Positive Effect Research Articles

Positive-Definite Converging Kernel Estimation of Long-Run Variance

Kernel estimators have been popular for decades in long-run variance estimation. To minimize the loss of efficiency measured by the mean-squared error in important aspects of kernel estimation, we propose a novel class of converging kernel estimators with three major properties: (a) the optimal bandwidth choice is model-free; (b) positive-definiteness is ensured through a principle-driven aggregation technique with no loss of theoretical efficiency; and (c) potentially misspecified prewhitening models and transformations of the time series do not harm the asymptotic efficiency. A shrinkage prewhitening transformation is proposed for more robust finite-sample performance. The estimator has a positive bias that diminishes with the sample size so that it is more conservative compared with the typically negatively biased classical estimators. The proposal improves upon standard kernel functions and can be well generalized to the multivariate case. We discuss its performance through simulation results and a real-data application in the forecast breakdown test.

Non-invasive [15O]H2O PET measurements of cerebral perfusion and cerebrovascular reactivity using an additional heart scan.

Obtaining the arterial input function (AIF) is essential for quantitative regional cerebral perfusion (rCBF) measurements using [15O]H2O PET. However, arterial blood sampling is invasive and complicates the scanning procedure. We propose a new non-invasive dual scan technique with an image derived input function (IDIF) from an additional heart scan. Six patients and two healthy subjects underwent [15O]H2O PET imaging of 1) heart and brain during baseline, and 2) heart and brain after infusion of acetazolamide. The IDIF was extracted from the left ventricle of the heart and compared to the AIF. The rCBF was compared for six bilateral cortical regions. AIFs and IDIFs showed strong agreement. rCBF with AIF and IDIF showed strong correlation for both baseline rCBF (R2 = 0.99, slope = 0.89 CI: [0.87; 0.91], p < 0.0001) and acetazolamide rCBF (R2 = 0.98, slope = 0.93, CI:[0.90;0.97], p < 0.0001) but showed a positive bias of 0.047 mL/(g·min) [-0.025; +0.119] for baseline and 0.024 [-1.04, +1.53] mL/(g·min) for acetazolamide. In conclusion, the invasive arterial cannulation can be replaced by an additional scan of the heart with a minor bias of rCBF estimation. The method is applicable to all scanner systems.

Textual sentiment classification in tourism research: between manual computing model and machine learning

ABSTRACT Contemporary tourism scholars increasingly embrace artificial intelligent technologies, such as machine learning algorithms, for sentiment analysis. This paper presents a counterargument by introducing the Tourist Sentiment Evaluation (TSE) model through manual computing algorithms. By a comparative experiment involving six machine learning models and the TSE model, this paper demonstrates that the TSE can outperform the selected machine learning approaches. The test relies on a mixed dataset, comprising 244,974 online reviews and multi-year questionnaire surveys from eight tourism destinations in China. This paper concludes that the manual computing approach retains distinctive advantages over AI approaches, due to the accuracy, explanatory and recursive applicability. Secondly, online score ratings are unreliable because they do not match actual reviews. Thirdly, this paper confirms the existence of social positive bias in the tourism context, known as the Pollyanna effect, where tourists exhibit a propensity to use positive words six times more frequently than negative words. This paper provides a counterargument to the prevailing tendency to adopt AI technologies in various domains, affirming the solid reliability of manual computation. Additionally, the utilisation of the TSE model holds significant potential for overcoming linguistic barriers by converting vast amounts of Chinese texts into quantified sentiment scores.

Aggregating flood damage functions: The peril of Jensen's gap

AbstractFlood risk models provide important information for disaster planning through estimating flood damage to exposed assets, such as houses. At large scales, computational constraints or data coarseness often lead modelers to aggregate asset data using a single statistic (e.g., the mean) prior to applying non‐linear damage functions. This practice of aggregating inputs to nonlinear functions introduces error and is known as Jensen's inequality; however, the impact of this practice on flood risk models has so far not been investigated. With a Germany‐wide approach, we isolate and compute the error resulting from aggregating four typical concave damage functions under 12 scenarios for flood magnitude and aggregation size. In line with Jensen's 1906 proof, all scenarios result in an overestimate, with the most extreme scenario of a 1 km aggregation for the 500‐year flood risk map yielding a country‐wide average bias of 1.19. Further, we show this bias varies across regions, with one region yielding a bias of 1.58 for this scenario. This work applies Jensen's 1906 proof in a new context to demonstrate that all flood damage models with concave functions will introduce a positive bias when aggregating and that this bias can be significant.

Valence-based biases in collective temporal thought: The role of question framing, culture, and age.

Collective temporal thought includes individuals' memories of group experiences and expectations about the group's collective future. Prior studies have found inconsistent valence biases (e.g., positivity) in North American collective memory and consistently negative biases in collective future thought. Discrepancies in collective memory valence biases may be due to different question framing across studies. Moreover, a limited number of studies extend collective temporal thought research beyond Western nations and few studies examine potential age-related differences in this area. Therefore, the present study investigates valence-based biases in collective temporal thought from the perspective of question framing, culture, and participant age. Participants (N = 1,548) included younger (20-39 years) and older (60+ years) adults from the USA and mainland China. Whereas Americans' collective memory biases varied across question framings, Chinese participants consistently displayed positivity biases. The American bias patterns were specific to collective memory and did not carry over to collective future thought ratings. Chinese participants showed higher dialectical thinking than American participants and dialectical thinking positively correlated with the proportion of positive events reported. Older adults generated significantly more positive events than younger adults, more so in collective memory than in collective future thought. Overall, collective temporal thinking is influenced by question framing, cultural context, and participant age.

Improving the Thermal Stability of Indium Oxide n-Type Field-Effect Transistors by Enhancing Crystallinity through Ultrahigh-Temperature Rapid Thermal Annealing.

Ultrathin indium oxide films show great potential as channel materials of complementary metal oxide semiconductor back-end-of-line transistors due to their high carrier mobility, smooth surface, and low leakage current. However, it has severe thermal stability problems (unstable and negative threshold voltage shifts at high temperatures). In this paper, we clarified how the improved crystallinity of indium oxide by using ultrahigh-temperature rapid thermal O2 annealing could reduce donor-like defects and suppress thermal-induced defects, drastically enhancing thermal stability. Not only does more crystalline indium oxide depict the high stability of threshold voltage in stringent high-temperature test environments and under positive bias, but it also shows much less degradation under forming gas annealing than as-deposited transistors. Furthermore, we also successfully solved the channel length-dependent threshold voltage problem, which is often observed in oxide transistors, by suppressing defects induced by the metal deposition process and metal doping.

Evaluation of Siemens Atellica AMH assay and comparison with Roche, Beckman and Ansh Labs.

Anti-Müllerian hormone (AMH) is an important marker for ovarian reserve and response to fertility treatments. However, interassay variability exists due to the lack of a standardized method. This study evaluates the performance of the new Siemens Healthineers Atellica IM AMH assay against established assays (Beckman DxI 600 Access, Roche cobas Elecsys® e801, and Ansh Labs AMH ELISA). We measured AMH concentrations in 120 residual serum samples from patients presenting for routine AMH testing using all four assays. Passing-Bablok regression and Bland-Altman method were used for data analysis. The Siemens Healthineers Atellica IM assay demonstrated strong correlation with Beckman DxI (slope: 1.07, R2: 0.9881) but showed a minimal positive bias. Conversely, the Roche cobas Elecsys® e801 assay exhibited a negative bias compared to Beckman DxI (slope: 0.74, R2: 0.9696), while the Ansh Labs assay demonstrated a significant positive bias with increasing variability at higher AMH concentrations. Overall, the Siemens Healthineers Atellica IM assay shows promise as an alternative method for AMH measurement, demonstrating good correlation with established assays. However, differences were observed between all assays, highlighting the importance of assay-specific interpretation for accurate clinical assessment.

Mobility and stability improvements through in-situ AlOx passivation on extremely thin 2 nm-thick InOx back-gate FETs

Abstract The effectiveness of in-situ AlOx passivation on mobility and stability improvement in 2-nm-thick InOx FETs is comprehensively investigated at atomic layer deposition (ALD) temperature ranging from 100oC to 200oC. The chemical state of extremely thin InOx channels are significantly changed by the in-situ AlOx passivation. As a result, AlOx/InOx FETs show superior overdrive current and hysteresis characteristic than those of InOx FETs fabricated at the same ALD temperature. It is also found that a AlOx passivation layer formed at 200oC results in a stronger reduction of InOx, leading to a mobility enhancement of 1.8 against AlOx/InOx FET fabricated at 100oC thanks to an increase of oxygen vacancies and resultant enhanced hopping conduction. For bias stability analysis, amount of hydrogen-induced trapping site within both AlOx and InOx layer is reduced at a higher ALD temperature, resulting in the improvement of both positive and negative bias stress stability.

DC field-biased multibit/analog artificial synapse featuring an additional degree of freedom for performance tuning.

Multibit/analog artificial synapses are in demand for neuromorphic computing systems. A problem hindering the utilization of memristive artificial synapses in commercial neuromorphic systems is the rigidity of their functional parameters, plasticity in particular. Here, we report fabricating polycrystalline rutile-based memristive memory segments with Ti/poly-TiO2/Ti structures featuring multibit/analog storage and the first use of a tunable DC-biasing for synaptic plasticity adjustment from short- to long-term. The unbiased device is of short-term plasticity, positive biasing increases the remanence of the recorded events and the device gains long-term plasticity at a specific biasing level determined from the device geometry. The adjustability of the biasing field provides an additional degree of freedom allowing performance tuning; the paired-pulse facilitation index of the device is tuned by the biasing level adjustment providing further functional versatility. An appropriately biased segment provides more than 10 synaptic weight levels linearly depending on the number and duration of the stimulating spikes. The relationship with spike magnitude is exponential. The experimentally determined nonlinearity coefficient of the biased device for 50 potentiating spikes is comparable to the best published data. The spike-timing-dependent plasticity determined experimentally for the biased device in its long-term plasticity mode fits the mathematical relationship developed for biological synapses. Fabricated on a titanium metal foil, the produced memristors are sturdy and flexible making them suitable for wearable and implantable intelligent electronics. Our findings are anticipated to raise the potential of forming artificial synapses out of polycrystalline metal oxide thin films.

Evaluating and Improving Snow in the National Water Model, Using Observations from the New York State Mesonet

Abstract This study leverages observations from the New York State Mesonet to evaluate and improve the representation of snow within the National Water Model (NWM) and its associated land surface model (Noah-MP). To do so, we run and analyze distributed NWM simulations, forced by gridded meteorological analyses, and Noah-MP point simulations, forced by New York State Mesonet (NYSM) observations. Distributed NWM runs, with a baseline configuration, show substantial SWE biases caused by biases in the meteorological forcing used, imperfect representation of snow processes, and mismatches between the land cover in the model and at NYSM station locations. Noah-MP point simulations, using the baseline configuration, reveal a systematic positive bias in SWE accumulation. Sensitivity experiments show that this bias can be mitigated by using an alternative precipitation phase partitioning method. Noah-MP point simulations, with improved precipitation phase partitioning, reveal a systematic negative bias in SWE ablation rates. Sensitivity experiments highlight uncertain parameters within Noah-MP that strongly affect ablation rates and show particularly large sensitivity to the snow albedo decay time-scale (TAU0) parameter, which modulates snow albedo decay rates. Reducing TAU0 improves ablation rates by reducing biases in surface albedo. Distributed NWM experiments, with precipitation phase partitioning and TAU0 adjusted based on Noah-MP point simulation results, show qualitatively similar sensitivities. However, the distributed experiments do not show clear improvements when compared to SWE and streamflow observations. This is likely due to some combination of the abovementioned sources of bias in the baseline-distributed run and (for streamflow) biases in other parameterized processes unrelated to snow in the NWM. Significance Statement Simulating snow on the ground is important for forecasting streamflow. This study compares snow simulations from a streamflow forecast model to observations from an advanced weather station network. Errors in simulated snow are caused by errors in the weather inputs to the model and errors in how the model represents complex physical processes. Some of these errors can be reduced by changing how the model classifies rain versus snow and how the model determines how much sunlight snow reflects. However, using these results to improve the forecast model is tricky, due to errors in the weather data inputs, errors in the representation of other complex processes, and differences between vegetation assumed in the model and that at the weather station locations.

Cognitive factors as mediators of the relationship between childhood trauma and depression symptoms: the mediating roles of cognitive overgeneralisation, rumination, and social problem-solving

ABSTRACT Background: Childhood trauma has negative immediate and long-term impacts on depression. Questions remain, however, regarding the cognitive factors influencing this relationship. This study aimed to investigate the role of three cognitive factors – cognitive overgeneralisation, rumination and social problem-solving – as mediating factors in the relationship between childhood trauma and symptoms of depression. Methods: We conducted a cross-sectional study in Iran from March to July 2023. Participants (N = 227; Mean age 32.44 ± 8.95 years) with depression completed measures of childhood trauma, depression, self-overgeneralisation, cognitive errors, memory specificity, rumination and social problem-solving. The conceptual model was assessed using structural equation modelling. Results: Structural equation modelling indicated that childhood trauma had a positive direct effect on depression symptoms. Childhood trauma had a positive indirect effect on depression symptoms through both self-overgeneralisation and rumination and a negative indirect effect on depression through effective social problem-solving strategies. Conclusions: The findings suggest increased exposure to childhood trauma may be associated with elevated depression and self-overgeneralisation, rumination, and effective social problem-solving strategies may play an important role in this relationship. These findings hold potential implications for those working with patients with depression and a history of childhood trauma.

Study on interface characteristics of n-heptane spray in sub/supercritical conditions

ABSTRACT With the increasing temperature and pressure in the cylinder of the diesel engine, the in-cylinder environment gradually exceeded the thermodynamic critical point of hydrocarbon fuel. Compared with subcritical spray, the phase transformation mechanism of supercritical spray is essentially changed. In this paper, the n-heptane fuel sprays in three conditions case 1 (T1 = 400 K P1 = 2 MPa), case 2 (T2 = 600 K P2 = 2 MPa), and case 3 (T3 = 800 K P3 = 6 MPa) were obtained by high-speed digital schlieren method on the test platform of a constant volume combustion bomb. The spray liquid phase, liquid–gas mixed layer, and mixture were divided, and the variation rules of the spray cone angle, the liquid phase length, maximum interface thickness, and liquid–gas mixed layer area were discussed. The results showed that the higher the ambient temperature and pressure, the more severe the fragmentation of the spray. Compared with the subcritical condition, the spray penetration distance in the supercritical condition tended to be flat faster. Compared with 400 K, 2 MPa condition, the spray cone angle was about 33° and 50% larger at 800 K, 6 MPa condition. The liquid core area at 800 K, 6 MPa condition was 60 cm2, reduced by 75% compared with 400 K, 2 MPa condition, resulting in better spray diffusion and mixing with atmospheric gas. The sensitivity analysis of ambient temperature and pressure on spray characteristic parameters shows that temperature has a greater impact on the interface mixing layer area (VIP = 1.23), and pressure has a greater on penetration distance and spray penetration rate (VIP = 1.23). When the environmental conditions exceed the thermodynamic critical point, the area of the liquid–gas mixed layer increases due to the transformation of spray from evaporation to diffusion and the phenomenon of interfacial layer enrichment. In summary, the supercritical condition promotes the mixing of spray and environment and has a positive effect on spray diffusion and atomization.

Improving the acidification kinetics, structural and sensory properties of low-fat yoghurt using high-pressure homogenization treatment

In this study, the impact of high pressure homogenization at 50, 100 and 150 MPa, on the physicochemical, rheological, textural, microstructural, and sensory properties as well as acidification kinetics of low-fat yoghurt was investigated. The results showed that a shorter fermentation time was obtained for yoghurt samples produced from high-pressure homogenized milk compared to the control sample. Homogenization of milk at high pressures resulted in an increase in the water holding capacity from 42.83 to 52.67 % and firmness from 1.01 to 1.45 N of yoghurt samples. The viscosity (Ƞ50) of yoghurt increased up to 0.446 Pa.s by milk homogenization and all yoghurt samples showed shear thinning behaviour. Microstructural analyses revealed that control sample had a typical open porous gel network of casein, while fewer porous and more dense protein network was observed in yoghurts from high pressure homogenized milk. The positive effect of the milk homogenization treatment on the sensory properties of yoghurts was observed as well. Principal component analysis visualized the effect of high pressure homogenization treatment and confirmed the close relationship between structural properties and overall acceptability. Among the tested low-fat yoghurts, high pressure milk homogenization at 150 MPa had the greatest potential for improving yoghurt structure, whereas 100 MPa pressure imparted the most acceptable sensorial properties.

UNDERSTANDING RACIAL BIAS AWARENESS ACROSS ADULTHOOD: THEMES OF BIAS, JUSTIFICATIONS, AND EMOTIONS

Abstract This project employed a mixed-methods approach to analyze how age-diverse White Americans (N = 345; age range: 19 to 85) make meaning of specific instances of personal racial bias. Across three data collections, that targeted younger, middle-aged, and older adults, we asked participants to write about a time when they were racially biased. In the samples, 98% of younger adults, 91% of middle-aged adults, and 86% of older adults indicated specific instances of racial bias, and many indicated antiblack bias. Age-diverse adults frequently assumed that racial out-group members were criminal or deviant or assumed that those individuals had an undesirable culture. The participants also often indicated numerous justifications and emotions about their bias. For example, common justifications across all ages included perceived threat or the ambiguity of the situation. Specific emotions and justifications only differed moderately by age. Our findings indicate that while age-diverse White adults may make meaning of their bias in different ways, they tend to do so with self-conscious emotions and bias justifications that do not mitigate bias. Critically, middle-aged and older adults were less likely to indicate emotions at all in their reports. These findings may reflect a positivity bias among older adults who are less willing to highlight or remember their negative emotions or it may speak to the possibility that they may feel less fear in intergroup settings. The current work offers insights into more personalized approaches to bias regulation by integrating specific bias contexts with bias justifications and emotional awareness.

Advanced geospatial analytics for evapotranspiration dynamics: Integration of Sentinel-1A and FAO Penman-Monteith method

Evapotranspiration (ET0) is vital for agriculture and environmental management, facing challenges from climate change. Optical remote sensing overcomes reliance on weather station data. The modeled ET0 using the FAO Penman-Monteith method and Partial Least Squares Regression on Sentinel-1A data with 2016-2017 meteorological archives. Comparative analyses revealed stability in transportation areas within deciduous forests and wetlands, contrasting temporal variations. ET0 was significantly influenced by relative humidity (RH) (70.80% to 89.89%), with temperature (T) playing a crucial role. Urban vegetated areas maintained stable T values (29.37°C), while forests exhibited dynamic T variations (24.24°C to 28.94°C). VH polarization captured diverse climatic influences, resulting in a broader range of dynamic ET0 values (7.38 to 10.76 mm/day) compared to VV polarization (6.74 to 9.34 mm/day). VH sensor performance varied; in October 2016 showed moderate accuracy R2 was 0.50 with slight underestimation Bias -0.08, while exceptional accuracy was seen in December 2017 R2 was 1.00 with positive bias (0.57) and excellent agreement KGE was 0.92. VV sensors in October 2016 had a firm fit R2 was 0.55, with moderate underestimation Bias -0.87, and in December 2017 displayed a good fit the R2 was 0.57, with slight overestimation Bias 0.44, and good agreement KGE 0.44. Integrating machine learning and satellite imagery enhances ET0 accuracy for real-time monitoring in adaptive management, addressing climate change, and showcasing sensor-specific variations. Future research should integrate multi-source synthetic aperture radar satellite data and machine learning for precise ET0 estimation in adaptive environmental management.

Photo survey estimates of annual recruitment in eastern North American sea duck populations

AbstractSea duck (tribe mergini) populations have experienced significant declines in recent years, though underlying causes are poorly understood. Information on population demographic parameters may provide insight for wildlife managers seeking to maintain sustainable harvest. However, population monitoring capacity for sea ducks is limited relative to other waterfowl species because of their remote breeding distribution. The United States Fish and Wildlife Service organizes a Parts Collection Survey (PCS), which estimates recruitment in sea duck populations using age ratios (juveniles/adult), though estimates are biased because harvest vulnerability differs between age cohorts. We used a photo survey to calculate estimates of annual recruitment for long‐tailed duck (Clangula hyemalis), black scoter (Melanitta americana), surf scoter (M. perspicillata), and white‐winged scoter (M. deglandi; hereafter sea ducks) populations in eastern North America. Our team of surveyors collected photos of flighted sea ducks from shore and by boat in 11 states and 1 province from 15 October–15 December annually in 2019–2022. We classified photographed birds according to age and sex and calculated juvenile proportions of each species using a Bayesian binomial model. To compare photo survey estimates with PCS estimates, we used a paired t‐test organized by year. We found strong evidence that PCS estimates of juvenile proportions were greater than photo survey estimates for 3 sea duck species, indicating a consistent positive bias in PCS driven by harvest vulnerability. We also derived novel estimates of juvenile harvest vulnerability using the mean difference between within‐year estimates. Our work demonstrated the photo survey methodology produced annual recruitment estimates for 4 poorly monitored waterfowl populations with greater sample sizes and reduced systematic biases relative to existing methods; we recommend managers continue to adopt this approach in future years with additional consideration given for spatial representation and refinement of image classification procedures for long‐tailed duck estimates.

Impact of gate bias on TID responses of BCD MOSFETs

The total ionizing dose (TID) effect on MOSFETs, which use the Bipolar-CMOS-DMOS (BCD) technology, is investigated under different gate biases utilizing X-rays. The threshold voltage, maximum transconductance and subthreshold swing of the device before and after irradiation were obtained. The results indicate that the TID effect is significantly influenced by gate bias. For NMOSFET, the maximum threshold voltage shift occurs at a positive gate bias of 3 V. For PMOSFET, the minimum threshold voltage shift occurs at a negative gate bias of −3 V. The mechanism was revealed to be the result of the combined effects of initial recombination, hole capture, and electron tunneling processes. However, the case of PMOSFET differs from NMOSFET due to the disappearance of electron tunneling and the change in the direction of hole movement under negative gate bias.

Bias Tunable SnS2/ReSe2 Tunneling Photodetector with High Responsivity and Fast Response Speed.

2D photodetectors operating in photovoltaic mode exhibit a trade-off between response speed and photoresponsivity. This work presents a phototransistor based on SnS2/ReSe2 heterojunction. Under negative bias, the energy band spike at the heterojunction interface impedes the carrier drifting so that the dark current is as low as 10-13A. The tunneling under positive bias significantly reduces the transmission time of photogenerated carriers, which enhances the responsivity and specific detectivity to 32.77AW-1 and 5.77×1011Jones, respectively. Under reverse bias, the enhanced built-in electric field strengthens the rapid separation of photogenerated carriers, which elevates a response speed to 10.5/24.1µs and a 3dB bandwidth to 54.8kHz. The device also exhibits a broad spectral detection capability, extending from the near-ultraviolet to the near-infrared. Furthermore, this work also executed high-quality ASCII communication and high-resolution broadband single-pixel imaging, which demonstrates great promise for incorporation into future broadband optoelectronic systems.

The effects of feedback and task accuracy in serial dependence to orientation.

Assimilative serial dependence in perception occurs where responses about a stimulus (e.g., orientation) are biased towards previously seen perceptual information (e.g., the orientation of the stimulus shown on the previous trial). This bias may occur to perceptual information from the previous trial, or to the response or decision made on the previous trial. We asked whether providing response feedback could change the serial dependence effect on the following trial. Twenty-one participants completed a task in which they adjusted an on-screen pointer to reproduce the orientation of a briefly-presented Gabor stimulus. They received feedback about the accuracy of their response that either reflected their actual accuracy or was random. We found significant positive biases to the stimulus and response only when the participant had received positive ("correct!") feedback on that trial. When the inducer response had been incorrect, the effect was significant only to the response itself and not to the stimulus. Overall, we suggest that our participants demonstrated a bias towards the percept from the previous trial, which is better represented by the response than the stimulus for incorrect trials, and that this effect can be modulated post-perceptually by feedback.

Resting-state functional network segregation of the default mode network predicts valence bias across the lifespan

Abstract The brain is organized into intrinsically connected functional networks that can be reliably identified during resting-state functional magnetic resonance imaging (fMRI). Healthy aging is marked by decreased network segregation, which is linked to worse cognitive functioning, but aging-related changes in emotion are less well characterized. Valence bias, which represents the tendency to interpret emotionally ambiguous information as positive or negative, is more positive in older than younger adults and is associated with differences in task-based fMRI activation in the amygdala, prefrontal cortex, and a cingulo-opercular (CO) network. Here, we examined valence bias, age, and resting-state network segregation of 12 brain networks in a sample of 221 healthy individuals from 6 to 80 years old. Resting-state network segregation decreased linearly with increasing age, extending prior reports of de-differentiation across the lifespan. Critically, a more positive valence bias was related to lower segregation of the default mode network (DMN), due to stronger functional connectivity of the DMN with CO and, to a lesser extent, the ventral attention network (VAN) in all participants. In contrast to this overall segregation effect, in participants over 39 years old (who tend to show a positive valence bias), bias was also related to weaker connectivity between the DMN and Reward networks. The present findings indicate that specific interactions between the DMN, a task control network (CO), an emotion processing network (Reward), and, to a weaker extent, an attention network (VAN), support a more positive valence bias, perhaps through regulatory control of self-referential processing and reduced emotional reactivity in aging. The current work offers further insight into the functional brain network alterations that may contribute to affective well-being and dysfunction across the lifespan.