Positive Effect Research Articles

Eltrombopag-Induced Falsely Elevated Bilirubin Concentrations in Enzymatic and Vanadate Oxidation Assays: Involvement of High Serum Eltrombopag Concentrations

Background: The administration of eltrombopag, used to restore low blood count, demonstrates a positive interference of blood bilirubin levels when analyzed through the diazo assay. However, research on bilirubin measurements using other methods is limited. Therefore, using an enzymatic assay, this study aimed to investigate the effect of serum eltrombopag on bilirubin measurements in patients with aplastic anemia. It further assessed the concentration-dependent effect of eltrombopag on bilirubin measurements using enzymatic and vanadate oxidation assays. Methods: Total and conjugated bilirubin concentrations measured using an enzymatic assay and serum eltrombopag concentrations were examined in 227 serum samples collected from 30 patients with aplastic anemia receiving eltrombopag. Eltrombopag-spiked samples were analyzed using the enzymatic and vanadate oxidation assays for total and conjugated bilirubin to determine its concentration-dependent effects. Results: A strong positive correlation was observed between total bilirubin and serum eltrombopag concentrations in patients receiving eltrombopag (r = 0.820). However, the correlation between conjugated bilirubin and serum eltrombopag concentrations was weaker (r = 0.413). In eltrombopag-spiked serum samples, the enzymatic assay showed significant false elevation of total bilirubin concentrations at ≥6.0 mcg/mL; no interference with conjugated bilirubin measurements was observed. The vanadate oxidation assay showed mild positive biases of 0.2 and 0.1 mg/dL for total and conjugated bilirubin concentrations, respectively, at a high eltrombopag concentration (50 mcg/mL). Conclusions: Eltrombopag causes clinically significant concentration-dependent interference in total blood bilirubin, but not in conjugated bilirubin measurements through the enzymatic assay in patients with aplastic anemia. The vanadate oxidation assay may be used as an alternative to measure total blood bilirubin when the eltrombopag concentration is below 50 mcg/mL.

Plasmonic Light Emission by Inelastic Charge Transport in Ultrathin Zinc Oxide/Metal Heterostructures.

Controlling light emission from plasmonic nanojunctions is crucial for developing tunable nanoscale light sources and integrated photonic applications. It requires precise engineering of plasmonic nanocavity electrodes and a detailed understanding of electrically driven light emission. Using scanning tunneling microscopy-induced luminescence (STML), we studied plasmonic light emission from ultrathin ZnO/Ag(111) inside a silver nanocavity. At positive bias, plasmonic luminescence, caused by radiative decay of localized surface plasmons (LSP), is spectrally low-pass filtered by the ZnO layers. The emission of photon energies above the conduction band edge energy (ECB) of ZnO is suppressed, while the spectral distribution below ECB resembles the LSP resonance on Ag(111). This spectral filtering is absent at negative bias and depends on the local electronic structure, as confirmed by spatial STML mapping. Our findings demonstrate that the ZnO conduction band serves as the initial state for plasmonic luminescence driven by inelastic electron transport across the ZnO/Ag(111) interface.

Effect of active layer thickness on device performance of InSnZnO thin-film transistors grown by atomic layer deposition.

Amorphous oxide semiconductors have garnered significant attention in recent years for their potential in flat-panel displays and back-end-of-line-compatible monolithic 3D (M3D) integration applications. This study explores amorphous InSnZnO thin films deposited via plasma-enhanced atomic layer deposition (PEALD) and the development of high-performance PEALD ITZO thin-film transistors (TFTs) with different active layer thicknesses, fabricated under a low thermal budget of 200 °C. By optimizing the deposition process of binary oxides InOx, SnOx, and ZnOx, a shared temperature window of 170-180 °C was identified for ITZO thin-film deposition. The deposited ITZO films, irrespective of thickness, exhibit an amorphous phase. Moreover, a reduction in ITZO film thickness from 24 to 4.8nm leads to an increase in the optical bandgap from 3.35 to 3.65eV. The channel thickness significantly impacts the threshold voltage and carrier density of ITZO TFTs. Optimized ITZO TFTs with a 16nm channel thickness demonstrate excellent electrical performance, including a threshold voltage of -0.58V, a field-effect mobility of 29cm2/V s, an on/off ratio exceeding 108, and a subthreshold swing of 74 mV/dec. Furthermore, the optimized ITZO TFT exhibits excellent stability under positive bias stress at 2 MV/cm, with a threshold voltage shift of 0.15V after 3600s. Consequently, ALD-based ITZO emerges as a promising channel material for future applications in transparent electronics and flat-panel displays.

Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path

Abstract. The response in cloud water content to changes in cloud condensation nuclei remains one of the major uncertainties in determining how aerosols can perturb cloud properties. In this study, we used an ensemble of large eddy simulations of marine stratocumulus clouds to investigate the correlation between cloud liquid water path (LWP) and the amount of cloud condensation nuclei. We compare this correlation directly from the model to the correlation derived using equations which are used to retrieve liquid water path from satellite observations. Our comparison shows that spatial variability in cloud properties and instrumental noise in satellite retrievals of cloud optical depth and cloud effective radii results in bias in the satellite-derived liquid water path. In-depth investigation of high-resolution model data shows that in large part of a cloud, the assumption of adiabaticity does not hold, which results in a similar bias in the LWP–CDNC (cloud droplet number concentration) relationship as seen in satellite data. In addition, our analysis shows a significant positive bias of between 18 % and 40 % in satellite-derived cloud droplet number concentration. However, for the individual ensemble members, the correlation between the cloud condensation nuclei and the mean of the liquid water path was very similar between the methods. This suggests that if cloud cases are carefully chosen for similar meteorological conditions and it is ensured that cloud condensation nuclei concentrations are well-defined, changes in liquid water can be confidently determined using satellite data.

Eyes on the body: Assessing attentional bias toward body-related stimuli in Anorexia Nervosa.

The aim of the present study was to assess whether patients with Anorexia Nervosa (AN) presented an attentional bias toward pictures of other women's bodies, as this bias could implicitly promote self-other comparisons thus increasing body/weight concerns. The sample included 48 healthy controls (HC) and 54 patients with AN. All participants performed a dot-probe task with pictures of bodies or body parts of underweight (UWB), normal weight (NWB) and overweight (OWB) women, while their gaze was recorded with an eye-tracking system. Two indices of attentional bias, a gaze direction bias and a gaze duration bias were extracted. The models conducted on both direction bias and duration bias showed a significant main effect of group, revealing a stronger attentional bias toward bodies in patients as compared to controls. One sample t-tests conducted on the direction bias of patients with AN revealed that they presented a significant positive bias at 500 ms toward all the bodies. At 1500 ms, instead, they presented a positive bias toward UWB and an avoidance bias of OWB. HC instead presented an initial avoidance of all body stimuli, and an avoidance of NWB and OWB at 1500 ms. Our results revealed a stronger attentional bias toward other women's bodies in patients than in HC. Moreover, patients presented a tendency to focalize their attention on UWB while they avoided maintaining their attention on OWB. This pattern might promote upward social comparisons, which are usually associated with negative self-evaluation and increased levels of body dissatisfaction.

Modifiable Psychological Mechanisms of Resilience Among UK Trainee and Newly Qualified Teachers.

Teaching is identified as a stressful occupation, with elevated levels of burnout among the profession. Research suggests that resilience may buffer against stress and psychological distress and potentially be a useful resource for this occupational group. This research aimed to identify mechanisms associated with trainee teachers' resilience across time. Using the cognitive model of resilience, we examined interpretation bias and emotion regulation as cognitive mechanisms associated with resilience. The study investigated whether these cognitive processes have an association with trainee teachers' resilience during teacher training and in the first year as teachers in two 1-year longitudinal online studies. Study 1 commenced before COVID-19 pandemic (September 2019), but ended during ongoing pandemic-related restrictions. Study 2 was conducted as a replication study, commenced during COVID-19 (May 2020). Resilience, short-term stress, chronic perceived stress, and cognitive mechanisms (interpretation bias, emotion regulation) were assessed at baseline (during teacher training), with resilience and short-term stress monitored at the 8-month and 13-month follow-ups. Across both studies, cross-sectional and longitudinal relationships were found between perceived stress, cognitive mechanisms, and resilience. Positive interpretation bias predicted trainee teachers' resilience across time, suggesting that it is likely to be a good target for interventions to promote resilience.

Role of Infiltration on Land–Atmosphere Feedbacks in Central Europe: Fully Coupled WRF-Hydro Simulations Evaluated with Cosmic-Ray Neutron Soil Moisture Measurements

Abstract The skill of regional climate models partly relies on their ability to represent land–atmosphere feedbacks in a realistic manner, through coupling with a land surface model. However, these models often suffer from insufficient or erroneous information on soil hydraulic parameters. In this study, the fully coupled land–atmosphere model WRF-Hydro driven with ERA5 reanalysis is employed to reproduce the regional climate over central Europe with a horizontal resolution of 4 km for the period 2017–20. Simulated soil moisture is compared with data from cosmic-ray neutron sensors (CRNSs) at three terrestrial environmental observatories. Soil hydraulic parameters from continental and global digital soil datasets (SoilGrids and EU-SoilHydroGrids), together with Campbell and van Genuchten–Mualem retention curve equations, are used to assess the role of infiltration on modeled land–atmosphere feedbacks. The percolation parameter is calibrated to better capture observed discharge amounts in the observatories. WRF-Hydro with Campbell and SoilGrids gives the lowest mean annual temperature and mean annual precipitation differences compared to the E-OBS product from European Climate Assessment and Dataset, which is achieved by reducing soil moisture in the rootzone, increasing air temperature, and decreasing precipitation through a positive soil moisture–precipitation feedback process. WRF-Hydro with van Genuchten–Mualem and EU-SoilHydroGrids best reproduces CRNS soil moisture daily variations, despite enhanced positive biases that generate a larger proportion of convective precipitation favored over wet soils and spurious discharge peaks. This study demonstrates the importance of infiltration processes to realistically reproduce land–atmosphere feedbacks. Significance Statement The ability to correctly reproduce the feedbacks between land and atmosphere is crucial for a regional climate model. This study shows that the nature of these land–atmosphere feedbacks is partly related to the description of soil infiltration, which potentially helps to improve regional climate modeling results. An updated method to disentangle the proportion of convective precipitation being favored over wet, dry, and mixed soils is provided, which sheds new light on the soil moisture–precipitation feedback mechanism.

Solid-state esophageal pressure sensor for the estimation of pleural pressure: a bench and first-in-human validation study

BackgroundAdvanced respiratory monitoring through the measurement of esophageal pressure (Pes) as a surrogate of pleural pressure helps guiding mechanical ventilation in ICU patients. Pes measurement with an esophageal balloon catheter, the current clinical reference standard, needs complex calibrations and a multitude of factors influence its reliability. Solid-state pressure sensors might be able to overcome these limitations.ObjectivesTo evaluate the accuracy of a new solid-state Pes transducer (Pessolid). We hypothesized that measurements are non-inferior to those obtained with a properly calibrated balloon catheter (Pesbal).MethodsAbsolute and relative solid-state sensor Pes measurements were compared to a reference pressure in a 5-day bench setup, and to simultaneously placed balloon catheters in 15 spontaneously breathing healthy volunteers and in 16 mechanically ventilated ICU patients. Bland–Altman analysis was performed using mixed effects modelling with bootstrapping to estimate bias and upper and lower limits of agreement (LoA) and their confidence intervals.ResultsBench study: Solid-state pressure transducers had a positive bias (Psolid – Pref) of around 1 cmH2O for the absolute minimal and maximum pressures, and no bias for pressure swings. Healthy volunteers: the solid-state transducer revealed a bias (i.e., Pessolid – Pesbal) [upper LoA; lower LoA] of 1.59 [8.21; − 5.02], − 2.32 [4.27; − 8.92] and 3.91 [11.04; − 3.23] cmH2O for end-expiratory, end-inspiratory and ΔPes values, respectively. ICU patients: the solid-state transducer showed a bias (Pessolid–Pesbal) [upper LoA; lower LoA] during controlled/assisted ventilation of: − 0.15 [1.41; − 1.72]/− 0.19 [5.23; − 5.62], 0.32 [3.45; − 2.82]/− 0.54 [4.81; − 5.90] and 0.47 [3.90; − 2.96]/0.35 [4.01; − 3.31] cmH2O for end-expiratory, end-inspiratory and ΔPes values, respectively. LoA were ≤ 2cmH2O for static measurements on controlled ventilation.ConclusionsThe novel solid-state pressure transducer showed good accuracy on the bench, in healthy volunteers and in ventilated ICU-patients. This could contribute to the implementation of Pes as advanced respiratory monitoring technique.Trial registrationClinicaltrials.gov identifier: NCT05817968 (patient study). Registered on 18 April 2023.

Solar radiation estimation in West Africa: impact of dust conditions during the 2021 dry season

Abstract. The anticipated increase in solar energy production in West Africa requires high-quality solar irradiance estimates, which are affected by meteorological conditions and in particular the presence of desert dust aerosols. This study examines the impact of incorporating desert dust into solar irradiance and surface temperature estimations. The research focuses on a case study of a dust event in March 2021, which is characteristic of the dry season in West Africa. Significant desert aerosol emissions at the Bodélé Depression are associated with a Harmattan flow that transports the plume westwards. Simulations of this dust event were conducted using the meteorological Weather Research and Forecasting (WRF) Model alone, as well as coupling it with the CHIMERE chemistry transport model, using three different datasets for the dust aerosol initial and boundary conditions (CAMS, GOCART, and MERRA-2). Results show that considering desert dust reduces estimation errors in global horizontal irradiance (GHI) by about 75 %. The dust plume caused an average of 18 % reduction in surface solar irradiance during the event. Additionally, the simulations indicated a positive bias in aerosol optical depth (AOD) and PM10 surface concentrations. The choice of dataset for initial and boundary conditions minimally influenced GHI, surface temperature, and AOD estimates, whereas PM10 concentrations and aerosol size distribution were significantly affected. This study underscores the importance of incorporating dust aerosols into solar forecasting for better accuracy.

Subclinical depressive symptoms and job stress differentially impact memory in working and retired older adults

Retirement has been associated with cognitive decline beyond normal age-related decline. However, there are many individual differences in retirement that can influence cognition. Subclinical depressive symptoms are common in late life and are associated with general memory decline and a bias towards remembering negative events (i.e., better memory for negative vs. positive or neutral stimuli), in opposition to a reported positivity bias (i.e., better memory for positive vs. negative or neutral stimuli) in aging. Furthermore, job stress is often a major contributor to retirement decisions and may impact cognition post-retirement. Here, we aimed to examine how subclinical depressive symptoms and job stress in working and retired older adults impacted emotional memory. We found that retired, but not working, older adults with greater depressive symptoms showed enhanced negative and impaired positive memory. Second, working older adults with moderately high current job stress showed better memory overall but a weaker positivity bias, while retired older adults with moderately high retrospective job stress showed worse memory overall and a stronger positivity bias. These findings suggest that subclinical depressive symptoms and job stress have differing impacts on emotional memory in late life depending on retirement status.

Glucometer versus analyzer: comparable results with negligible clinical risk

This study assessed the reliability of Roche Accu-Chek Inform II glucometers in a real-world setting. A retrospective analysis was conducted on 6,695 paired results. Capillary samples were tested using Roche Accu-Chek Inform II glucometers, while venous samples were analyzed using Roche Cobas c503/702 analyzers. Compliance was assessed using modified criteria based on the ISO 15197 guideline and the CLSI EP09-A3 guideline using Passing-Bablok regression analysis, Bland-Altman plots, and Surveillance Error Grid (SEG) analysis. The overall compliance of glucometer results within ±15% or 0.83 mmol/L (15 mg/dL) of the reference method was 81.5%, below the acceptance criterion of 94.6%. SEG analysis showed that 90.3% of the paired results fell within the No-risk zone, with less than 0.001% in the moderate/lower-risk zone. The Emergency Department results indicated 87.8% overall compliance and 92.2% of pairs falling in the No-risk zone. Based on the regression analysis, the glucometer results showed a positive constant bias of nearly 0.33 mmol/L (6 mg/dL). The Bland-Altman plots showed a positive mean difference of 0.43 mmol/L for results ≤5.55 mmol/L (≤100 mg/dL) and a positive mean percentage difference of 3.77% for results >5.55 mmol/L (>100 mg/dL), within the permissible deviation. The compliance values ranged from 76.0% to 90.3% for clinical concentration groups, with the highest compliance found between >16.65–22.20 mmol/L (>300–400 mg/dL). The Accu-Chek Inform II glucometers demonstrated in real-world reliability, with most results falling within acceptable risk categories. However, compliance still needs improvement, so manufacturers should assess opportunities for advancement.

Multiscale Simulation of the Impact of Defects on Elevated-Metal Metal-Oxide IGZO TFTs

This study explores the impact of oxygen vacancy defects on elevated-metal metal-oxide (EMMO) IGZO TFTs under positive bias stress (PBS) using TCAD and DFT simulation. Findings reveal that oxygen vacancies accumulating at the channel/passivation layer interface and within the channel under PBS lead to negative threshold voltage shifts and reduced mobility. Additionally, higher tail state densities contribute to a positive Vth shift. These results provide important insights into the defect-related reliability of EMMO IGZO TFTs, guiding the design of more reliable devices.

Reliability of high-performance monolayer MoS2 transistors on scaled high-κ HfO2

The successful integration of ultrathin high-κ insulators is essential for the advancement of ultra-scaled field-effect transistors (FETs) based on two-dimensional (2D) semiconductors in future technology nodes. However, defects within the high-κ stack or at the interfaces can significantly degrade the performance of these “interface-only” devices, raising questions regarding their long-term reliability. Here, we study the reliability of monolayer MoS2 FETs on ultra-thin high-κ HfO2. Interestingly, we observe a two-stage threshold voltage shift (ΔVTH) under positive bias temperature stress (PBTS) and hot carrier degradation (HCD). This two-stage ΔVTH is absent in devices fabricated on exfoliated hBN, suggesting that the donor state generation (negative ΔVTH) is induced by atomic-layer-deposition (ALD) processes in HfO2-based devices. Elastic Recoil Detection Analysis (ERDA) indicates that hydrogen, likely from the ALD precursor, is a probable cause, highlighting the need for ALD process refinement to improve 2D FET stability for CMOS compatibility.

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.

Potential of long-term satellite observations and reanalysis products for characterising soil drying: trends and drought events

Abstract. Soil drying has multiple adverse impacts on the environment, society, and economy. Thus, it is crucial to monitor and characterise related drought events and to understand how underlying geophysical trends may affect them. Here, we compare the ability of long-term satellite observations and state-of-the-art reanalysis products to characterise soil drying. We consider the European Space Agency Climate Change Initiative (ESA CCI) remote-sensing surface soil moisture products (encompassing an ACTIVE, a PASSIVE, and a COMBINED product) as well as surface and root zone soil moisture from the ERA5, ERA5-Land, and MERRA-2 reanalysis products. In addition, we use a new root zone soil moisture dataset derived from the ESA CCI COMBINED product. We analyse global surface and root zone soil moisture trends in these products over the 2000–2022 period. Furthermore, we investigate the impact of the products' trend representation on their ability to capture major seasonal soil moisture (or agroecological) drought events as a use case. The latter is based on the analysis of 17 selected drought events documented in the scientific literature; these events are characterised by their severity (the time-accumulated standardised soil moisture anomalies), magnitude (the minimum of the standardised anomalies over time), duration, and spatial extent. The soil moisture trends are globally diverse and partly contradictory between products. ERA5, ERA5-Land, and ESA CCI COMBINED show larger fractions of drying trends, whereas ESA CCI ACTIVE and MERRA-2 display more widespread wetting trends. The differences between reanalysis products are related to a positive mean bias in the precipitation trends and regionally negative biases in surface air temperature trends in MERRA-2 compared with ground observational products, suggesting that this reanalysis underestimates drying trends. Given these biases in the MERRA-2 precipitation and temperature trends and considering available validation studies, the ESA CCI COMBINED-based products and ERA5-Land are considered more reliable and are consecutively used for a synthesis of global surface and root zone soil moisture trends. This synthesis suggests a consistent tendency towards soil drying during the last 2 decades in these products in 49.3 % of the surface and 44.5 % of the root zone layers of the covered global land area. The respective fractions of wetting trends amount to 21.1 % and 20.6 % for the surface and root zone, respectively, while areas with no trend direction consensus amount to 29.6 % and 35.0 %, respectively, reflecting the considerable uncertainties associated with global soil moisture trends. Geographically, drying is localised to parts of Europe and the Mediterranean; the Black Sea–Caspian Sea and Central Asian region; Siberia; parts of the western USA and the Canadian Prairies; and larger parts of South America, parts of southern and northern Africa, and parts of northwestern Australia. All investigated products mostly capture the considered drought events. Overall, the events tend to be least pronounced in the ACTIVE remote-sensing product across all drought metrics, particularly with respect to the magnitudes. Furthermore, MERRA-2 shows lower drought magnitudes than the other products, in both the surface layer and the root zone. The COMBINED remote-sensing products (surface and root zone soil moisture dataset) display partly stronger drought severities than the other products. In the root zone, the droughts are dampened with respect to the magnitude and smaller with respect to the spatial extent than in the surface layer, but they show a tendency toward prolonged durations and stronger severities. The product differences in the magnitude and severity of the drought events are consistent with the differences in soil moisture trends, which demonstrates that the representation of soil moisture trends plays a fundamental role in the drought-detection capacity of the different products.

Structural and electronic properties of interstitial oxygen defect in amorphous indium gallium oxide (IGO) semiconductors: a theoretical study

Abstract We elucidate the role of gallium (Ga) in the structural and electronic properties of amorphous indium gallium oxide(a-IGO) for different Ga concentrations with oxygen interstitial defects by using hybrid density functional methods. Ab initio molecular dynamic simulations reveal that Ga substitution significantly affects the structural characteristics and that Ga-O coordination is particularly sensitive to changes in oxygen stoichiometry. The electronic structure indicates the formation of an O-O dimer in the neutral state. The stability of this dimer upon capturing electrons is influenced by the local atomic structure around the dimer. When the bond breaks, the dimer's antibonding defect level is significantly lowered from the conduction band, approaching the valence band. This makes it more energetically advantageous for the dimer to capture two electrons. We statistically studied the Ga concentration dependence on the impact of O2 dimer generation in a-IGO. Formation transition energy indicates that O-O bond is broken easily with more Ga, which acts as an electron trap identifying the origin of positive bias stress (PBS) observed in the transistor behavior.

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.