The Mediating Role of Affective States in Short-Term Effects of Activity Engagement on Working Memory in Older Age.

INTRODUCTION: It has been shown that activity engagement is associated with cognitive ability in older age, but mechanisms behind the associations have rarely been examined. Following a recent study which showed short-term effects of activity engagement on working memory performance appearing 6 h later, this study examined the mediating role of affective states in this process. METHODS: For 7 times per day over 2 weeks, 150 Swiss older adults (aged 65-91 years) reported their present (sociocognitive/passive leisure) activities and affective states (high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative) and completed an ambulatory working memory task on a smartphone. RESULTS: Multilevel vector autoregression models showed that passive leisure activities were associated with worse working memory performance 6 h later. Passive leisure activities were negatively associated with concurrent high-arousal positive affect (and high-arousal negative affect); high-arousal positive affect was negatively associated with working memory performance 6 h later. A Sobel test showed a significant mediation effect of high-arousal positive affect linking the time-lagged relationship between passive leisure activities and working memory. Additionally, sociocognitive activities were associated with better working memory performance 6 h later. Sociocognitive activities were associated with concurrent higher high- and low-arousal positive affect, which, however, were not associated with working memory performance 6 h later. Thus, a mediation related to sociocognitive activities was not found. DISCUSSION: Passive leisure activities could influence working memory performance through high-arousal positive affect within a timeframe of several hours. Results are discussed in relation to an emotional, and possibly a neuroendocrine, pathway explaining the time-lagged effects of affective states on working memory performance.

A Multi-market Comparison of the Intraday Lead-Lag Relations Among Stock Index-Based Spot, Futures and Options.

Using 1-min data, we explore the dynamic variation of the intraday lead-lag relations between stock indices and their derivatives through a comprehensive study with broader coverage of research objectives and methodologies. This paper provides explicit evidence that the futures and options exhibit price leadership over the spot market, and the options is ahead of the futures on most trading days in all three markets. This paper also reports a new finding that the relation between the derivative and its underlying index reverses when the index return has a significantly larger mean value, and the reversal phenomenon is also observed in the relations between the futures and the options, which enriches the empirical results of intraday lead-lag relations. Moreover, these conclusions still hold under the impact of extreme events, e.g., the outbreak of the Covid-19. Finally, we construct a pair trading strategy based on the intraday lead-lag relationships, which can get better performance than the corresponding spot index. Our findings can potentially help regulators understand the price discovery process between the index and its derivatives, and also be of great value for timely adjustment of investors intraday trading strategies.

Using Multi-Dimensional Dynamic Time Warping to Identify Time-Varying Lead-Lag Relationships.

This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series. Specifically, this manuscript contributes to the literature by improving upon the use towards lead-lag estimation. Our two-step procedure computes the multi-dimensional DTW alignment with the aid of shapeDTW and then utilises the output to extract the estimated time-varying lead-lag relationship between the original time series. Next, our extensive simulation study analyses the performance of the algorithm compared to the state-of-the-art methods Thermal Optimal Path (TOP), Symmetric Thermal Optimal Path (TOPS), Rolling Cross-Correlation (RCC), Dynamic Time Warping (DTW), and Derivative Dynamic Time Warping (DDTW). We observe a strong outperformance of the algorithm regarding efficiency, robustness, and feasibility.

Multiscale Price Lead-Lag Relationship between Steel Materials and Industry Chain Products Based on Network Analysis.

As two main steelmaking materials, iron ore and scrap steel have different price lead-lag relationships (PLRs) on midstream and downstream steel products in China. The relationships also differ as the time scale varies. In this study, we compare the price influences of two important steel materials on midstream and downstream steel products at different time scales. First, we utilize the maximal overlap discrete wavelet transform (MODWT) method to decompose the original steel materials and products price series into short-term, midterm, and long-term time scale series. Then, we introduce the cross-correlation and Podobnik test method to calculate and test the price lead-lag relationships (PLRs) between two steel materials and 16 steel products. Finally, we construct 12 price lead-lag relationship networks and choose network indicators to present the price influence of the two materials at different time scales. We find that first, most scrap steel and steel products prices fluctuate at the same time lag order, while iron ore leads most steel products price for one day. Second, products that exist in the downstream industry chain usually lead to iron ore. Third, as the time scale becomes longer, the lead relationships from steel materials to steel products become closer.

Local Lead-Lag Relationships and Nonlinear Granger Causality: An Empirical Analysis.

The Granger causality test is essential for detecting lead-lag relationships between time series. Traditionally, one uses a linear version of the test, essentially based on a linear time series regression, itself being based on autocorrelations and cross-correlations of the series. In the present paper, we employ a local Gaussian approach in an empirical investigation of lead-lag and causality relations. The study is carried out for monthly recorded financial indices for ten countries in Europe, North America, Asia and Australia. The local Gaussian approach makes it possible to examine lead-lag relations locally and separately in the tails and in the center of the return distributions of the series. It is shown that this results in a new and much more detailed picture of these relationships. Typically, the dependence is much stronger in the tails than in the center of the return distributions. It is shown that the ensuing nonlinear Granger causality tests may detect causality where traditional linear tests fail.

COVID-19 and the liquidity network.

We investigate the impact of the COVID-19 pandemic on liquidity interlinkages of US industry groups. We employ a lead-lag liquidity network method that allows us to analyse liquidity interrelationships beyond contemporaneous spillover effects. We document that sectors differ in their liquidity interactions during the pre-COVID period, with some sectors more interlinked than others. We also document that the crisis induced by COVID had a significant effect on the liquidity network, with all sectors becoming more interconnected relative to the pre-COVID period. The effect varies across industries, with the utilities sector being the most affected, and telecommunication services the least.

An Analysis of China's Onshore and Offshore Exchange Rates-Adjusted Thermal Optimal Path Approach Based on Pruning and Path Segmentation.

The study of the lead-lag relationship between the Hong Kong offshore Renminbi (CNH) spot market and onshore (CNY) spot market is of great importance for its wide application in market risk management. In this paper, we study the correlation between the CNH and CNY spot markets in the contexts of daily closing price change and the 2011-2016 Bid-Ask spread (BAS). We test the existence of causality relation between CNH/CNY pairwise change and BAS by using the conventional method of vector auto-regression (VAR) model in the observation period. Furthermore, we detect the local lead-lag dependence relationships between CNH/CNY pairwise change and BAS by using a non-parametric approach-adjusted Thermal Optimal Path (TOP) method. Through introducing a Pruning and Path segmentation algorithm, we address the problem of computation infeasibility that may be encountered in application of the existing TOP method for the detection of lead-lag relationship between two time series with long time duration. Theoretical analyses and simulation results are presented to verify validity of adjusted TOP method in the setting of big time-series data set. This study also provides some interesting findings: (1) the offshore CNH market is informationally integrated with the onshore CNY market from two aspects of closing price change over two consecutive single days and BAS used as a proxy for market liquidity; (2) Local dependency between the two markets changes with economic conditions changing, which would facilitate both investor and policy maker decision making.

Fluid Intelligence Predicts Change in Depressive Symptoms in Later Life: The Lothian Birth Cohort 1936.

We examined reciprocal, time-ordered associations between age-related changes in fluid intelligence and depressive symptoms. Participants were 1,091 community-dwelling older adults from the Lothian Birth Cohort 1936 study who were assessed repeatedly at 3-year intervals between the ages of 70 and 79 years. On average, fluid intelligence and depressive symptoms worsened with age. There was also a dynamic-coupling effect, in which low fluid intelligence at a given age predicted increasing depressive symptoms across the following 3-year interval, whereas the converse did not hold. Model comparisons showed that this coupling parameter significantly improved overall fit and had a correspondingly moderately strong effect size, accounting on average for an accumulated 0.9 standard-deviation increase in depressive symptoms, following lower cognitive performance, across the observed age range. Adjustment for sociodemographic and health-related covariates did not significantly attenuate this association. This implies that monitoring for cognitive decrements in later life may expedite interventions to reduce related increases in depression risk.

Right-ear precedence and vocal emotion contagion: The role of the left hemisphere.

Much evidence suggests that the processing of emotions is lateralized to the right hemisphere of the brain. However, under some circumstances the left hemisphere might play a role, particularly for positive emotions and emotional experiences. We explored whether emotion contagion was right-lateralized, lateralized valence-specifically, or potentially left-lateralized. In two experiments, right-handed female listeners rated to what extent emotionally intoned pseudo-sentences evoked target emotions in them. These sound stimuli had a 7 ms ear lead in the left or right channel, leading to stronger stimulation of the contralateral hemisphere. In both experiments, the results revealed that right ear lead stimuli received subtly but significantly higher evocation scores, suggesting a left hemisphere dominance for emotion contagion. A control experiment using an emotion identification task showed no effect of ear lead. The findings are discussed in relation to prior findings that have linked the processing of emotional prosody to left-hemisphere brain regions that regulate emotions, control orofacial musculature, are involved in affective empathy processing areas, or have an affinity for processing emotions socially. Future work is needed to eliminate alternative interpretations and understand the mechanisms involved. Our novel binaural asynchrony method may be useful in future work in auditory laterality.

Risks and interrelationships of subdistrict house prices: the case of Amsterdam.

This paper uses individual house transaction data from 1995 to 2014 in Amsterdam to explore the risks and interrelationships of the subdistrict house prices. Simple indicators suggest that house prices grow faster and are more risky in the central business district and its immediate surrounding areas than in the peripherals. Furthermore, we observe an over time decreasing intervariations between the subdistrict house price growth rates, whereas we find a lead-lag and house price causal flow from the more central to the peripheral subdistricts.

Control Design and Digital Implementation of a Fast 2-Degree-of-Freedom Translational Optical Image Stabilizer for Image Sensors in Mobile Camera Phones.

This study presents design, digital implementation and performance validation of a lead-lag controller for a 2-degree-of-freedom (DOF) translational optical image stabilizer (OIS) installed with a digital image sensor in mobile camera phones. Nowadays, OIS is an important feature of modern commercial mobile camera phones, which aims to mechanically reduce the image blur caused by hand shaking while shooting photos. The OIS developed in this study is able to move the imaging lens by actuating its voice coil motors (VCMs) at the required speed to the position that significantly compensates for imaging blurs by hand shaking. The compensation proposed is made possible by first establishing the exact, nonlinear equations of motion (EOMs) for the OIS, which is followed by designing a simple lead-lag controller based on established nonlinear EOMs for simple digital computation via a field-programmable gate array (FPGA) board in order to achieve fast response. Finally, experimental validation is conducted to show the favorable performance of the designed OIS; i.e., it is able to stabilize the lens holder to the desired position within 0.02 s, which is much less than previously reported times of around 0.1 s. Also, the resulting residual vibration is less than 2.2-2.5 µm, which is commensurate to the very small pixel size found in most of commercial image sensors; thus, significantly minimizing image blur caused by hand shaking.

Fast response of vegetation in East Asia to abrupt climatic events during the last deglaciation.

Climate changes had major impacts on the vegetation of East Asia during the last deglaciation. However, the rate and pattern of vegetation succession in response to large-scale climatic events during this interval are controversial. Here, we present well-dated decadal-resolution pollen records from annually laminated Maar Lake Xiaolongwan during the last deglaciation. The vegetation changes were rapid and near-synchronous with millennial-scale climatic events, including Greenland Stadial 2.1a (GS-2.1a), Greenland Interstadial 1 (GI-1), Greenland Stadial 1 (GS-1), and the early Holocene (EH). The vegetation responded in different ways to the different rates of climate change. Vegetation change was gradual [∼1 thousand years (kyr) response time] during the transition between GS-2.1a and GI-1, but it was faster (∼0.4 kyr response time) during the transitions between GI-1, GS-1, and the EH, resulting in different patterns of vegetation succession. Additionally, the amplitude and pattern of vegetation changes resembled those in the records of regional climate change based on long-chain n-alkanes δ13C and stalagmite δ18O, as well as in the mid-latitude Northern Hemisphere temperature record and the Greenland ice core δ18O record. Therefore, the rate and pattern of vegetation succession in the Changbai Mountain of Northeast Asia during the last deglaciation were sensitive to the characteristics of changes in the regional hydrothermal conditions and mid-latitude Northern Hemisphere temperature, which were linked to both high- and low-latitude atmospheric-oceanic dynamics. Overall, our findings reveal a close relationship between ecosystem succession and hydrothermal changes during these millennial-scale climatic events in East Asia during the last deglaciation.

Effect of process parameters and formulation properties on the lead-lag between in-line NIR tablet press feed frame and off-line NIR tablet measurements.

The use of in-line near-infrared (NIR) measurements for tablet potency monitoring and diversion was studied. First, the optimal sample size for in-line NIR measurements inside the feed chute and the dosing and filling chamber of the tablet press feed frame was determined to allow proper comparison between these different measurement positions. Because of the considerably longer measurement time needed to obtain the same sample size inside the feed chute compared to the feed frame, the possibility of powder segregation inside the feed chute and the additional powder mixing inside the feed frame, the latter is preferred over the feed chute for in-line blend potency monitoring. Next, a design of experiments (DoE) was performed to evaluate the effect of paddle speed, turret speed, overfill level and formulation properties upon the lead-lag and the time it takes before the powder blend that is expelled at the dosing station is measured by the NIR inside the dosing chamber. Lead-lag is defined as the difference in time and API concentration between the measured in-line NIR response inside the filling chamber of the feed frame and the off-line NIR tablet response. Paddle speed and turret speed were the only compression parameters affecting lead-lag. Lead-lag decreased with increasing paddle speed for the first formulation. For the second formulation, lead-lag decreased with decreasing paddle speed and/or increasing turret speed. Formulation properties did not have an effect on the lead-lag. The in-line NIR response inside the dosing chamber of the feed frame was found to be closely following the tablet NIR response. Therefore, the dosing chamber could be used as an additional in-line NIR position for tablet potency monitoring and diversion. It can provide an extra layer of confidence about the final tablet quality. To demonstrate this potential benefit of simultaneous in-line NIR measurements inside the filling and dosing chamber of the feed frame, a tableting experiment was performed where a surrogate API spike was introduced into the product stream to mimic a potential process disturbance. The in-line NIR measurements inside the filling chamber allow diverting tablets in-time when the blend potency crosses the predefined control limits. And because the NIR response inside the dosing chamber closely follows the tablet NIR response, tablet diversion can discontinue when the blend potency inside the dosing chamber is again within the control limits. This could increase the yield of the tableting process by avoiding a longer than needed wash-out period and rejecting tablets that meet the release limits.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center.

Introduction: Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices. Methods: Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony. Results: It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors. Discussion: These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Development of a tablet press feed frame lead lag determination model using in-line and off-line NIR measurements.

For continuous pharmaceutical manufacturing of oral solid dosages, it is essential that product quality is measured inline. In this application, a continuous rotary tablet press is used. The goal is a model-based assessment of the quality of the blend in the feed frame to determine whether the concentration of the active pharmaceutical ingredient (API) will be within the prescribed limits. This is to achieve a better quality assurance than by offline testing of a small sample of tablets. In this way, product quality for real-time release (RTR) could be implemented. With a near-infrared (NIR) probe, the concentration of the API in the feed chute and the feed-frame were measured, as well as the API concentration of the tablets by an offline NIR measurement. These different data sets are connected and used for the residence time distribution characterization of the mixing dynamic of the tablet press. A residence time distribution model is fitted to the data, and is further used to compute the lead-lag time. This yields information on how long it takes for a quantity of product to go from being measured in the feed frame until ending up in tablets. Further, it gives information on the occurrence of mixing in the feed-frame itself. These models allow making accurate predictions of whether tablets fall within specified concentration range in real-time. The real-time prediction can be used in combination with a control system both to maintain the quality of the blend as well as to know which tablets to discard. This real-time quality assurance will lead to less material waste and fewer declined batches of tablets.

Determination and understanding of lead-lag between in-line NIR tablet press feed frame and off-line NIR tablet measurements.

The influence of different tableting process parameters on lead-lag was studied by collecting in-line near-infrared (NIR) spectra in the filling chamber of the tablet press feed frame and off-line NIR tablet data. Lead-lag is defined as the difference in time and API concentration between the measured in-line feed frame NIR response and the off-line NIR tablet data. Lead-lag results from the product formulation blend undergoing additional mixing after passing the NIR probe inside the feed frame, before being filled into the dies of the tablet press. A design of experiments (DoE) was performed to evaluate the effect of the tableting process factors paddle speed, turret speed, overfill level, paddle speed ratio and feed frame type upon lead-lag. Paddle speed and turret speed were identified as the only tableting parameters affecting lead-lag. Lead-lag decreased with increasing paddle speed or turret speed and became negligible at high paddle speed and high turret speed. Overfill level, paddle speed ratio and feed frame type did not affect lead-lag, suggesting that the amount and the trajectory of the recirculating powder in the feed frame did not significantly vary and hence influence the lead-lag within the examined process factor ranges. Finally, a methodology was developed using the in-line feed frame NIR measurements for the continuous monitoring and control of blend potency and tablet content uniformity. Tablet diversion should start when the in-line feed frame monitored blend potency exceeds the predefined control limits and can discontinue when this blend potency is again within the control limits for a duration equal to the lead-lag time. A combination of continuous blend potency monitoring inside the feed frame and in-process tablet weight control allows real-time tablet content uniformity assurance. Although the findings of this study are restricted to the specific equipment, tableting parameter ranges and product formulation used, the suggested approach for lead-lag determination and continuous tablet content uniformity monitoring can be applied to any rotary tablet press and product formulation.

Dynamics lead-lag relationship of jumps among Chinese stock index and futures market during the Covid-19 epidemic.

This paper introduces thermal optimal path method to investigate the dynamics lead-lag relationship of jumps among Chinese stock index and futures market under the background of the Covid-19 epidemic. Based on three representative stock indexes and their index futures in China, we find the lead-lag structure changes significantly before and after the outbreak of COVID-19. Before the epidemic, there is mutual effect between different markets jumps. However, CSI 300 futures and SSE 50 futures significantly lead other markets for the after-epidemic period. For the volatility forecasting based on cross-market jumps, the lagged jumps of CSI 300 and SSE 50 index futures have significantly impacts on the volatility forecast of other markets.

Revisiting the relationship between spot and futures markets: evidence from commodity markets and NARDL framework.

This study aims to investigate the relationship between the spot and futures commodity markets. Considering the complexity of the relationship, we use a nonlinear autoregressive distributed lag (NARDL) framework that considers the asymmetry and nonlinearity in both the long and short run. Based on the daily returns of six commodity indices reaggregated on three commodity types, our study reaches some interesting findings. Our analysis highlights a bidirectional relationship between both markets over the short and long run, with a greater lead for the futures market. This result confirms the future market's dominant contribution to price discovery in commodities. Changes in commodity prices appear first in the futures market, as informed investors and speculators prefer trading on this market that is characterized by low costs and a high-leverage effect. Then, the information is transmitted from the futures to the spot market through arbitrageurs' activity, which explains the nonlinearity of the relationship. These results are helpful to scholars, investors and policymakers.

A robust dual interval type-2 fuzzy lead-lag based UPFC for stability enhancement using Harris Hawks Optimization.

A Harris Hawks Optimization (HHO)tuned dual interval type-2 fuzzy lead-lag (Dual-IT2FLL) based unified power flow controller (UPFC) is proposed to minimize oscillations in single and multimachine power systems. The proposed damping controller coordinates between the modulation index (MI) and phase angle of series and shunt converters of UPFC simultaneously and is designed using speed deviation, a remote input signal for stability improvement. The performance of the proposed controller is verified through nonlinear time and frequency domain simulations under different operating conditions. The graphical simulations and validations using OPAL-RT OP5600 are presented to access the stability performance. Comparison based on different performance indices (PIs), like mean, standard deviation, overshoots and settling time are also considered to prove the better performance of the proposed HHO tuned dual-IT2FLL based UPFC over others under different operating conditions.

COVID-19, stock market and sectoral contagion in US: a time-frequency analysis.

We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.