Search Results (15)

Background/Objectives: New devices such as surface electromyography (sEMG) have been proposed to support traditional gnathological examination and diagnostic protocols. The aim of this study is to investigate whether sEMG can be considered a diagnostic instrument to discriminate between healthy subjects and patients with temporomandibular disorders (TMDs) of an articular or muscular nature. Methods: A systematic review was conducted according to PRISMA guidelines using literature searches of MEDLINE (via PubMed), Scopus, and Web of Science. Inclusion criteria: recent clinical studies (≤10 years) in English or Italian, involving electromyography in TMD diagnosis, with a control group of healthy patients. Data considered to be homogenous were subjected to meta-analysis (95% confidence interval [CI]; α = 0.05). Hedge g was calculated because all variables were continuous. Articles meeting the inclusion criteria were checked for further consideration, and relevant data were collected into two tables. In total, 18 studies were included after full-text reading. Meta-analyses were carried out for the static impact index (IMP), percentage overlapping coefficient (POC), and torque coefficient, and dynamic Symmetrical Mastication Index (SMI). Results: Patients with TMD had lower values in all parameters except IMP. sEMG registered a reduction in masseter activity, lower chewing efficiency, and an increase in fatigue during contractions in TMD patients. Conclusions: sEMG is not reliable to distinguish healthy from TMD patients, but despite the limitations related to the high variability in the studies (type of electromyography, static or dynamic tests, and population characteristics), the sEMG results are reliable considering the POC and SMI parameters, encouraging more in-depth studies for a predictable clinical practice. Patients with TMD had lower values in the dynamic index SMI and in static indexes POC and torque coefficient, except IMP. EMG might performs better if employed in muscle forms. Full article

The global ageing population faces rising depression rates due to social, economic, and health changes. Depression in older adults, often linked to isolation and health issues, requires comprehensive care. Psychotherapeutic interventions could be effective in reducing symptoms, offering personalized and holistic support. Particularly low-threshold interventions, such as those offered in community-dwelling older adults, which older adults can easily access and which may reduce stigma, promise to close the treatment gap. This review examines community-based psychotherapeutic interventions for older adults with depression. Methods: This review investigates psychotherapeutic interventions for reducing depressive symptoms in older adults in a community setting. RCTs were assessed using Joanna Briggs Institute tools. The following databases were searched: CINAHL Plus with Full Text, MedicLatina, MEDLINE with Full Text, and the Psychology and Behavioral Sciences Collection. Results: A meta-analysis of 13 studies with 1528 participants showed a medium, significant pooled effect size at post-intervention (Hedges’ g = −0.36, p < 0.001) and substantial heterogeneity. Follow-up analysis of studies indicated a small, non-significant effect (Hedges’ g = −0.17, p = 0.27). Group interventions, particularly the “reminiscence protocol”, had the largest significant effect. Discussion: This systematic review and meta-analysis found that in community-dwelling older adults’ group psychotherapeutic interventions, particularly the “reminiscence protocol” and “modified behavioral activation treatment” are most effective for reducing depressive symptoms. Individual psychotherapeutic interventions like “prevention of suicide in primary care elderly” and “behavioral activation” also show effectiveness, with group psychotherapeutic interventions being generally more effective than when these treatments are offered in individual psychotherapeutic interventions. Conclusion: Group and individual psychotherapeutic interventions reduce depressive symptoms in community-dwelling older adults, with group psychotherapeutic interventions being more effective. Full article

Background/Objectives: Light therapy has emerged as a promising non-pharmacological treatment for depressive symptoms. This meta-analysis aims to evaluate the effectiveness of light therapy specifically for depressive symptoms in elderly populations, with a focus on how different light intensities and spectra influence treatment outcomes. Methods: A systematic search targeting studies on light therapy for depressive symptoms in older adults was performed across multiple databases, including PubMed, Google Scholar, PsycINFO, and EMBASE, covering studies from database inception until July 2024. A total of 565 records were identified, with 461 studies remaining after removing duplicates. Following the screening of titles and abstracts, 54 studies underwent full-text review, resulting in the inclusion of 22 studies with a total of 1290 participants (687 in the intervention group and 603 in the control group). Results: The overall effect size for light therapy on depressive symptoms was moderate (Hedges’ g = 0.525, p < 0.001). Higher light intensities (10,000 lux and above) demonstrated significantly greater effectiveness compared to lower intensities. White light had the most substantial effect, while bluish light showed moderate efficacy. Significant heterogeneity was observed across studies (I² = 80.459%), indicating variability in treatment outcomes based on study design, intensity, and light spectrum. Conclusions: This meta-analysis confirms that light therapy is an effective treatment for reducing depressive symptoms in older adults, particularly at higher intensities and with specific light spectra such as white light. Given the heterogeneity in results, future research should focus on optimizing treatment parameters to enhance clinical outcomes within this population. Full article

Unsymmetrical dimethylhydrazine (UDMH) is a common liquid propellant widely used in rocket engines and other applications. The safety of UDMH in service is affected by its slow oxidation during long-term storage to form impurities such as dimethylamine (DMA) and formaldehyde dimethylhydrazone (FDH). How these impurities affect combustion performance is not known, and in order to assess these effects, the present experiments investigated the combustion characteristics of self-igniting fuels and carried out ignition delay time measurements and flame propagation velocity measurements of pure UDMH and its denatured mixtures in a nitrogen tetroxide (NTO) atmosphere. This experiment was carried out to measure the delay time of hedge ignition of pure UDMH and qualitative analysis of its flame propagation properties under vacuum conditions at room temperature (T = 293 K). Ignition delay time measurements and flame propagation characterization were performed under the same experimental conditions for UDMH mixed with 1%, 5% and 10% FDH, UDMH mixed with 1%, 5% and 10% H₂O, UDMH mixed with 1%, 5% and 10% DMA, as well as for UDMH mixed with the same proportions of the three substances (1%, 5% and 10%). The flame propagation characteristics were analyzed. The results showed that the incorporation of DMA, H₂O and FDH in different proportions could inhibit the combustion of UDMH to varying degrees and prolong its ignition delay time. It is worth noting that the introduction of FDH had the least effect on it, and the least effect was observed at a concentration of 1%. In contrast, the effect of DMA on UDMH is more obvious, and the addition of H₂O has the largest increase in the ignition delay time of UDMH. In the flame propagation experiment, the flame of the experimental group adding H₂O can no longer fill the whole experimental window, while the other experimental groups can still make the window full of flame. Combined with the measurements of the ignition delay time, it can be seen that the moisture content has the greatest effect on the combustion characteristics. Full article

Understanding the changes in cognitive processing that accompany changes in posture can expand our understanding of embodied cognition and open new avenues for applications in (neuro)ergonomics. Recent studies have challenged the question of whether standing up alters cognitive performance. An electronic database search for randomized controlled trials was performed using Academic Search Complete, CINAHL Ultimate, MEDLINE, PubMed, and Web of Science following PRISMA guidelines, PICOS framework, and standard quality assessment criteria (SQAC). We pooled data from a total of 603 healthy young adults for incongruent and 578 for congruent stimuli and Stroop effect (mean age = 24 years). Using random-effects results, no difference was found between sitting and standing for the Stroop effect (Hedges’ g = 0.13, 95% CI = −0.04 to 0.29, p = 0.134), even when comparing congruent (Hedges’ g = 0.10; 95% CI: −0.132 to 0.339; Z = 0.86; p = 0.389) and incongruent (Hedges’ g = 0.18; 95% CI: −0.072 to 0.422; Z = 1.39; p = 0.164) stimuli separately. Importantly, these results imply that changing from a seated to a standing posture in healthy young adults is unlikely to have detrimental effects on selective attention and cognitive control. To gain a full understanding of this phenomenon, further research should examine this effect in a population of healthy older adults, as well as in a population with pathology. Full article

The stock market is constantly shifting and full of unknowns. In India in 2000, technological advancements led to significant growth in the Indian stock market, introducing online share trading via the internet and computers. Hence, it has become essential to manage risk in the Indian stock market, and volatility plays a critical part in assessing the risks of different stock market elements such as portfolio risk management, derivative pricing, and hedging techniques. As a result, several scholars have lately been interested in forecasting stock market volatility. This study analyzed India VIX (NIFTY 50 volatility index) to identify the behavior of the Indian stock market in terms of volatility and then evaluated the forecasting ability of GARCH- and RNN-based LSTM models using India VIX out of sample data. The results indicated that the NIFTY 50 index’s volatility is asymmetric, and leverage effects are evident in the results of the EGARCH (1, 1) model. Asymmetric GARCH models such as EGARCH (1, 1) and TARCH (1, 1) showed slightly better forecasting accuracy than symmetric GARCH models like GARCH (1, 1). The results also showed that overall GARCH models are slightly better than RNN-based LSTM models in forecasting the volatility of the NIFTY 50 index. Both types of models (GARCH models and RNN based LSTM models) fared equally well in predicting the direction of the NIFTY 50 index volatility. In contrast, GARCH models outperformed the LSTM model in predicting the value of volatility. Full article

Recent evidence suggests that diet can modify the risk of future cognitive impairment and dementia. A biologically plausible rationale and initial clinical data indicate that the antioxidant activities of dietary carotenoids may assist the preservation of cognitive function. A meta-analysis of randomized controlled trials was conducted to examine the relationship between carotenoid supplementation and cognitive performance. A literature search was conducted in the MEDLINE (via PubMed), Scopus, Web of Science, and Cochrane databases from their inception to July 2020. A total of 435 studies were retrieved. Abstract screening using predefined inclusion and exclusion criteria was followed by full-text screening and data extraction of study characteristics and measured outcomes. A meta-analysis of eligible trials was performed using a random-effects model to estimate pooled effect size. We identified 9 studies with a total of 4402 nondemented subjects, whose age ranged from 45 to 78 years. Results of the pooled meta-analysis found a significant effect of carotenoid intervention on cognitive outcomes (Hedge’s g = 0.14; 95% confidence interval: 0.08, 0.20, p < 0.0001). There was no evidence of heterogeneity among the studies (?2 = 0.00, I² = 0.00%, H² = 1.00) or publication bias. Although further studies are needed, our results suggest that carotenoid interventions are associated with better cognitive performance. Thus, these dietary compounds may help to reduce the risk of cognitive impairment and dementia. Full article

This study employs the Vector Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity (VAR-AGARCH) model to examine both return and volatility spillovers from the USA (developed) and China (Emerging) towards eight emerging Asian stock markets during the full sample period, the US financial crisis, and the Chinese Stock market crash. We also calculate the optimal weights and hedge ratios for the stock portfolios. Our results reveal that both return and volatility transmissions vary across the pairs of stock markets and the financial crises. More specifically, return spillover was observed from the US and China to the Asian stock markets during the US financial crisis and the Chinese stock market crash, and the volatility was transmitted from the USA to the majority of the Asian stock markets during the Chinese stock market crash. Additionally, volatility was transmitted from China to the majority of the Asian stock markets during the US financial crisis. The weights of American stocks in the Asia-US portfolios were found to be higher during the Chinese stock market crash than in the US financial crisis. For the majority of the Asia-China portfolios, the optimal weights of the Chinese stocks were almost equal during the Chinese stock market crash and the US financial crisis. Regarding hedge ratios, fewer US stocks were required to minimize the risk for Asian stock investors during the US financial crisis. In contrast, fewer Chinese stocks were needed to minimize the risk for Asian stock investors during the Chinese stock market crash. This study provides useful information to institutional investors, portfolio managers, and policymakers regarding optimal asset allocation and risk management. Full article

We use the the heterogeneous autoregressive realized volatility (HAR-RV) model to analyze both in sample and out-of-sample whether a measure of investor happiness predicts the daily realized volatility of oil-price returns, where we use high-frequency intraday data to measure realized volatility. Full-sample estimates reveal that realized volatility is significantly negatively linked to investor happiness at a short forecast horizon. Similarly, out-of-sample results indicate that investor happiness significantly improves the accuracy of forecasts of realized volatility at a short forecast horizon. Results for a medium and a long forecast horizon are insignificant. We argue that our results shed light on the role played by speculation in oil products and the potential function of oil-related products as a hedge against risks in traditional financial assets. Full article

Pace bowlers must often perform extended bowling spells with maximal ball release speed (BRS) while targeting different delivery lengths when playing a multi-day match. This study investigated the effect of an eight over spell upon pace bowling biomechanics and performance at different delivery lengths. Nine male bowlers (age = 18.8 ± 1.7 years) completed an eight over spell, while targeting different lengths (short: 7–10 m, good: 4–7 m, full: 0–4 m from the batter’s stumps, respectively) in a randomized order. Trunk, knee and shoulder kinematics and ground reaction forces at front foot contact (FFC), as well as run-up velocity and BRS were measured. Paired sample t-tests (p ≤ 0.01), Hedges’ g effect sizes, and statistical parametrical mapping were used to assess differences between mean variables from the first and last three overs. No significant differences (p = 0.05–0.98) were found in any discrete or continuous variables, with the magnitude of difference being trivial-to-medium (g = 0.00–0.73) across all variables. Results suggest pace bowlers sustain BRS through a single eight over spell while tolerating the repeatedly high whole-body biomechanical loads as suggested by maintaining the kinematics or technique at the assessed joints during FFC. Practically, the findings are advantageous for bowling performance and support current bowling load monitoring practices. Full article

For a high-power static synchronous compensator (STATCOM), a full-power pre-operation test in the factory is necessary to ensure the product quality of a newly manufactured one. But owing to the hardware limitation and cost of test platform, such test is currently too difficult to conduct in the factory, thus it poses great risk to the on-site operation and commissioning. To address this issue, this paper proposes an individual phase full-power testing method for STATCOM. By changing the port connection, three-phase STATCOM was reconstructed into a structure that two phases are in parallel and then in series with the third-phase, and then connected to two phases of the rated voltage grid. Then by rationally matching the voltage and current of three phases, the parallel phases can get a reactive current hedging under both the rated voltage and rated current, meanwhile three phases maintain their active power balance. As a result, STATCOM gets a phase full-power tested phase by phase. The simulation results in Matlab/Simulink show that, under the proposed test system, both the voltage and current of the parallel two phases get their rated values while the grid current is only about 3% of the rated current, meanwhile the DC-link voltage of each phase converter is stabilized. Compared with other testing methods for STATCOM, this method requires neither extra hardware nor high-capacity power supply to construct the test platform, but it can simultaneously examine both the entire main circuit and a large part of the control system in STATCOM. Therefore, it provides a cost-effective engineering method for the factory test of high-power STATCOM. Full article

This paper explores the use of neural networks to reduce the computational cost of pricing and hedging variable annuity guarantees. Pricing these guarantees can take a considerable amount of time because of the large number of Monte Carlo simulations that are required for the fair value of these liabilities to converge. This computational requirement worsens when Greeks must be calculated to hedge the liabilities of these guarantees. A feedforward neural network is a universal function approximator that is proposed as a useful machine learning technique to interpolate between previously calculated values and avoid running a full simulation to obtain a value for the liabilities. We propose methodologies utilizing neural networks for both the tasks of pricing as well as hedging four different varieties of variable annuity guarantees. We demonstrated a significant efficiency gain using neural networks in this manner. We also experimented with different error functions in the training of the neural networks and examined the resulting changes in network performance. Full article

By reinterpreting the calibration of structural models, a reassessment of the importance of the input variables is undertaken. The analysis shows that volatility is the key parameter to any calibration exercise, by several orders of magnitude. To maximize the sensitivity to volatility, a simple formulation of Merton’s model is proposed that employs deep out-of-the-money option implied volatilities. The methodology also eliminates the use of historic data to specify the default barrier, thereby leading to a full risk-neutral calibration. Subsequently, a new technique for identifying and hedging capital structure arbitrage opportunities is illustrated. The approach seeks to hedge the volatility risk, or vega, as opposed to the exposure from the underlying equity itself, or delta. The results question the efficacy of the common arbitrage strategy of only executing the delta hedge. Full article

On the condition that both futures and options exist in the markets for hedging, this paper examines the optimal hedging strategy under price risk and background risk. Compared with the previous research, which has studied options hedging against basis risk and production risk being extended to options and futures hedging against price risk and background risk, we proposed a model and have taken the budget of buying options into consideration. The model is fairly general and some existing models are special cases of it. We firstly derive the necessary and sufficient conditions that guarantee the optimality of an under-hedge, a full-hedge and an over-hedge of futures for the risk-averse utility. Then, sufficient conditions are stipulated under which an over-hedge is optimal. Furthermore, we propose a program minimizing of tail conditional expectation (TCE), which is inherently equivalent to the risk measure of expected shortfall risk (ES) or the conditional VaR (CVaR) under the continuous-time framework. Finally, we find that ES, in our proposed model, is significantly smaller than the one in the model of options hedging only. Therefore, the results emphasize the need for combining futures hedging and options hedging, and it also shows that imposing background risk, whether it be additive or multiplicative, always has a great impact on the hedging efficiency. We also present some sensitivities of the relevant parameters to provide some suggestions for the investors. Full article

We extend the analysis on hedging with price and output uncertainty by endogenizing the output decision. Specifically, we consider the joint determination of output and hedging in the case of flexibility in production. We show that the risk-averse firm always maintains a short position in the futures market when the futures price is actuarially fair. Moreover, in the context of an example, we show that the presence of production flexibility reduces the incentive to hedge for all risk averse agents. Full article