Electrophysiological correlates of emotional source memory in high-trait-anxiety individuals

The interaction between recognition memory and emotion has become a research hotspot in recent years. Dual process theory posits that familiarity and recollection are two separate processes contributing to recognition memory, but further experimental evidence is needed. The present study explored the emotional context effects on successful and unsuccessful source retrieval amongst 15 high-trait-anxiety college students by using event-related potentials (ERPs) measurement. During study, a happy, fearful, or neutral face picture first was displayed, then a Chinese word was superimposed centrally on the picture and subjects were asked to remember the word and the corresponding type of picture. During the test participants were instructed to press one of four buttons to indicate whether the displayed word was an old or new word. And then, for the old word, indicate whether it had been shown with a fearful, happy, or neutral face during the study. ERPs were generally more positive for remembered words than for new words and the ERP difference was termed as an old/new effect. It was found that, for successful source retrieval (it meant both the item and the source were remembered accurately) between 500 and 700 ms (corresponding to a late positive component, LPC), there were significant old/new effects in all contexts. However, for unsuccessful source retrieval (it meant the correct recognition of old items matched with incorrect source attribution), there were no significant old/new effects in happy and neutral contexts, though significant old/new effects were observed in the fearful context. Between 700 and 1200 ms (corresponding to a late slow wave, LSW), there were significant old/new effects for successful source retrieval in happy and neutral contexts. However, in the fearful context, the old/new effects were reversed, ERPs were more negative for successful source retrieval compared to correct rejections. Moreover, there were significant emotion effects for successful source retrieval at this time window. Further analysis showed ERPs of old items were more negative in fearful context than in neutral context. The results showed that early unsuccessful fearful source retrieval processes (related to familiarity) were enhanced, but late successful fearful source retrieval processes during source retrieval monitoring (related to recollection) were weakened. This provided preliminary evidence for the dual processing theory

Problem gambling, gambling correlates and health seeking attitudes in a Chinese sample: An empirical evaluation.

There is an increasing consensus that problem gambling (PG) is a serious social issue among the Chinese, but little is known of the factors associated with PG among the Chinese using validated and improved PG measure-ments. This study examined the patterns of PG and the PG predictive ability of variables such as gam-bling-related cognitions, gambling urge, depression, anxiety, stress, and help-seeking attitudes among Chinese individuals living in Taiwan. The participants consisted of 801 Taiwanese Chinese student and community indi-viduals (Mean age = 25.36 years). The prevalence of PG (Problem Gambling Severity Index; PGSI) and patho-logical gambling (South Oaks Gambling Screen; SOGS) are higher in this Taiwanese Chinese sample as com-pared with past prevalence research. Significant differences were found between PGSI groups (i.e., non-PG, low-risk, moderate-risk, and PG) in socio-demographic variables. Erroneous gambling-related cognitions and overall negative psychological states significantly predicted PG. In addition, interaction effects of gender, mediation effects, and the predictive ability of help-seeking attitudes were discussed. The findings of this study have important implications in the understanding of PG among the Chinese. Gambling-related cognitions and negative psychological states are important factors that should be addressed in intervention programs

Treatment for anxiety disorders in Malaysia

This current study aims to systematically review the treatments for anxiety disorders in Malaysia. PsycINFO, MEDLINE databases, and 28 local journals were used to search published papers in this area. Eight articles were subjected to review after excluding 273 papers that did not meet the inclusion criteria. A total of 598 participants with various types of anxiety disorders were included in the review. Based on the findings, the combination of pharmacotherapy and psychotherapy provided better treatment outcomes if compared to psychotherapy or pharmacotherapy alone. The combination of selective serotonin reuptake inhibitors and cognitive behaviour therapy was considered as one of the most effective treatment to treat patients with anxiety disorders in Malaysia. This is in line with the clinical practice guidelines from the Ministry of Health Singapore and Canada. Even though there were some limitations in the methodology and reporting of the results, it can be concluded that efforts have been taken to conduct studies related to treatments for patients with anxiety disorders in Malaysia. Future studies are suggested to make conscious efforts to overcome these limitations

Geographic uncertainties in external exposome studies: A multi-scale approach to reduce exposure misclassification

Background: Many studies on environment-health associations have emphasized that the selected buffer size (i.e., the scale of the geographic context when exposures are assigned at people's address location) may affect estimated effect sizes. However, there is limited methodological progress in addressing these buffer size-related uncertainties. Aim: We aimed to 1) develop a statistical multi-scale approach to address buffer-related scale effects in cohort studies, and 2) investigate how environment-health associations differ between our multi-scale approach and ad hoc selected buffer sizes. Methods: We used lacunarity analyses to determine the largest meaningful buffer size for multiple high-resolution exposure surfaces (i.e., fine particulate matter [PM2.5], noise, and the normalized difference vegetation index [NDVI]). Exposures were linked to 7.7 million Dutch adults at their home addresses. We assigned exposure estimates based on buffers with fine-grained distance increments until the lacunarity-based upper limit was reached. Bayesian Cox model averaging addressed geographic uncertainties in the estimated exposure effect sizes within the exposure-specific upper buffer limits on mortality. Z-tests assessed statistical differences between averaged effect sizes and those obtained through pre-selected 100, 300, 1200, and 1500 m buffers. Results: The estimated lacunarity curves suggested exposure-specific upper buffer size limits; the largest was for NDVI (960 m), followed by noise (910 m) and PM2.5 (450 m). We recorded 845,229 deaths over eight years of follow-up. Our multi-scale approach indicated that higher values of NDVI were health-protectively associated with mortality risk (hazard ratio [HR]: 0.917, 95 % confidence interval [CI]: 0.886–0.948). Increased noise exposure was associated with an increased risk of mortality (HR: 1.003, 95 % CI: 1.002–1.003), while PM2.5 showed null associations (HR:0.998, 95 % CI: 0.997–1.000). Effect sizes of NDVI and noise differed significantly across the averaged and prespecified buffers (p < 0.05). Conclusions: Geographic uncertainties in residential-based exposure assessments may obscure environment-health associations or risk spurious ones. Our multi-scale approach produced more consistent effect estimates and mitigated contextual uncertainties

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults