Index cohesive force analysis reveals that the US market became prone to systemic collapses since 2002

Background

The 2007–2009 financial crisis, and its fallout, has strongly emphasized the need to define new ways and measures to study and assess the stock market dynamics.

Methodology/Principal Findings

The S&P500 dynamics during 4/1999–4/2010 is investigated in terms of the index cohesive force (ICF - the balance between the stock correlations and the partial correlations after subtraction of the index contribution), and the Eigenvalue entropy of the stock correlation matrices. We found a rapid market transition at the end of 2001 from a flexible state of low ICF into a stiff (nonflexible) state of high ICF that is prone to market systemic collapses. The stiff state is also marked by strong effect of the market index on the stock-stock correlations as well as bursts of high stock correlations reminiscence of epileptic brain activity.

Conclusions/Significance

The market dynamical states, stability and transition between economic states was studies using new quantitative measures. Doing so shed new light on the origin and nature of the current crisis. The new approach is likely to be applicable to other classes of complex systems from gene networks to the human brain.     

Framework for Modelling Economic Impacts of Invasive Species,Applied to Pine Wood Nematode in Europe

Background

Economic impact assessment of invasive species requires integration of information on pest entry, establishment and spread, valuation of assets at risk and market consequences at large spatial scales. Here we develop such a framework and demonstrate its application to the pinewood nematode, Bursaphelenchus xylophilus, which threatens the European forestry industry. The effect of spatial resolution on the assessment result is analysed.

Methodology/Principal Findings

Direct economic impacts resulting from wood loss are computed using partial budgeting at regional scale, while impacts on social welfare are computed by a partial equilibrium analysis of the round wood market at EU scale. Substantial impacts in terms of infested stock are expected in Portugal, Spain, Southern France, and North West Italy but not elsewhere in EU in the near future. The cumulative value of lost forestry stock over a period of 22 years (2008–2030), assuming no regulatory control measures, is estimated at €22 billion. The greatest yearly loss of stock is expected to occur in the period 2014–2019, with a peak of three billion euros in 2016, but stabilizing afterwards at 300–800 million euros/year. The reduction in social welfare follows the loss of stock with considerable delay because the yearly harvest from the forest is only 1.8%. The reduction in social welfare for the downstream round wood market is estimated at €218 million in 2030, whereby consumers incur a welfare loss of €357 million, while producers experience a €139 million increase, due to higher wood prices. The societal impact is expected to extend to well beyond the time horizon of the analysis, and long after the invasion has stopped.

Conclusions/Significance

Pinewood nematode has large economic consequences for the conifer forestry industry in the EU. A change in spatial resolution affected the calculated directed losses by 24%, but did not critically affect conclusions.     

The illogicality of stock-brokers: psychological experiments on the effects of prior knowledge and belief biases on logical reasoning in stock trading

Background

Explanations for the current worldwide financial crisis are primarily provided by economists and politicians. However, in the present work we focus on the psychological-cognitive factors that most likely affect the thinking of people on the economic stage and thus might also have had an effect on the progression of the crises. One of these factors might be the effect of prior beliefs on reasoning and decision-making. So far, this question has been explored only to a limited extent.

Methods

We report two experiments on logical reasoning competences of nineteen stock-brokers with long-lasting vocational experiences at the stock market. The premises of reasoning problems concerned stock trading and the experiments varied whether or not their conclusions—a proposition which is reached after considering the premises—agreed with the brokers'' prior beliefs. Half of the problems had a conclusion that was highly plausible for stock-brokers while the other half had a highly implausible conclusion.

Results

The data show a strong belief bias. Stock-brokers were strongly biased by their prior knowledge. Lowest performance was found for inferences in which the problems caused a conflict between logical validity and the experts'' belief. In these cases, the stock-brokers tended to make logically invalid inferences rather than give up their existing beliefs.

Conclusions

Our findings support the thesis that cognitive factors have an effect on the decision-making on the financial market. In the present study, stock-brokers were guided more by past experience and existing beliefs than by logical thinking and rational decision-making. They had difficulties to disengage themselves from vastly anchored thinking patterns. However, we believe, that it is wrong to accuse the brokers for their “malfunctions”, because such hard-wired cognitive principles are difficult to suppress even if the person is aware of them.     

Identifying Hubs in Protein Interaction Networks

Background

In spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs), it is common to define an ad hoc degree scale that defines “hub” proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.

Methodology

In this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.

Conclusions

We find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks.     

Using Complex Networks to Characterize International Business Cycles

Background

There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles.

Methodology/Principal Findings

We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries’ GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples.

Conclusion

The use of complex networks is valuable for understanding the business cycle comovements at an international level.     

Modeling HIV/AIDS Drug Price Determinants in Brazil: Is Generic Competition a Myth?

Background

Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs) being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of international legislation and trade agreements on intellectual property rights may reduce availability of generic drugs for HIV care.

Methods and Findings

Our analyses are based on effective prices paid for ARV procurement in Brazil between 1996 and 2009. Data panel structure was exploited to gather ex-ante and ex-post information and address various sources of statistical bias. In-difference estimation offered in-depth information on ARV market characteristics which significantly influence prices. Although overall ARV prices follow a declining trend, changing characteristics in the generic segment help explain recent increase in generic ARV prices. Our results show that generic suppliers are more likely to respond to factors influencing demand size and market competition, while originator suppliers tend to set prices strategically to offset compulsory licensing threats and generic competition.

Significance

In order to guarantee the long term sustainability of access to antiretroviral treatment, our findings highlight the importance of preserving and stimulating generic market dynamics to sustain developing countries'' bargaining power in price negotiations undertaken with originator companies.     

A Cross-Sectional Analysis of Variation in Charges and Prices across California for Percutaneous Coronary Intervention

Background

Though past studies have shown wide variation in aggregate hospital price indices and specific procedures, few have documented or explained such variation for distinct and common episodes of care.

Objectives

We sought to examine the variability in charges for percutaneous coronary intervention (PCI) with a drug-eluting stent and without major complications (MS-DRG-247), and determine whether hospital and market characteristics influenced these charges.

Methods

We conducted a cross-sectional analysis of adults admitted to California hospitals in 2011 for MS-DRG-247 using patient discharge data from the California Office of Statewide Health Planning and Development. We used a two-part linear regression model to first estimate hospital-specific charges adjusted for patient characteristics, and then examine whether the between-hospital variation in those estimated charges was explained by hospital and market characteristics.

Results

Adjusted charges for the average California patient admitted for uncomplicated PCI ranged from $22,047 to $165,386 (median: $88,350) depending on which hospital the patient visited. Hospitals in areas with the highest cost of living, those in rural areas, and those with more Medicare patients had higher charges, while government-owned hospitals charged less. Overall, our model explained 43% of the variation in adjusted charges. Estimated discounted prices paid by private insurers ranged from $3,421 to $80,903 (median: $28,571).

Conclusions

Charges and estimated discounted prices vary widely between hospitals for the average California patient undergoing PCI without major complications, a common and relatively homogeneous episode of care. Though observable hospital characteristics account for some of this variation, the majority remains unexplained.     

Geographically widespread swordfish barcode stock identification: a case study of its application

Background

The swordfish (Xiphias gladius) is a cosmopolitan large pelagic fish inhabiting tempered and tropical waters and it is a target species for fisheries all around the world. The present study investigated the ability of COI barcoding to reliably identify swordfish and particularly specific stocks of this commercially important species.

Methodology

We applied the classical DNA barcoding technology, upon a 682 bp segment of COI, and compared swordfish sequences from different geographical sources (Atlantic, Indian Oceans and Mediterranean Sea). The sequences of the 5′ hyper-variable fragment of the control region (5′dloop), were also used to validate the efficacy of COI as a stock-specific marker.

Case Report

This information was successfully applied to the discrimination of unknown samples from the market, detecting in some cases mislabeled seafood products.

Conclusions

The NJ distance-based phenogram (K2P model) obtained with COI sequences allowed us to correlate the swordfish haplotypes to the different geographical stocks. Similar results were obtained with 5′dloop. Our preliminary data in swordfish Xiphias gladius confirm that Cytochrome Oxidase I can be proposed as an efficient species-specific marker that has also the potential to assign geographical provenance. This information might speed the samples analysis in commercial application of barcoding.     

Outcome of Assisted Reproductive Technology (ART) and Subsequent Self-Reported Life Satisfaction

Objective

To compare life satisfaction between women with successful or unsuccessful outcome after assisted reproductive treatment (ART) by taking into account the time since the last ART.

Design

Cohort study.

Setting

Tertiary hospital.

Patients

A total of 987 consecutive women who had undergone ART during 1996–2007 were invited and altogether 505 women participated in the study.

Interventions

A postal enquiry with a life satisfaction scale.

Main Outcome Measure

Self-reported life satisfaction in respect to the time since the last ART.

Results

In general, women who achieved a live birth after ART had a significantly higher life satisfaction than those who had unsuccessful ART, especially when compared in the first three years. The difference disappeared in the time period of 6–9 years after ART. The unsuccessfully treated women who had a child by some other means before or after the unsuccessful ART had comparable life satisfaction with successfully treated women even earlier.

Conclusions

Even if unsuccessful ART outcome is associated with subsequent lower level of life satisfaction, it does not seem to threaten the long-term wellbeing.     

Gender-related differences in the dysfunctional resting networks of migraine suffers

Background

Migraine shows gender-specific incidence and has a higher prevalence in females. However, little is known about gender-related differences in dysfunctional brain organization, which may account for gender-specific vulnerability and characteristics of migraine. In this study, we considered gender-related differences in the topological property of resting functional networks.

Methodology/Principal Findings

Data was obtained from 38 migraine patients (18 males and 20 females) and 38 healthy subjects (18 males and 20 females). We used the graph theory analysis, which becomes a powerful tool in investigating complex brain networks on a whole brain scale and could describe functional interactions between brain regions. Using this approach, we compared the brain functional networks between these two groups, and several network properties were investigated, such as small-worldness, network resilience, nodal centrality, and interregional connections. In our findings, these network characters were all disrupted in patients suffering from chronic migraine. More importantly, these functional damages in the migraine-affected brain had a skewed balance between males and females. In female patients, brain functional networks showed worse resilience, more regions exhibited decreased nodal centrality, and more functional connections revealed abnormalities than in male patients.

Conclusions

These results indicated that migraine may have an additional influence on females and lead to more dysfunctional organization in their resting functional networks.     

Motor Properties of Peripersonal Space in Humans

Background

A stimulus approaching the body requires fast processing and appropriate motor reactions. In monkeys, fronto-parietal networks are involved both in integrating multisensory information within a limited space surrounding the body (i.e. peripersonal space, PPS) and in action planning and execution, suggesting an overlap between sensory representations of space and motor representations of action. In the present study we investigate whether these overlapping representations also exist in the human brain.

Methodology/Principal Findings

We recorded from hand muscles motor-evoked potentials (MEPs) induced by single-pulse of transcranial magnetic stimulation (TMS) after presenting an auditory stimulus either near the hand or in far space. MEPs recorded 50 ms after the near-sound onset were enhanced compared to MEPs evoked after far sounds. This near-far modulation faded at longer inter-stimulus intervals, and reversed completely for MEPs recorded 300 ms after the sound onset. At that time point, higher motor excitability was associated with far sounds. Such auditory modulation of hand motor representation was specific to a hand-centred, and not a body-centred reference frame.

Conclusions/Significance

This pattern of corticospinal modulation highlights the relation between space and time in the PPS representation: an early facilitation for near stimuli may reflect immediate motor preparation, whereas, at later time intervals, motor preparation relates to distant stimuli potentially approaching the body.     

The Effect of Souvenaid on Functional Brain Network Organisation in Patients with Mild Alzheimer’s Disease: A Randomised Controlled Study

Background

Synaptic loss is a major hallmark of Alzheimer’s disease (AD). Disturbed organisation of large-scale functional brain networks in AD might reflect synaptic loss and disrupted neuronal communication. The medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect, is designed to enhance synapse formation and function and has been shown to improve memory performance in patients with mild AD in two randomised controlled trials.

Objective

To explore the effect of Souvenaid compared to control product on brain activity-based networks, as a derivative of underlying synaptic function, in patients with mild AD.

Design

A 24-week randomised, controlled, double-blind, parallel-group, multi-country study.

Participants

179 drug-naïve mild AD patients who participated in the Souvenir II study.

Intervention

Patients were randomised 1∶1 to receive Souvenaid or an iso-caloric control product once daily for 24 weeks.

Outcome

In a secondary analysis of the Souvenir II study, electroencephalography (EEG) brain networks were constructed and graph theory was used to quantify complex brain structure. Local brain network connectivity (normalised clustering coefficient gamma) and global network integration (normalised characteristic path length lambda) were compared between study groups, and related to memory performance.

Results

The network measures in the beta band were significantly different between groups: they decreased in the control group, but remained relatively unchanged in the active group. No consistent relationship was found between these network measures and memory performance.

Conclusions

The current results suggest that Souvenaid preserves the organisation of brain networks in patients with mild AD within 24 weeks, hypothetically counteracting the progressive network disruption over time in AD. The results strengthen the hypothesis that Souvenaid affects synaptic integrity and function. Secondly, we conclude that advanced EEG analysis, using the mathematical framework of graph theory, is useful and feasible for assessing the effects of interventions.

Trial registration

Dutch Trial Register NTR1975.     

Detecting temporal protein complexes from dynamic protein-protein interaction networks

Background

Proteins dynamically interact with each other to perform their biological functions. The dynamic operations of protein interaction networks (PPI) are also reflected in the dynamic formations of protein complexes. Existing protein complex detection algorithms usually overlook the inherent temporal nature of protein interactions within PPI networks. Systematically analyzing the temporal protein complexes can not only improve the accuracy of protein complex detection, but also strengthen our biological knowledge on the dynamic protein assembly processes for cellular organization.

Results

In this study, we propose a novel computational method to predict temporal protein complexes. Particularly, we first construct a series of dynamic PPI networks by joint analysis of time-course gene expression data and protein interaction data. Then a Time Smooth Overlapping Complex Detection model (TS-OCD) has been proposed to detect temporal protein complexes from these dynamic PPI networks. TS-OCD can naturally capture the smoothness of networks between consecutive time points and detect overlapping protein complexes at each time point. Finally, a nonnegative matrix factorization based algorithm is introduced to merge those very similar temporal complexes across different time points.

Conclusions

Extensive experimental results demonstrate the proposed method is very effective in detecting temporal protein complexes than the state-of-the-art complex detection techniques.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-335) contains supplementary material, which is available to authorized users.     

Long-term costs and health impact of continued global fund support for antiretroviral therapy

Background

By the end of 2011 Global Fund investments will be supporting 3.5 million people on antiretroviral therapy (ART) in 104 low- and middle-income countries. We estimated the cost and health impact of continuing treatment for these patients through 2020.

Methods and Findings

Survival on first-line and second-line ART regimens is estimated based on annual retention rates reported by national AIDS programs. Costs per patient-year were calculated from country-reported ARV procurement prices, and expenditures on laboratory tests, health care utilization and end-of-life care from in-depth costing studies. Of the 3.5 million ART patients in 2011, 2.3 million will still need treatment in 2020. The annual cost of maintaining ART falls from $1.9 billion in 2011 to $1.7 billion in 2020, as a result of a declining number of surviving patients partially offset by increasing costs as more patients migrate to second-line therapy. The Global Fund is expected to continue being a major contributor to meeting this financial need, alongside other international funders and domestic resources. Costs would be $150 million less in 2020 with an annual 5% decline in first-line ARV prices and $150–370 million less with a 5%–12% annual decline in second-line prices, but $200 million higher in 2020 with phase out of stavudine (d4T), or $200 million higher with increased migration to second-line regimens expected if all countries routinely adopted viral load monitoring. Deaths postponed by ART correspond to 830,000 life-years saved in 2011, increasing to around 2.3 million life-years every year between 2015 and 2020.

Conclusions

Annual patient-level direct costs of supporting a patient cohort remain fairly stable over 2011–2020, if current antiretroviral prices and delivery costs are maintained. Second-line antiretroviral prices are a major cost driver, underscoring the importance of investing in treatment quality to improve retention on first-line regimens.     

Global Self-Regulation of the Cellular Metabolic Structure

Background

Different studies have shown that cellular enzymatic activities are able to self-organize spontaneously, forming a metabolic core of reactive processes that remain active under different growth conditions while the rest of the molecular catalytic reactions exhibit structural plasticity. This global cellular metabolic structure appears to be an intrinsic characteristic common to all cellular organisms. Recent work performed with dissipative metabolic networks has shown that the fundamental element for the spontaneous emergence of this global self-organized enzymatic structure could be the number of catalytic elements in the metabolic networks.

Methodology/Principal Findings

In order to investigate the factors that may affect the catalytic dynamics under a global metabolic structure characterized by the presence of metabolic cores we have studied different transitions in catalytic patterns belonging to a dissipative metabolic network. The data were analyzed using non-linear dynamics tools: power spectra, reconstructed attractors, long-term correlations, maximum Lyapunov exponent and Approximate Entropy; and we have found the emergence of self-regulation phenomena during the transitions in the metabolic activities.

Conclusions/Significance

The analysis has also shown that the chaotic numerical series analyzed correspond to the fractional Brownian motion and they exhibit long-term correlations and low Approximate Entropy indicating a high level of predictability and information during the self-regulation of the metabolic transitions. The results illustrate some aspects of the mechanisms behind the emergence of the metabolic self-regulation processes, which may constitute an important property of the global structure of the cellular metabolism.     

Mesoscopic structure conditions the emergence of cooperation on social networks

Background

We study the evolutionary Prisoner''s Dilemma on two social networks substrates obtained from actual relational data.

Methodology/Principal Findings

We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement with the observations in both real substrates.

Conclusion

Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.     

Evolvement of uniformity and volatility in the stressed global financial village

Background

In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village.

Methodology/Principal Findings

We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets—U.S., U.K., Germany, Japan, China and India—from January 2000 until December 2010. We found that while the developed “western” markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing “eastern” markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches “identity”—it switches between periods of high meta-correlations with the “western” markets and periods when it behaves more similarly to the “eastern” markets.

Conclusions/Significance

The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive “financial seismograph” to detect early signs of global financial crises so they can be treated before they develop into worldwide events.     

Efficient prediction of human protein-protein interactions at a global scale

Background

Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.

Results

On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments.

Conclusions

The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0383-1) contains supplementary material, which is available to authorized users.     

Large Daily Stock Variation Is Associated with Cardiovascular Mortality in Two Cities of Guangdong,China

Objective

The current study aimed to examine the effects of daily change of the Shenzhen Stock Exchange Index on cardiovascular mortality in Guangzhou and Taishan, China.

Methods

Daily mortality and stock performance data during 2006–2010 were collected to construct the time series for the two cities. A distributed lag non-linear model was utilized to examine the effect of daily stock index changes on cardiovascular mortality after controlling for potential confounding factors.

Results

We observed a delayed non-linear effect of the stock index change on cardiovascular mortality: both rising and declining of the stock index were associated with increased cardiovascular deaths. In Guangzhou, the 15–25 lag days cumulative relative risk of an 800 index drop was 2.08 (95% CI: 1.38–3.14), and 2.38 (95% CI: 1.31–4.31) for an 800 stock index increase on the cardiovascular mortality, respectively. In Taishan, the cumulative relative risk over 15–25 days lag was 1.65 (95% CI: 1.13–2.42) for an 800 index drop and 2.08 (95% CI: 1.26–3.42) for an 800 index rising, respectively.

Conclusions

Large ups and downs in daily stock index might be important predictor of cardiovascular mortality.     

Effects of Core Self-Evaluations on the Job Burnout of Nurses: The Mediator of Organizational Commitment

Objective

To explore the impact of Core self-evaluations on job burnout of nurses, and especially to test and verify the mediator role of organizational commitment between the two variables.

Method

Random cluster sampling was used to pick up participants sample, which consisted of 445 nurses of a hospital in Shanghai. Core self-evaluations questionnaire, job burnout scale and organizational commitment scale were administrated to the study participants.

Results

There are significant relationships between Core self-evaluations and dimensions of job burnout and organizational commitment. There is a significant mediation effect of organizational commitment between Core self-evaluations and job burnout.

Conclusions

To enhance nurses’ Core self-evaluations can reduce the incidence of job burnout.