Negative Effects Research Articles

Evaluation of Hurricane Analysis and Forecast System (HAFS) Error Statistics Stratified by Internal Structure and Environmental Metrics

Abstract This study quantifies tropical cyclone (TC) error statistics from the Hurricane Analysis and Forecast System (HAFS) across different environmental conditions (e.g., vertical wind shear) and inner core structural metrics. A particular focus is the evolution of poorly understood aspects of internal TC structure, including vortex tilt, and their impact on forecast errors. Although previous studies have demonstrated that vortex tilt, vertical wind shear, and precipitation processes impact TC intensity and track, this is the first known study to stratify these cooperative interactions to gain insights on their relationships with forecast errors. A three-year retrospective sample of forecasts in the North Atlantic basin from two HAFS configurations (-A and -B) demonstrates that TCs with larger tilt magnitudes have larger forecast track errors on average than smaller tilt TCs. Smaller tilt magnitudes have larger absolute intensity errors in short range forecasts, whereas larger tilt magnitudes tend to have larger negative intensity biases at medium range. TCs with a tilted vortex are shown to have both left of shear (maximizing DSL) and left of tilt oriented positional track biases. Furthermore, those cases with greater downshear biases tend to have more convection and larger positive intensity biases, highlighting the importance of the interplay between inner core characteristics and forecast errors.

Machine learning methods for propensity and disease risk score estimation in high-dimensional data: a plasmode simulation and real-world data cohort analysis

IntroductionMachine learning (ML) methods are promising and scalable alternatives for propensity score (PS) estimation, but their comparative performance in disease risk score (DRS) estimation remains unexplored.MethodsWe used real-world data comparing antihypertensive users to non-users with 69 negative control outcomes, and plasmode simulations to study the performance of ML methods in PS and DRS estimation. We conducted a cohort study using UK primary care records. Further, we conducted a plasmode simulation with synthetic treatment and outcome mimicking empirical data distributions. We compared four PS and DRS estimation methods: 1. Reference: Logistic regression including clinically chosen confounders. 2. Logistic regression with L1 regularisation (LASSO). 3. Multi-layer perceptron (MLP). 4. Extreme Gradient Boosting (XgBoost). Covariate balance, coverage of the null effect of negative control outcomes (real-world data) and bias based on the absolute difference between observed and true effects (for plasmode) were estimated. 632,201 antihypertensive users and nonusers were included.ResultsML methods outperformed the reference method for PS estimation in some scenarios, both in terms of covariate balance and coverage/bias. Specifically, XgBoost achieved the best performance. DRS-based methods performed worse than PS in all tested scenarios.DiscussionWe found that ML methods could be reliable alternatives for PS estimation. ML-based DRS methods performed worse than PS ones, likely given the rarity of outcomes.

The multi-dimensionality of citizen satisfaction: A conjoint experimental approach

Current research demonstrated that many factors affect public satisfaction of government services. One central challenge for scholars is that citizen satisfaction is a multi-dimensional concept, yet most empirical tests focus on a small number of factors, and do not account for the simultaneous effects of the many factors. In this study, we present a comprehensive approach that accounts for this multi-dimensionality, and views satisfaction as dependent on two categories of factors: service-specific attributes, and performance comparisons. We assess the multi-dimensional nature of citizen satisfaction with a conjoint experiment, a methodological tool that allows us to test the causal effect of multiple factors operating at the same time. We use the conjoint design to investigate citizen satisfaction from every-day government services. The findings suggest that citizen satisfaction is driven by both groups of variables. Also, we find evidence for a negativity bias in public evaluations when service-specific attributes are involved: individuals' reported satisfaction is more sensitive to negative information like higher costs or unprofessional behavior by service providers compared to positive description of these factors. At the same time, we find that factors in the performance comparisons category create more balanced effects on satisfaction with respect to the information valence. The analysis reveals the drivers of public satisfaction of government services and the importance of key factors. The use of a conjoint design provides a more appropriate tool to tackle the multi-dimensional nature of a central public administration concept of citizen satisfaction.

Ultrathin α-Bi2O3 Thin-Film Transistor for Cost-Effective Oxide-TFT Inverters.

Electronics is advancing toward greater diversity and sustainability by prioritizing energy efficiency and cost-effectiveness. Metal oxide thin-film transistor (TFT) represents a technology at the forefront of advancing next-generation sustainable electronics, and exploring oxide channel compositions is a crucial step in opening opportunities for developing next-generation device applications. This study presents the first development of n-channel α-Bi2O3-TFTs using a 4 nm ultrathin channel prepared by a cost-effective vacuum-free and solvent-free liquid metal printing method in ambient air. Even the pristine device exhibited a clear TFT action but required a large negative gate bias to turn off due mainly to excess carriers from oxygen vacancy in the α-Bi2O3 channel. Oxygen-containing post-annealing reduced both channel carrier and subgap defect densities, enabling the development of depletion and enhancement-type α-Bi2O3-TFTs with the saturation mobility of 2-4 cm2 V-1 s-1. Two types of oxide-TFT-based inverter circuits, zero-VGS-NMOS and CMOS inverters, were fabricated by using α-Bi2O3-TFTs, operating in a high voltage gain of over 130. This work demonstrates the potential of oxide semiconductor materials toward the development of next-generation sustainable electronics.

Reinforcement Learning with Multi-Policy Movement Strategy for Weakly Supervised Temporal Sentence Grounding

Temporal grounding involves identifying the target moment based on the provided sentence in an untrimmed video. In weakly supervised temporal grounding studies, existing temporal sentence grounding methods face challenges in (1) learning semantic alignment between the candidate window and language query and (2) identifying accurate temporal boundaries during the grounding process. In this work, we propose a reinforcement learning (RL)-based multi-policy movement framework (MMF) for weakly supervised temporal sentence grounding. We imitate the behavior of human beings when grounding specified content in a video, starting from a coarse location and then identifying fine-grained temporal boundaries. The RL-based framework initially sets a series of candidate windows and learns to adjust them step-by-step by maximizing the rewards, indicating the semantic alignment between the current window and the query. To better learn the alignment, we propose a Gaussian-based Dual-Alignment Module (GDAM) which combines the strengths of both scoring-based and reconstruction-based alignment methods, addressing the issues of negative sample bias and language bias. We also employ the multi-policy movement strategy (MMS) which grounds the temporal position in a coarse-to-fine manner. Extensive experiments demonstrate that our proposed method outperforms existing weakly supervised algorithms, achieving state-of-the-art performance on the Charades-STA and ActivityNet Captions datasets.

Drone-based infrared thermography to measure the intranasal temperature of baleen whales

ABSTRACT Traditional methods for quantifying the internal temperature of marine mammals require handling live animals, which is not practical for free-swimming baleen whales. Developing a less invasive, more repeatable method would significantly improve our understanding of whale health and thermal physiology. Infrared thermography (IRT) devices compatible with remotely piloted aircraft systems (RPAS) have facilitated qualitative assessments of heat signatures from marine mammals at sea, but absolute temperatures derived using this approach are rare. The goal of this study was to develop a precise empirical method for estimating intranasal temperatures of baleen whales using RPAS-based IRT. We conducted controlled field experiments and flights over North Atlantic right whales (Eubalaena glacialis, NARWs) to develop and test the methodology. Two approaches were evaluated to estimate intranasal temperatures from IRT sensor intensities: a three-point empirical line regression calibrated per flight using known-temperature objects and a generalized linear model incorporating environmental variables. Controlled field experiments demonstrated that the former approach had a median bias of −0.6°C (interquartile range: 1.5ºC), while the latter approach had unexplained negative proportional bias with increasing true temperature of the target object. After accounting for bias, the former approach yielded an average intranasal temperature of 26.9 ± 1.7°C for 21 unique NARWs. The anatomy of the mysticete upper respiratory tract and physiological heat conservation strategies may explain why estimates were low compared to internal temperatures measured from baleen whales using other techniques (30–39ºC). Variability within whales was less than ± 2°C, supporting the use of these methods to monitor the health of individuals over time. However, variability among whales was greater (up to 7ºC). Improvements in our understanding of whale physiology and respiratory mechanics and advancements in RPAS-based IRT calibrations could make this technology more reliable for assessing individual body temperatures and monitoring populations in the future.

Impact of bias stress and endurance switching on electrical characteristics of polycrystalline ZnO-TFTs with Al2O3 gate dielectric

Abstract This study experimentally investigates electrical characteristics and degradation phenomena in polycrystalline zinc oxide thin-film transistors (ZnO-TFTs). ZnO-TFTs with Al2O3 gate dielectric, Al-doped ZnO (AZO) source–drain contacts, and AZO gate electrode are fabricated using remote plasma-enhanced atomic layer deposition at a maximum process temperature of 190 °C. We employ positive bias stress (PBS), negative bias stress (NBS), and endurance cycling measurements to evaluate the ZnO-TFT performance and examine carrier dynamics at the channel-dielectric interface and at grain boundaries in the polycrystalline channel. DC transfer measurements yield a threshold voltage of −5.95 V, a field-effect mobility of 53.5 cm2/(V∙s), a subthreshold swing of 136 mV dec−1, and an on-/off-current ratio above 109. PBS and NBS measurements, analysed using stretched-exponential fitting, reveal the dynamics of carrier trapping and de-trapping between the channel layer and the gate insulator. Carrier de-trapping time is 88 s under NBS at −15 V, compared to 1856 s trapping time under PBS at +15 V. Endurance tests across 109 cycles assess switching characteristics and temporal changes in ZnO-TFTs, focusing on threshold voltage and field-effect mobility. The threshold voltage shift observed during endurance cycling is similar to that of NBS due to the contrast in carrier trapping/de-trapping time. A measured mobility hysteresis of 19% between the forward and reverse measurement directions suggests grain boundary effects mediated by the applied gate bias. These findings underscore the electrical resilience of polycrystalline ZnO-TFTs and the aptitude for 3D heterogeneous integration applications.

Numerical Simulation on the Impact of Back Gate Voltage in Thin Body and Thin Buried Oxide of Silicon on Insulator (SOI) MOSFETs

Silicon-on-Insulator (SOI) technology provides a solution for controlling Short-Channel Effects (SCEs) and enhancing the performance of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). However, scaling down SOI MOSFETs to a nanometer scale does not necessarily yield further scaling benefits. Introducing multiple gates, such as a double gate configuration, can effectively mitigate SCEs. Nonetheless, fabricating a flawless double gate structure is an exceedingly challenging endeavor that remains unrealized. The adoption of a back gate bias, with an asymmetrical thickness arrangement between the front and back gates, mimicking the behavior of a double gate, offers an alternative approach. This approach has the potential to modify the electrical characteristics of the device, thus potentially leading to improved control over SCEs. In this study, we employed 2D simulations using Atlas to investigate the influence of back gate biases, namely, -2.0 V, 0 V, and 2.0 V on a 10 nm silicon thickness at the top and a 20 nm buried oxide thickness for n-channel MOSFETs. We focused on key parameters, including threshold voltage (VTh), Drain Induced Barrier Lowering (DIBL), and Subthreshold Swing (SS). The results demonstrate that a negative back gate bias is the most favorable configuration, as it yields superior performance. This translates into more effectively controlled SCEs across all the parameters of interest.

Bistability-enhanced elastocaloric cooling device based on a natural rubber foil

A novel solid-state elastocaloric cooling device is presented, making use of a bistable actuation mechanism for loading of a natural rubber (NR) foil refrigerant. The thicknesses of the foil refrigerants are 290 and 650 μm in an initial undeformed state, while their lateral size is 9 × 26.5 mm2. Owing to the large surface-to-volume ratio of the NR foils, heat transfer to the heat sink and source is accomplished by a solid–solid mechanical contact. The loading mechanism consists of a rotating lever arm providing for stable positions at contact to the heat sink and source, which allows for significant power saving during elastocaloric cycling. In addition, the negative biasing associated with bistability favors good thermal contact at the end positions, which improves heat transfer resulting in a maximum temperature span ΔTdevice of 4.2 K in the strain range of 300%–700% under adiabatic conditions. The coefficient of performance of the device COPdevice reaches values up to 5.7 for foil refrigerants of 290 μm thickness. The maximum cooling power is 214 mW corresponding to a specific cooling power of 3.4 Wg−1.

Electing in the dark? Voting behavior in light of polarization

This paper develops a behavioral public choice model. It provides testable hypothesis to explain voter shifts in European national elections in the last decade. The model comprises three blocs of parties, the government, the opposition and so-called “profiteers”. Retrospective voters evaluate the performance of each bloc. Furthermore, it introduces an exogenous polarizing event that can affect the government’s and the profiteers’ chance to satisfy voters. Moreover, voters are subject to the negativity bias, which means that negative changes in probabilities to satisfy are stronger than positive changes. This framework yields various results on voting behavior under polarization. Most are robust to the introduction of non-voting. The government only profits from polarization iff sufficiently many positively voters are polarized in their favor to outweigh both the negativity bias and the increased competitiveness by profiteers due to polarization. Profiteers, strengthened by polarization, harm the opposition and increase voter turnout. Additionally, a higher negativity bias impairs the government, decreases voter turnout and benefits the opposition and profiteers.

Debiased hybrid contrastive learning with hard negative mining for unsupervised person re-identification

The goal of unsupervised person re-identification is to retrieve a specific person across several non-overlapping cameras without the aid of manual labeling information. In recent times, contrastive learning has found extensive application in undertaking the complexities of unsupervised person Re-ID. Nevertheless, prevailing approaches often ignore the bias in negative proxy sampling and the significance of hard negatives in contrastive learning. These limitations have constrained the performance of existing methods. To solve these issues, we introduce a Debiased Hybrid Contrastive Learning with Hard Negative Mining (DHCL-HNM) approach. Particularly, the proposed approach employs an instance-level memory bank to save the class prototypes for all training images. In each training epoch, the memory bank undergoes clustering, dividing the dataset into un-clustered outliers and clustered images with pseudo labels. Then, the debiasing of negative proxies and the hard negative mining are integrated into a hybrid contrastive learning process to enhance the intra-class similarity and the instance discrimination. The debiasing operation is realized during the sampling of negative proxies to reduce the negative effects of false negatives. In the meantime, the hard negative mining can guide the Re-ID model to concentrate on the hard negatives by reweighting negative proxies based on their similarities to the anchor sample. The efficiency of the proposed method in the realm of unsupervised person Re-ID is demonstrated through comprehensive experiment outcomes conducted on several datasets.

Understanding thickness-dependent stability of tungsten-doped indium oxide transistors

In this study, the influence of the thickness of the channel layer on the electrical properties and stability of tungsten-doped indium oxide (IWO) thin-film transistors (TFTs) was investigated. Although oxide-semiconductor TFTs, particularly indium gallium zinc oxide, are promising, problems related to oxygen vacancies have led to their instability. In contrast, IWO has proven to be a compelling alternative because of its robust resistance to oxygen vacancies. IWO TFTs with varying channel thicknesses (10, 20, and 30 nm) were fabricated, and the device parameters, such as threshold voltage (Vth), subthreshold swing (SS), field-effect mobility (μFE), and on/off current ratio (Ion/Ioff), were analyzed. It was found that as the channel thickness increased, Vth exhibited a negative shift and SS increased, indicating an increase in carrier concentration. This phenomenon is attributed to the bulk trap density, in particular to oxygen vacancies. Negative bias stress tests confirmed the influence of the oxygen vacancies, with thicker channels showing more pronounced shifts. Low-frequency noise measurements were consistent with the carrier number fluctuation model, indicating that defects within the channel region contribute to the observed noise. The study concludes that identifying an optimal channel thickness during device manufacturing is crucial for improved TFT performance, with 20 nm devices characterized by high μFE and comparable trap density to 10 nm. This study provides valuable insight into the nuanced relationship between the channel thickness, trap density, and electrical performance of IWO TFTs.

Exploring the Impact of Negative Bias Temperature Instability in SiGe p-MOSFETs Utilizing a Two-Stage Model

Exploring the Impact of Negative Bias Temperature Instability in SiGe p-MOSFETs Utilizing a Two-Stage Model

One-Step Magneton Sputtering of Crystalline Cu-Doped TiO2 Coatings: Characterization and Antibacterial Activity

Early biofilm formation could be inhibited by applying a thin biocompatible copper coating to reduce periprosthetic infections. In this study, we deposited crystalline Cu-doped TiO2 films using one-step DC magnetron sputtering in an oxygen atmosphere on a biased Ti6Al4V alloy without external heating. The bias voltage varied from −25 V to −100 V, and the resultant substrate temperature was measured. The deposited coatings were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), microhardness, scratch and hydrophilicity tests, potentiodynamic polarization measurements, and antibacterial assays against S. aureus and E. coli. The findings demonstrated that when a higher negative bias is applied, the substrate temperature drops, and the anatase to rutile transformation is initiated without indicating obvious Cu-containing phases. The SEM images of the films showed spherical agglomerates with homogeneously distributed Cu with decreasing Cu content as the bias value increased. Higher bias results in the grain refinement of the thinning coatings with more lattice microstrain and more defects, together with an increase in water contact angles and hardness values. Samples biased at −75 V exhibited the highest adhesive strength between coatings and substrate, whereas the specimen biased at −50 V demonstrated higher corrosion resistance. Cu-containing TiO2 coatings with pure anatase phase composition and Cu concentrations of 2.62 wt.% demonstrated excellent bactericidal activity against both S. aureus and E. coli. The layers containing 2.34 wt.% Cu exhibited very good antibacterial properties against S. aureus, only. According to these findings, the produced copper-doped TiO2 coatings have high bactericidal qualities in vitro and may be used to prepare orthopaedic and dental implants in the future.

Beyond dislike counts: How YouTube users react to the visibility of social cues

This study investigates the impact of YouTube’s 2021 policy, which hides dislike counts and limits a form of negative social feedback. It examines how this change affects social media herding behavior—the tendency of users to align with the majority opinion. We adopted a mixed-method approach, incorporating an online experiment that simulates the YouTube interface and an Interrupted Time Series analysis of real-world user reactions, to assess how the policy affects user engagement. Specifically, we looked at how the absence of one-sided digital cues, combined with content characteristics and individual user predispositions, influences user behavior. Our findings suggest that YouTube’s initiative to boost platform positivity had limited success: user responses were more influenced by their ideological leanings than by visible digital cues; Hiding dislikes reduced commenting frequencies and inadvertently increased negative expression. These results highlight the stronger role of ideological beliefs over social cues in shaping engagement, challenging the presumed impact of audience conformity and the negativity bias on social media dynamics.

Diverse Perspectives: An Inclusive Serious Game for (International) Students

Universities have increasingly diverse student populations. While a greater variety of students' backgrounds, skills and abilities exist, this does not necessarily mean they have more inclusive interactions. A lack of inclusive interactions can cause negative biases against people who are different from oneself. One strategy to mitigate bias is exposure to situations where students encounter social dilemmas with others and are stimulated to reflect on their interactions. These experiences could be simulated within a serious game as a safe learning environment. Moreover, serious games allow the player to broaden their mental perspective by showing the world through the eyes of others. This paper presents the design and evaluation of the serious game called Diverse Perspectives. This visual novel with multiple endings captures social dilemmas and allows the player to view them from a different angle through perspective switches. We evaluate Diverse Perspectives with quantitative ( N = 32) and qualitative measures on attitude towards diversity and gaming experience measured with the Shortened Version of the Miville-Guzman Universality-Diversity Scale and the Game Experience Questionnaire. Participants indicate they find the perspective switch helpful as it creates an understanding of the other person's view.

Avoiding avalanche breakdown in planar GaN Gunn diodes by means of a substrate contact

Abstract Impact ionization originated by the buffer leakage current, together with high electric fields ( > 3 MV cm−1) at the anode corner of the isolating trenches, has been identified as the failure mechanism of shaped planar GaN Gunn diodes when biased above 20 V, so that no evidence of Gunn oscillations in fabricated devices has been observed yet. In order to avoid the avalanche, we propose the addition of a Schottky substrate terminal, which, by means of Monte Carlo simulations, has been confirmed to be able to suppress such not-desired leakage current when applying a negative substrate bias. When the substrate bias is positive, impact ionization is also reduced due to the lower electric field at the hotspot, but a vertical cathode-substrate current degrades the device operation. In order to avoid such current, we propose the use a MIS configuration for the substrate contact, which is the optimal solution.

Heart Rate Variability During Rapid Eye Movement Sleep is Associated with Reduced Negative Memory Bias.

Emotional memories change over time, but the mechanisms supporting this change are not well understood. Sleep has been identified as one mechanism that supports memory consolidation, with sleep selectively benefitting negative emotional consolidation at the expense of neutral memories, with specific oscillatory events linked to this process. In contrast, the consolidation of neutral and positive memories, compared to negative memories, has been associated with increased vagally-mediated vagal heart rate variability (HRV) during wakefulness. However, how HRV during sleep contributes to emotional memory consolidation remains unexplored. We investigated how sleep oscillations and vagal contributions during sleep contribute to the consolidation of neutral and negative memories. Using a double-blind, placebo-controlled, within-subject, cross-over design, we examined the impact of pharmacological vagal suppression using zolpidem on overnight emotional memory consolidation. Thirty-two participants encoded neutral and negative pictures in the morning, followed by picture recognition tests before and after a night of sleep. Zolpidem or placebo was administered in the evening before overnight sleep, and participants were monitored with electroencephalography and electrocardiography. In the placebo condition, greater overnight improvement for neutral pictures was associated with higher vagal HRV in both Non-Rapid Eye Movement Slow Wave Sleep (NREM SWS) and REM. Additionally, the emotional memory tradeoff (i.e., difference between consolidation of neutral versus negative memories) was associated with higher vagal HRV during REM, but in this case, neutral memories were remembered better than negative memories, indicating a potential role for REM vagal HRV in promoting a positive memory bias overnight. Zolpidem, on the other hand, reduced vagal HRV during SWS, increased NREM sigma power, and eliminated the positive memory bias. Lastly, we used a stepwise linear mixed effects regression to determine how NREM sigma power and vagal HRV during REM independently explained the variance in the emotional memory tradeoff effect. We found that the addition of vagal HRV in combination with sleep significantly improved the model's fit. Overall, our results suggest that sleep brain oscillations and vagal signals synergistically interact in the overnight consolidation of emotional memories, with REM vagal HRV critically contributing to the positive memory bias.

The Making of Good News: Discursive Construction of Good News Through News Values

ABSTRACT Good news aims to redress the balance from negative bias and contributes to a more comprehensive form of journalism. This article explores the largely ignored discursive construction of good news through news values. It first investigates the features of good news stories as against top news stories in the mainstream media, and then identifies differences in the discursive practices by the mainstream media and the good news outlets in covering the same events. The findings show that in the mainstream media, top news stories tend to highlight Eliteness and Negativity, whereas good news stories give emphasis to Personalization and Positivity. When covering the same events, reports by the good news outlets show an overemphasis on Positivity, and those by the mainstream media demonstrate a more balanced distribution of the major news values. It is proposed that good news can serve as a valuable complement to top news in the mainstream media. Reports in the mainstream media tend to be more comprehensive and informative, and the relatively shorter reports in the good news outlets pay more attention to the positive aspects of the event that are effective in uplifting the readers’ mood.

A Compact V-Band Temperature Compensation Low-Noise Amplifier in a 130 nm SiGe BiCMOS Process.

This paper presents a compact V-band low-noise amplifier (LNA) featuring temperature compensation, implemented in a 130 nm SiGe BiCMOS process. A negative temperature coefficient bias circuit generates an adaptive current for temperature compensation, enhancing the LNA's temperature robustness. A T-type inductive network is employed to establish two dominant poles at different frequencies, significantly broadening the amplifier's bandwidth. Over the wide temperature range of -55 °C to 85 °C, the LNA prototype exhibits a gain variation of less than 1.5 dB at test frequencies from 40 GHz to 65 GHz, corresponding to a temperature coefficient of 0.01 dB/°C. At -55 °C, 25 °C, and 85 °C, the measured peak gains are 25.5 dB, 25 dB, and 24.4 dB, respectively, with minimum noise figures (NF) of 3.0 dB, 3.5 dB, and 4.2 dB, and DC power consumptions of 22.3 mW, 27.6 mW, and 34.4 mW. Moreover, the total silicon area of the LNA chip is 0.37 mm2, including all test pads, while the core area is only 0.09 mm2.