). However, the role of these signature gene alterations in PDAC is still not well understood, especially, how these genetic lesions individually or in combination contribute mechanistically to human pancreatic oncogenesis is still elusive. Moreover, a cell culture transformation model with sequential accumulation of signature genetic alterations in human pancreatic ductal cells that resembles the multiple-step human pancreatic carcinogenesis is still not established. In the present study, through the stepwise introduction of the signature genetic alterations in PDAC into the HPV16-E6E7 immortalized human pancreatic duct epithelial (HPDE) cell line and the hTERT immortalized human pancreatic ductal HPNE cell line, we developed the novel experimental cell culture transformation models with the most frequent gene alterations in PDAC and further dissected the molecular mechanism of transformation. We demonstrated that the combination of activation of K-ras and Her2, inactivation of p16/p14 and Smad4, or K-ras mutation plus p16 inactivation, was sufficient for the tumorigenic transformation of HPDE or HPNE cells respectively. We found that these transformed cells exhibited enhanced cell proliferation, anchorage-independent growth in soft agar, and grew tumors with PDAC histopathological features in orthotopic mouse model. Molecular analysis showed that the activation of K-ras and Her2 downstream effector pathways –MAPK, RalA, FAK, together with upregulation of cyclins and c-myc were involved in the malignant transformation. We discovered that MDM2, BMP7 and Bmi-1 were overexpressed in the tumorigenic HPDE cells, and that Smad4 played important roles in regulation of BMP7 and Bmi-1 gene expression and the tumorigenic transformation of HPDE cells. IPA signaling pathway analysis of microarray data revealed that abnormal signaling pathways are involved in transformation. This study is the first complete transformation model of human pancreatic ductal cells with the most common gene alterations in PDAC. Altogether, these novel transformation models more closely recapitulate the human pancreatic carcinogenesis from the cell origin, gene lesion, and activation of specific signaling pathway and histopathological features.

Representation via Probabilities: Models of Probabilistic Modeling

How do probabilistic models represent their targets and how do they allow us to learn about them? The answer to this question depends on a number of details, in particular on the meaning of the probabilities involved. To classify the options, a minimalist conception of representation (Su\'arez 2004) is adopted: Modelers devise substitutes (``sources'') of their targets and investigate them to infer something about the target. Probabilistic models allow us to infer probabilities about the target from probabilities about the source. This leads to a framework in which we can systematically distinguish between different models of probabilistic modeling. I develop a fully Bayesian view of probabilistic modeling, but I argue that, as an alternative, Bayesian degrees of belief about the target may be derived from ontic probabilities about the source. Remarkably, some accounts of ontic probabilities can avoid problems if they are supposed to apply to sources only.

Cultural models of healing and health: An ethnography of professional nurses and healers

Cultural models of the domains healing and health are important in how people understand health and their behavior regarding it. The biomedicine model has been predominant in Western society. Recent popularity of holistic health and alternative healing modalities contrasts with the biomedical model and the assumptions upon which that model has been practiced. The holistic health movement characterizes an effort by health care providers and others such as nurses to expand the biomedical model and has often incorporated alternative modalities. This research described and compared the cultural models of healing of professional nurses and alternative healers. A group of nursing faculty who promote a holistic model were compared to a group of healers using healing touch. Ethnographic methods of participant observation, free listing and pile sort were used. Theoretical sampling in the free listings reached saturation at 18 in the group of nurses and 21 in the group of healers. Categories consistent for both groups emerged from the data. These were: physical, mental, attitude, relationships, spiritual, self management, and health seeking including biomedical and alternative resources. The healers had little differentiation between the concepts health and healing. The nurses, however, had more elements in self management for health and in health seeking for healing. This reflects the nurse's role in facilitating the shift in locus of responsibility between health and healing. The healers provided more specific information regarding alternative resources. The healer's conceptualization of health was embedded in a spiritual belief system and contrasted dramatically with that of biomedicine. The healer's models also contrasted with holistic health in the areas of holism, locus of responsibility, and dealing with uncertainty. The similarity between the groups and their dissimilarity to biomedicine suggest a larger cultural shift in beliefs regarding health care. ^

Models of DNA sequence evolution

Models of DNA sequence evolution and methods for estimating evolutionary distances are needed for studying the rate and pattern of molecular evolution and for inferring the evolutionary relationships of organisms or genes. In this dissertation, several new models and methods are developed.^ The rate variation among nucleotide sites: To obtain unbiased estimates of evolutionary distances, the rate heterogeneity among nucleotide sites of a gene should be considered. Commonly, it is assumed that the substitution rate varies among sites according to a gamma distribution (gamma model) or, more generally, an invariant+gamma model which includes some invariable sites. A maximum likelihood (ML) approach was developed for estimating the shape parameter of the gamma distribution $(\alpha)$ and/or the proportion of invariable sites $(\theta).$ Computer simulation showed that (1) under the gamma model, $\alpha$ can be well estimated from 3 or 4 sequences if the sequence length is long; and (2) the distance estimate is unbiased and robust against violations of the assumptions of the invariant+gamma model.^ However, this ML method requires a huge amount of computational time and is useful only for less than 6 sequences. Therefore, I developed a fast method for estimating $\alpha,$ which is easy to implement and requires no knowledge of tree. A computer program was developed for estimating $\alpha$ and evolutionary distances, which can handle the number of sequences as large as 30.^ Evolutionary distances under the stationary, time-reversible (SR) model: The SR model is a general model of nucleotide substitution, which assumes (i) stationary nucleotide frequencies and (ii) time-reversibility. It can be extended to SRV model which allows rate variation among sites. I developed a method for estimating the distance under the SR or SRV model, as well as the variance-covariance matrix of distances. Computer simulation showed that the SR method is better than a simpler method when the sequence length $L>1,000$ bp and is robust against deviations from time-reversibility. As expected, when the rate varies among sites, the SRV method is much better than the SR method.^ The evolutionary distances under nonstationary nucleotide frequencies: The statistical properties of the paralinear and LogDet distances under nonstationary nucleotide frequencies were studied. First, I developed formulas for correcting the estimation biases of the paralinear and LogDet distances. The performances of these formulas and the formulas for sampling variances were examined by computer simulation. Second, I developed a method for estimating the variance-covariance matrix of the paralinear distance, so that statistical tests of phylogenies can be conducted when the nucleotide frequencies are nonstationary. Third, a new method for testing the molecular clock hypothesis was developed in the nonstationary case. ^