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Background: Findings of reward disturbances in unaffected relatives of patients with schizophrenia suggest reward disturbances as an endophenotype for schizophrenia. Twin studies, where 1 twin has been diagnosed with a schizophrenia spectrum disorder, can further explore this. Methods: We used Danish registries to identify twin pairs with at least 1 twin having a schizophrenia spectrum disorder diagnosis and control twin pairs matched on age, sex, and zygosity. The analyses included data from 34 unaffected co-twins (16 females), 42 probands with schizophrenia spectrum disorder (17 females), and 83 control twins (42 females). Participants performed a modified incentive delay task during functional magnetic resonance imaging. Whole-brain group differences were analyzed by performing comparisons between co-twins and control twins. Correlations with cognitive flexibility were tested. Results: Compared with control twins, co-twins showed no differences in striatal regions, but increased signal in the dorsolateral prefrontal cortex (DLPFC) during missed target contrast was observed. In co-twins, increased DLPFC signal was associated with lower intra-extra dimensional set-shifting scores indicative of higher cognitive flexibility. Conclusions: Unaffected co-twins did not have decreased striatal activity during anticipation as previously reported for patients with schizophrenia. Instead, they showed increased activity in the DLPFC during evaluation of missed target contrast, which correlated with their level of cognitive flexibility. Unaffected co-twins had no diagnosis at a mean age of 40 years. This could indicate that greater cognitive flexibility and increased activity in the right DLPFC during processing of unexpected negative outcome represents a compensatory resilience mechanism in predisposed twins.

In this study, we explore climate justice with specific reference to vulnerability at the level of different sectors in 90 developing countries in Asia, Africa and Europe, over a period from 2010 to 2019. The paper seeks to advance the discussion on the idea that adaptation financing is allocated according to the level of need in the recipient country and sector. By considering five crucial sectors (food, water, health, infrastructure and habitat), we explore the linear and quadratic effect of the vulnerability of each sector on the allocated endowment. The study is based on a dynamic panel regression method based on the Generalized Method of Moments (GMM) in the system model. Our findings reveal that vulnerability is an important consideration in funding allocation. The results suggest that the relationship between adaptation funding and vulnerability is sector-dependent. We also observe that this relationship is non-linear, providing further evidence of distributive justice in terms of allocating more funding to the most vulnerable sectors. Climate justice begins to emerge when vulnerability reaches a certain threshold. However, it appears that the infrastructure sector is dysfunctional in terms of adaptation financing needs and investments undertaken. Overall, the regulations put in place should further integrate climate risk parameters into technical and procedural standards to make projects more effective and climate justice more widespread.

With increasing population growth and urban sprawl, many coastal lowlands are unprecedentedly vulnerable to climate change and its impacts, such as rising sea levels, increasing extreme storm events, and coastal flooding. Quantifying coastal flood vulnerability serves as a tool to identify a system’s weakness, monitor its change, and support making targeted climate adaptation policies. The assessment framework proposed in this research uses principal component analysis (PCA) and a weighting method to build a composite indicator of flood vulnerability index and evaluate the vulnerability for 256 coastal census tracts and 24 municipalities along the coast of Connecticut, USA. The research uses Keiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity to test sample adequacy and performs data standardization for all indicators. Through PCA, 30 coastal vulnerability-related indicators were grouped into four major dimensions: hazard exposure, socio-economic, physical/land use and land cover, and natural. The findings highlight the variations of flood vulnerability across highly urbanized areas, suburban areas, and rural areas; and the gradient from coastal low-elevation region to high-elevation inland area. This variance is unevenly caused by different dimensions although they may trade-off with each other when aggregated, the dominant dimensions play a significant or decisive role in the vulnerability assessment. This research built an automatic and objective assessment framework that is flexible enough to be applied at a smaller scale so as to obtain detailed analysis and it can be used as a decision-making support system.

Integrated community energy system (ICES) enables multi-energy synergy and impulses interaction of integrated demand response (IDR) from the demand side. Nevertheless, the randomness lies in IDR resources and renewable generation in the ICES configuration issue still lacks thorough analysis. Furthermore, the widely focused concern of resiliency urges more proactive consideration of potential emergencies at the planning stage of ICES. To this end, this paper proposed a resilience-oriented stochastic ICES configuration framework considering IDR influence. First, generalized IDR models are set up in detail with elaborate fuzzy feature analysis of price-responsive multi-energy loads. Then, the vulnerability indicators of tie lines and converting devices of the ICES are first introduced to demonstrate the occasional outage in the normal operation and blackout in the emergent case. In addition, the worst-case conditional value-at-risk (WCVaR) theory is innovatively integrated to the traditional risk-neutral model, which is formulated as a two-stage stochastic chance-constrained programming problem, aiming to combine portfolio with minimizing the worst-case cost caused by a disaster. The models are then transformed into mixed-integer linear programming problems via several linearization techniques. Finally, the results of the case studies showed the established model's superiority in improving the overall economy (reduce 6.94% of the worst-case cost) and system resiliency (decrease the value-at-risk by 3.20%) against an unforeseen hurricane. Meanwhile, the ICES reliability was also improved by declining 25.65% of unintended load curtailment faced with an emergency. The proposed approach provided an efficient preventive portfolio scheme of the IDR-integrated ICES for decision-makers' different risk preferences of natural hazards.

The risk of climate change impacts occurring is a function of a socioecological system’s exposure and vulnerability to climate-related hazards. Vulnerability itself is the result of a system's sensitivity and adaptive capacity. The potential climate change driven biophysical impacts on the municipality Totonicapán in the western highlands of Guatemala are well documented in outcome vulnerability studies and projected to be severe. They include droughts, frosts, forest fires and life zone changes which also represent important hazards to the municipality’s population. Yet, recent detailed socioeconomic information on the municipality’s contextual vulnerability is scarce. Moreover, social capital which is central to the yet successful management of the unique communal coniferous forests is poorly understood. The present study evaluates the contextual vulnerability of the municipality's population and communal forests using 5 interviews and 167 household surveys from 3 communities for 15 socioeconomic indicators. Qualitative analysis of the interviews urges for further investigation into the link between emigration to the USA, the loss of social capital and communal forest management. Quantitative analysis of the indicators and their aggregation into a vulnerability index by Principal Component Analysis demonstrates that education is the most important vulnerability factor, followed by income which was negatively related to natural resource dependency. An overarching theme was gender inequality. The study is a plea for location and population specific research and adaptation strategies as it identifies significant differences even between communities of the same municipality.

We previously reported familial aggregation in flush response to niacin skin patch among schizophrenia patients and their nonpsychotic relatives. However, little is known about whether this abnormal skin response is associated with genetic loading for schizophrenia. This study compared the niacin flush response in subjects from families with only one member affected with schizophrenia (simplex families) with those from families having a sib-pair with schizophrenia (multiplex families). Subjects were patients with schizophrenia and their nonpsychotic first-degree relatives from simplex families (176 probands, 260 parents, and 80 siblings) and multiplex families (311 probands, 180 parents, and 52 siblings) as well as 94 healthy controls. Niacin patches of 3 concentrations (0.001M, 0.01M, and 0.1M) were applied to forearm skin, and the flush response was rated at 5, 10, and 15 minutes, respectively, with a 4-point scale. More attenuated flush response to topical niacin was shown in schizophrenia probands and their relatives from multiplex families than in their counterparts from simplex families, and the differentiation was better revealed using 0.1M concentration of niacin than 0.01M or 0.001M. For the highest concentration of 0.1M and the longest time lag of 15 minutes, a subgroup of probands (23%), parents (27%), and siblings (19%) still exhibited nonflush response. Flush response to niacin skin patch is more impaired in schizophrenia patients and their relatives from families with higher genetic loading for schizophrenia, and this finding has implications for future genetic dissection of schizophrenia. © 2008 The Authors., published_or_final_version

Though a reduced flush response to niacin has been found in schizophrenic patients, whether it is a vulnerability indicator to schizophrenia remains little known. We aimed to examine the familial aggregation in niacin flush response among schizophrenic patients and their nonpsychotic relatives. In a sample of 153 schizophrenia probands, 217 parents, 70 siblings, and 94 normal subjects, 3 concentrations (0.001 M, 0.01 M, and 0.1 M) of niacin were applied to the forearm skin and the flush response was rated at 5, 10, and 15 minutes, respectively, with a 4-point scale. Both the heritability for continuous flush scores and the recurrence risk ratios for binary nonflush response in the nonpsychotic relatives of schizophrenic patients were estimated, and ordinal logistic regression analyses of relatives' niacin response on probands' were further conducted to adjust for potential confounders. The greatest heritabilities ranged from 47% (0.01 M at 10 minutes) to 54% (0.1 M at 5 minutes). The risk ratios of 0.01 M at 10 minutes (ranging from 2.60 for using score 1 or less to 5.06 for using score 0 as nonflush) and 5 minutes (1.66 for using score 0 as nonflush) were significantly greater than one. Multiple ordinal logistic regression analyses further revealed that the association between probands and relatives in niacin flush response remained after adjustment for potential confounders, including age, sex, allergy, tobacco smoking, and coffee drinking. These findings provide support for the potential of niacin flush response as a vulnerability indicator to schizophrenia. © The Author 2006. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved., link_to_subscribed_fulltext

The aim of the paper is to analyse the vulnerability of the Central and Eastern European accession countries to the EU as well as that of Turkey and Russia to a financial crisis. Our methodology is an extension of the signals approach. We develop a composite indicator to measure the evolution of the risk potential in each country. Our findings show that crises in Central and Eastern Europe are caused by much the usual suspects as in others emerging markets. In particular an overvalued exchange rate, weak exports and dwindling currency reserves have good predictive power for assessing crisis vulnerabilities.

The aim of paper is to analyse the vulnerability of the Central and Eastern European accession countries to the EU as well as that of Turkey and Russia to a financial crisis. Our methodology is an extension of the signals approach. We develop a composite indicator to measure the evolutin of of the risk potential in each country. Our findings show that crises in Central and Eastern Europe are caused by much the usual suspects s in others emerging markets. In particular an overvalued exchange rate. Weak exports and dwindling currency reserves have good precictive power for assessing crisis vulnerabilities. Keywords: F31, F47, financial crises, vulnerability indicator, Central and Eastern Europe

The aim of paper is to analyse the vulnerability of the Central and Eastern European accession countries to the EU as well as that of Turkey and Russia to a financial crisis. Our methodology is an extension of the signals approach. We develop a composite indicator to measure the evolutin of of the risk potential in each country. Our findings show that crises in Central and Eastern Europe are caused by much the usual suspects s in others emerging markets. In particular an overvalued exchange rate. Weak exports and dwindling currency reserves have good precictive power for assessing crisis vulnerabilities.