Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study

The issue of information sharing and exchanging is one of the most important issues in the areas of artificial intelligence and knowledge-based systems (KBSs), or even in the broader areas of computer and information technology. This paper deals with a special case of this issue by carrying out a case study of information sharing between two well-known heterogeneous uncertain reasoning models: the certainty factor model and the subjective Bayesian method. More precisely, this paper discovers a family of exactly isomorphic transformations between these two uncertain reasoning models. More interestingly, among isomorphic transformation functions in this family, different ones can handle different degrees to which a domain expert is positive or negative when performing such a transformation task. The direct motivation of the investigation lies in a realistic consideration. In the past, expert systems exploited mainly these two models to deal with uncertainties. In other words, a lot of stand-alone expert systems which use the two uncertain reasoning models are available. If there is a reasonable transformation mechanism between these two uncertain reasoning models, we can use the Internet to couple these pre-existing expert systems together so that the integrated systems are able to exchange and share useful information with each other, thereby improving their performance through cooperation. Also, the issue of transformation between heterogeneous uncertain reasoning models is significant in the research area of multi-agent systems because different agents in a multi-agent system could employ different expert systems with heterogeneous uncertain reasonings for their action selections and the information sharing and exchanging is unavoidable between different agents. In addition, we make clear the relationship between the certainty factor model and probability theory.

A mechanistic study on reduced toxicity of irontecan by coadministered thalidomide, a tumor necrosis factor-a inhibitor

Dose-limiting diarrhea and myelosuppression compromise the success of irinotecan (7-ethyl-10-[4-[1-piperidino]-1-piperidino] carbonyloxycamptothecin) (CPT-11)-based chemotherapy. A recent pilot study indicates that thalidomide attenuates the toxicity of CPT-11 in cancer patients. This study aimed to investigate whether coadministered thalidomide modulated the toxicities of CPT-11 and the underlying mechanisms using several in vivo and in vitro models. Diarrhea, intestinal lesions, cytokine expression, and intestinal epithelial apoptosis were
monitored. Coadministered thalidomide (100 mg/kg i.p. for 8 days) significantly attenuated body weight loss, myelosuppression, diarrhea, and intestinal histological lesions caused by CPT-11 (60 mg/kg i.v. for 4 days). This was accompanied by inhibition of tumor necrosis factor-, interleukins 1 and 6 and interferon-, and intestinal epithelial apoptosis. Coadministered
thalidomide also significantly increased the systemic exposure of CPT-11 but decreased that of SN-38 (7-ethyl-10-hydroxycampothecin). It significantly reduced the biliary excretion and cecal exposure of CPT-11, SN-38, and SN-38 glucuronide. Thalidomide hydrolytic products inhibited hydrolysis of CPT-11 in rat liver microsomes but not in primary rat hepatocytes. In addition, thalidomide and its major hydrolytic products, such as phthaloyl glutamic acid (PGA), increased the intracellular accumulation of CPT-11 and SN-38 in primary rat hepatocytes. They also significantly decreased the transport of CPT-11 and SN-38 in Caco-2 and parental MDCKII cells. Thalidomide and PGA also significantly inhibited P-glycoprotein (PgP/MDR1), multidrug resistance-associated protein (MRP1)- and MRP2-mediated CPT-11 and SN-38 transport in MDCKII cells. These results provide insights into the pharmacodynamic and  pharmacokinetic mechanisms for the protective effects of thalidomide against CPT-11-induced intestinal toxicity.

Lack of functional alpha-lactalbumin prevents involution in Cape fur seals and identifies the protein as an apoptotic milk factor in mammary gland involution

The mammary gland undergoes a sophisticated programme of developmental changes during pregnancy/lactation. However, little is known about processes involving initiation of apoptosis at involution following weaning. We used fur seals as models to study the molecular process of involution as these animals display a unique mammary gland phenotype. Fur seals have long lactation periods whereby mothers cycle between secreting copious quantities of milk for 2 to 3 days suckling pups on land, with trips to sea alone to forage for up to 23 days during which time mammary glands remain active without initiating apoptosis/involution.

Longitudinal evaluation of a risk-factor model for adolescent suicidality

This research developed two best-fitting structural equation models of risk factors for adolescent depression and suicidality: a core model, which included parenting factors, gender, depression, and suicidality, and an extended model, which also encompassed personality traits (Introversion and Impulsivity) and mood factors (Anxiety and Anger). Further, this research investigated the consistency of model fit across time (Le., 1 month & 12 months) and samples, and explored the effectiveness of the ReachOut! Internet site as a psychoeducational prevention strategy for adolescent depression and suicidality. Gender, age, and location differences were also explored. Participants were 185 Year-9 students and 93 Year-10 students aged 14 - 16 years, from seven secondary schools in regional and rural Victoria. Students were given a survey which included the Parental Bonding Instrument (Parker, Tupling, & Brown, 1979), the Millon Adolescent Personality Inventory (Millon, Green, & Meagher, 1982), the Profile of Mood States Inventory (McNair & Lorr, 1964), items on suicidal behaviour including some questions from the Revised Adolescent Suicide Questionnaire (Pearce & Martin, 1994), and questions on loss and general demographics. Results supported an indirect model of risk factors, with family factors directly influencing personality factors, which in turn influenced mood factors, including depression, which then influenced suicidality. At the theoretical level, results supported Attachment Theory (Bowlby, 1969), demonstrating that perceived parenting styles that are warm and not overly controlling are more conducive to an adolescent's emotional well-being than are parenting styles that are cold and controlling. Further, results supported Millon's theory of personality (1981), demonstrating that parenting style influences a child's personality. Short-term intervention effects from the internet site were a decrease in Introversion for the full sample, and decreased Inhibition and Suicidality for a high-risk subgroup. Long-term age effects were decreased Inhibition and increased Anxiety for the fall sample. There was also a probable intervention effect for Depression for the high-risk subgroup. No location differences for the risk factors were found between regional and rural areas.

Relevance of health literacy models for people with severe mental illness

People with severe mental illness experience elevated levels of impairment, morbidity and health-risk behaviours compared with the general population. Despite this, it is consistently reported that they do not visit health professionals, including preventative health professionals, as regularly as the general population. Their poor health suggests that current health promotion efforts have been largely ineffective in addressing their specific needs. Barriers that might explain this include lack of motivation, expense and lack of access. Health literacy is also a potentially important factor. As a part of a programme of work to develop appropriate and effective health promotion for this group, we have explored existing health-literacy models and their relevance to marginalized populations, in particular, people experiencing severe mental illness. A comprehensive search of the literature was undertaken. Models of health literacy identified were analyzed to determine the source population, underpinning theory/frameworks, supporting research evidence and to consider their potential generalisability. This paper presents an analysis of existing health-literacy models in the context of severe mental illness. We propose that because existing models of health literacy were developed through consultation with people experiencing challenges to specific health and social issues, for example, cancer, low income and limited education, this raises questions as to the applicability of these models to people experiencing severe and ongoing mental illness. Whilst such individuals were not actively excluded in the development of the existing models, we propose the development of an alternative model which considers this population's needs and limitations in accessing effective health-promotion campaigns/programs.

A factor-analytic study exploring the factors of co-worker cohesion

Despite the applied importance of cohesion within organisational settings, researchers have yet to reach consensus about the dimensionality of group cohesion, and therefore appropriate tools for its measurement. The way that cohesion has generally been conceptualised has changed over time, but the measures appear not to reflect the underlying theory. This deficiency has impeded attempts to explore the relationship between co-worker cohesion and group performance (Beal et al., 2003; Mullen & Copper, 1994). Given inconsistent findings from previous factor analyses of cohesion, the present study employed exploratory means to help clarify the factor structure of cohesion within the workplace. Potential participants were recruited via the researchers' social networks. This snowballing technique led to 236 participants completing the online questionnaire. Exploratory factor analysis revealed four first-order factors of team commitment, friendliness, interpersonal conflict and communication that collectively accounted for 55.17% of the variance shared among the 75 cohesion items. Subsequently, a single higher-order factor was extracted which accounted for over half of the co-variation among the first order factors. This higher-order factor seems to reflect a general cohesion factor, as it was loaded by a diffuse collection of items, including those from the four lower-order factors as well as items that failed to load onto these lower-order factors. While there were similarities between these results and those of previous studies, the present factor structure did not map perfectly onto any of the existing conceptual models of cohesion. This finding highlights the need to incorporate some alternate factors that have previously been given little consideration.

Quantifying urbanisation as a risk factor for non-communicable disease

Aim of this study was to investigate the poorly understood relationship between the process of urbanization and non-communicable diseases (NCDs) in Sri Lanka using a multi-component, quantitative measure of urbanicity.

NCD prevalence data were taken from the Sri Lankan Diabetes and Cardiovascular Study comprising a representative sample of people from seven of the nine provinces in Sri Lanka (n=4,485/5,000; response rate=89.7%). We constructed a measure of the urban environment for seven areas using a seven-item scale based on data from study clusters to develop an ―urbanicity” scale. The items were population size, population density, and access to markets, transportation, communications/media, economic factors, environment/sanitation, health, education, and housing quality. Linear and logistic regression models were constructed to examine the relationship between urbanicity and chronic disease risk factors.

Among men, urbanicity was positively associated with physical inactivity (OR: 3.22; 2.27 – 4.57), high body mass index (OR: 2.45; 95% CI: 1.88 – 3.20) and diabetes mellitus (OR: 2.44; 95% CI: 1.66 – 3.57). Among women, too, urbanicity was positively associated with physical inactivity (OR: 2.29; 95% CI: 1.64 – 3.21), high body mass index (OR: 2.92;95% CI: 2.41 – 3.55) and diabetes mellitus (OR: 2.10; 95% CI: 1.58 – 2.80).

There is a clear relationship between urbanicity and common modifiable risk factors for chronic disease in a representative sample of Sri Lankan adults.

Granular Activated Carbon (GAC) adsorption in tertiary wastewater treatment : experiments and models

Wastewater treatment has always been a major concern in the developed countries. Over the last few decades, activated carbon adsorption has gained importance as an alternative tertiary wastewater treatment and purification process. In this study, granular activated carbon (GAC) adsorption was evaluated in terms of total organic carbon (TOC) removal from low strength synthetic wastewater. This paper provides details on adsorption experiments conducted on synthetic wastewater to develop suitable adsorption isotherms. Although the inorganics used in the synthetic wastewater solution had an overall unfavourable effect on adsorption of organics, the GAC adsorption system was found to be effective in removing TOC from the wastewater. This study showed that equation of state (EOS) theory was able to fit the adsorption isotherm results more precisely than the most commonly used Freundlich isotherm. Biodegradation of the organics with time was the most crucial and important aspect of the system and it was taken into account in determining the isotherm parameters. Initial organic concentration of the wastewater was the determining factor of the model parameters, and hence the isotherm parameters were determined covering a wide range of initial organic concentrations of the wastewater. As such, the isotherm parameters derived using the EOS theory could predict the batch adsorption and fixed bed adsorption results of the multi-component system successfully. The isotherm parameters showed a significant effect on the determination of the mass transfer coefficients in batch and fixed bed systems.

Topic transition detection using hierarchical hidden Markov and semi-Markov models

In this paper we introduce a probabilistic framework to exploit hierarchy, structure sharing and duration information for topic transition detection in videos. Our probabilistic detection framework is a combination of a shot classification step and a detection phase using hierarchical probabilistic models. We consider two models in this paper: the extended Hierarchical Hidden Markov Model (HHMM) and the Coxian Switching Hidden semi-Markov Model (S-HSMM) because they allow the natural decomposition of semantics in videos, including shared structures, to be modeled directly, and thus enabling efficient inference and reducing the sample complexity in learning. Additionally, the S-HSMM allows the duration information to be incorporated, consequently the modeling of long-term dependencies in videos is enriched through both hierarchical and duration modeling. Furthermore, the use of the Coxian distribution in the S-HSMM makes it tractable to deal with long sequences in video. Our experimentation of the proposed framework on twelve educational and training videos shows that both models outperform the baseline cases (flat HMM and HSMM) and performances reported in earlier work in topic detection. The superior performance of the S-HSMM over the HHMM verifies our belief that duration information is an important factor in video content modeling.

M-Dimension : multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network.

We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

Confirmatory factor analysis of the Beck Depression inventory in obese individuals seeking surgery

Background : The Beck Depression Inventory (BDI) is frequently employed as measure of depression in studies of obesity. The aim of the study was to assess the factorial structure of the BDI in obese patients prior to bariatric surgery.

Methods : Confirmatory factor analysis was conducted on the current published factor analyses of the BDI. Three published models were initially analysed with two additional modified models subsequently included. A sample of 285 patients presenting for Lap-Band® surgery was used.

Results : The published bariatric model by Munoz et al. was not an adequate fit to the data. The general model by Shafer et al. was a good fit to the data but had substantial limitations. The weight loss item did not significantly load on any factor in either model. A modified Shafer model and a proposed model were tested, and both were found to be a good fit to the data with minimal differences between the two. A proposed model, in which two items, weight loss and appetite, were omitted, was suggested to be the better model with good reliability.

Conclusions : The previously published factor analysis in bariatric candidates by Munoz et al. was a poor fit to the data, and use of this factor structure should be seriously reconsidered within the obese population. The hypothesised model was the best fit to the data. The findings of the study suggest that the existing published models are not adequate for investigating depression in obese patients seeking surgery.

A factor analytical approach to the efficient futures market hypothesis

Most empirical evidence suggests that the efficient futures market hypothesis, henceforth referred to as EFMH, stating that spot and futures prices should cointegrate with a unit slope on futures prices, does not hold, a finding at odds with many theoretical models. This article argues that these results can be attributed in part to the low power of univariate tests, and that the use of panel data can generate more powerful tests. The current article can be seen as a step in this direction. In particular, a newly developed factor analytical approach is employed, which is very general and, in addition, free of the otherwise so common incidental parameters bias in the presence of fixed effects. The approach is applied to a large panel covering 17 commodities between March 1991 and August 2012. The evidence suggests that the EFMH cannot be rejected once the panel evidence has been taken into account. © 2014 Wiley Periodicals, Inc.

Predicting migratory flight altitudes by physiological migration models

Using the altitudinal profiles of wind, temperature, pressure, and humidity in three flight models, we tried to explain the altitudinal distributions of nocturnal migrants recorded by radar above a desert in southern Israel. In the simplest model, only the tailwind component was used as a predictor of the most preferred flight altitude (T model). The energy model (E model) predicted flight ranges according to mechanical power consumption in flapping flight depending on air density and wind conditions, assuming optimal adjustment of airspeed and compensation of crosswinds, and including the influence of mass loss during flight. The energy-water model (EW model) used the same assumptions and parameters as the E model but also included restrictions caused by dehydration. Because wind was by far the most important factor governing altitudinal distribution of nocturnal migrants, differences in predictions of the three models were small. In a first approach, the EW model performed slightly better than the E model, and both performed slightly better than the T model. Differences were most pronounced in spring, when migrants should fly high according to wind conditions, but when climbing and descending they must cross lower altitudes where conditions are better with respect to dehydration. A simplified energy model (Es model) that omits the effect of air density on flight costs explained the same amount of variance in flight altitude as the more complicated E and EW models. By omitting the effect of air density, the Es model predicted lower flight altitudes and thus compensated for factors that generally bias height distributions downward but are not considered in the models (i.e. climb and descent through lower air layers, cost of ascent, and decrease of oxygen partial pressure with altitude). Our results confirm that wind profiles, and thus energy rather than water limitations, govern the altitudinal distribution of nocturnal migrants, even under the extreme humidity and temperature conditions in the trade wind zone.

Regulation of granulocyte colony-stimulating factor and its receptor in skeletal muscle is dependent upon the type of inflammatory stimulus

The cytokine granulocyte colony-stimulating factor (G-CSF) binds to its receptor (G-CSFR) to stimulate hematopoietic stem cell mobilization, myelopoiesis, and the production and activation of neutrophils. In response to exercise-induced muscle damage, G-CSF is increased in circulation and G-CSFR has recently been identified in skeletal muscle cells. While G-CSF/G-CSFR activation mediates pro- and anti-inflammatory responses, our understanding of the role and regulation in the muscle is limited. The aim of this study was to investigate, in vitro and in vivo, the role and regulation of G-CSF and G-CSFR in skeletal muscle under conditions of muscle inflammation and damage. First, C2C12 myotubes were treated with lipopolysaccharide (LPS) with and without G-CSF to determine if G-CSF modulates the inflammatory response. Second, the regulation of G-CSF and its receptor was measured following eccentric exercise-induced muscle damage and the expression levels we investigated for redox sensitivity by administering the antioxidant N-acetylcysteine (NAC). LPS stimulation of C2C12 myotubes resulted in increases in G-CSF, interleukin (IL)-6, monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor-α (TNFα) messenger RNA (mRNA) and an increase in G-CSF, IL-6, and MCP-1 release from C2C12 myotubes. The addition of G-CSF following LPS stimulation of C2C12 myotubes increased IL-6 mRNA and cytokine release into the media, however it did not affect MCP-1 or TNFα. Following eccentric exercise-induced muscle damage in humans, G-CSF levels were either marginally increased in circulation or remain unaltered in skeletal muscle. Similarly, G-CSFR levels remained unchanged in response to damaging exercise and G-CSF/G-CSFR did not change in response to NAC. Collectively, these findings suggest that G-CSF may cooperate with IL-6 and potentially promote muscle regeneration in vitro, whereas in vivo aseptic inflammation induced by exercise did not change G-CSF and G-CSFR responses. These observations suggest that different models of inflammation produce a different G-CSF response.