Directional Bias Research Articles

Validation of seasonal mean radiant temperature simulations in hot arid urban climates

We validated seasonal RayMan and ENVI-met mean radiant temperature (TMRT) simulations to assess model performance in a sensitivity analysis from cold to extremely hot conditions. Human-biometeorological validation data were collected in Tempe, Arizona via transects during five field campaigns between 2014 and 2017. Transects were conducted across seven locations in two to three-hour intervals from 6:00 to 23:00 LST with a Kestrel meter and thermal camera (2014–2015) and the mobile instrument platform MaRTy (2017). Observations across diverse urban forms, sky view factors, and seasons covered a wide range of solar radiation regimes from a minimum TMRT of 8.7 °C to a maximum of 84.9 °C. Both models produced large simulation errors across regimes with RMSE ranging from 8 °C to 12 °C (RayMan) and 11.2 °C to 16.1 °C (ENVI-met), exceeding a suggested TMRT accuracy of ±5 °C for heat stress studies. RayMan model errors were largest for engineered enclosed spaces, complex urban forms, and extreme heat conditions. ENVI-met was unable to resolve intra-domain spatial variability of TMRT and exhibited large errors with RMSE up to 25.5 °C for engineered shade. Both models failed to accurately simulate TMRT for hot conditions. Errors varied seasonally with overestimated TMRT in the summer and underestimated TMRT in the winter and shoulder seasons. Results demonstrate that models should not be used under micrometeorological or morphological extremes without in-situ validation to quantify errors and assess directional bias due to model limitations.

Evolutionary directions of single nucleotide substitutions and structural mutations in the chloroplast genomes of the family Calycanthaceae

BackgroundChloroplast genome sequence data is very useful in studying/addressing the phylogeny of plants at various taxonomic ranks. However, there are no empirical observations on the patterns, directions, and mutation rates, which are the key topics in chloroplast genome evolution. In this study, we used Calycanthaceae as a model to investigate the evolutionary patterns, directions and rates of both nucleotide substitutions and structural mutations at different taxonomic ranks.ResultsThere were 2861 polymorphic nucleotide sites on the five chloroplast genomes, and 98% of polymorphic sites were biallelic. There was a single-nucleotide substitution bias in chloroplast genomes. A → T or T → A (2.84%) and G → C or C → G (3.65%) were found to occur significantly less frequently than the other four transversion mutation types. Synonymous mutations kept balanced pace with nonsynonymous mutations, whereas biased directions appeared between transition and transversion mutations and among transversion mutations. Of the structural mutations, indels and repeats had obvious directions, but microsatellites and inversions were non-directional. Structural mutations increased the single nucleotide mutations rates. The mutation rates per site per year were estimated to be 0.14–0.34 × 10− 9 for nucleotide substitution at different taxonomic ranks, 0.64 × 10− 11 for indels and 1.0 × 10− 11 for repeats.ConclusionsOur direct counts of chloroplast genome evolution events provide raw data for correctly modeling the evolution of sequence data for phylogenetic inferences.

Programmable Coding Metasurface Reflector for Reconfigurable Multibeam Antenna Application

In this article, we propose a method of designing programmable coding metasurface with a reconfigurable number of reflected beams. Each unit cell of the metasurface is loaded with one varactor to enable adjustable phase responses. The bias, beneath the ground drilled with small holes, is connected to unit cells by a thin via through the holes, to avoid adverse influences on unit cells. To simplify the bias network, a super unit composed of 5× 5 unit cells is taken as the coding element of realizing 2-D coding sequences. With different bias voltages, the unit cell will produce different reflection phases. By programming the bias voltages, the number and directions of reflected beams can be tailored due to different coding sequences. Under normal incident, reflected waves will be split into multiple beams whose directions can be flexibly controlled. We designed a prototype, implemented our design, and carried out experiments. Both the simulation and experiment results show that the number of reflected beams can be reconfigured between 1 and 5. Reflect beam number reconfigurability of such metasurfaces can be readily used as planar reflector of antennas and may find applications in wireless communications.

Patient demographic and psychosocial characteristics associated with 30-day recall of self-reported lower urinary tract symptoms.

Measurement of self-reported lower urinary tract symptoms (LUTS) typically uses a recall period, for example, "In the past 30 days…." Compared to averaged daily reports, 30-day recall is generally unbiased, but recall bias varies by item. We examined the associations between personal characteristics (eg, age, symptom bother) and 30-day recall of LUTS using items from the Symptoms of Lower Urinary Tract Dysfunction Research Network Comprehensive Assessment of Self-reported Urinary Symptoms questionnaire. Participants (127 women and 127 men) were recruited from 6 US tertiary care sites. They completed daily assessments for 30 days and a 30-day recall assessment at the end of the study month. For each of the 18 tested items, representing 10 LUTS, the average of the participant's daily responses was modeled as a function of their 30-day recall, the personal characteristic, and the interaction between the 30-day recall and the characteristic in separate general linear regression models, adjusted for sex. Nine items representing 7 LUTS exhibited under- or overreporting (recall bias) for at least 25% of participants. Bias was associated with personal characteristics for six LUTS. Underreporting of incontinence was associated with older age, lower anxiety, and negative affect; overreporting of other LUTS was associated with, symptom bother, symptom variability, anxiety, and depression. We identified under- or overreporting that was associated with personal characteristics for six common LUTS. Some cues (eg, less bother and lower anxiety) were related to recall bias in an unexpected direction. Thus, providers should exercise caution when making judgments about the accuracy of a patient's symptom recall based on patient demographic and psychosocial characteristics.

Controllable Orthogonal Mode Rejection for Smart Polarization Diversity at Millimeter-Wave Frequency

A ferromagnetic loaded device for controllable orthogonal mode rejection at millimeter-Wave is presented in this brief. The device is based on dual image dielectric guide (DIDG) capable of supporting both vertical (V-mode) and horizontal (H-mode) polarization. Two ferrite pillboxes are placed vertically (axis parallel to V-mode) and horizontally (axis parallel to H-mode) beside and above the DIDG, receptively. These pillboxes act as whispering gallery mode resonators interacting with the mode parallel to their axis depending on the applied magnetic DC bias, resulting in controllable mode rejection beneficial in smart antenna systems. Despite traditional magnetically tunable ferrite based components, the proposed design is mostly based on the direction of the magnetic bias requiring a small magnetic bias of 1 mT. An aperture coupling transition from Microstrip line to DIDG is used to perform orthogonal mode decomposition as well as proposing planar circuits excitation and integration. Measured polarization filtering bandwidth provided by each pillbox is 0.4 GHz having insertion loss higher than 10 dB (no transmission) and port isolation of higher than 15 dB. Insertion loss of the case, when the rejection mechanism is off, is around 3 dB.

Using finite element analyses to assess the effect of a thickness gradient on the stress profile at the epoxy/silicone interface of thin coatings subjected to pull-off loading

Silicone-based materials can be applied on ship hulls to serve as foul release coatings. Depending on the application, coatings are not likely to have a uniform thickness. Pull-off tests of epoxy studs from silicone coatings with a thickness gradient found that for the thickest coatings, release initiated at the edge and proceeded inward with no bias in the peeling direction, and as the thickness decreased the release initiated on the thin side of the coating. Release mechanism and critical pull-off force were also affected. In this work, finite element models were developed to predict the detailed stress field at the silicone/epoxy interface in silicone coatings with a thickness gradient. Average coating thickness, thickness gradient, and Poisson's ratio were varied to determine changes in the value and location of the peak interface stress and determine the properties that produce the highest peak interface stress, which should correspond to the lowest critical pull-off force. While the peak stress increased with increasing thickness gradients in all cases, the optimal geometric properties depended on the Poisson's ratio of the coating, so the specific material chosen is an important factor. The location of the peak stress was nearly always on the thin side of the coating when a thickness gradient was present, although the exact location (i.e., edge or interior) also depended on the Poisson's ratio.

Detecting Chirality in Two-Terminal Electronic Nanodevices.

Central to spintronics is the interconversion between electronic charge and spin currents, and this can arise from the chirality-induced spin selectivity (CISS) effect. CISS is often studied as magnetoresistance (MR) in two-terminal (2T) electronic nanodevices containing a chiral (molecular) component and a ferromagnet. However, fundamental understanding of when and how this MR can occur is lacking. Here, we uncover an elementary mechanism that generates such an MR for nonlinear response. It requires energy-dependent transport and energy relaxation within the device. The sign of the MR depends on chirality, charge carrier type, and bias direction. Additionally, we reveal how CISS can be detected in the linear response regime in magnet-free 2T nanodevices, either by forming a chirality-based spin-valve using two or more chiral components or by Hanle spin precession in devices with a single chiral component. Our results provide operation principles and design guidelines for chirality-based spintronic nanodevices and technologies.

Speed and accuracy of saccades in patients with glaucoma evaluated using an eye tracking perimeter

BackgroundTo examine the speed and accuracy of saccadic eye movements during a novel eye tracking threshold visual field assessment and determine whether eye movement parameters may improve ability to detect glaucoma.MethodsA prospective study including both eyes of 31 patients with glaucoma and 23 controls. Standard automated perimetry (SAP) and eye tracking perimetry (saccadic vector optokinetic perimetry, SVOP) was performed. SVOP provided data on threshold sensitivity, saccade latency, and two measures of accuracy of saccades (direction bias and amplitude bias). The relationship between eye movement parameters and severity of glaucoma was examined and Receiver Operating Characteristic curves were used to assess ability to detect glaucoma.ResultsPatients with glaucoma had significantly slower saccades (602.9 ± 50.0 ms versus 578.3 ± 44.6 ms for controls, P = 0.009) and reduced saccade accuracy (direction bias = 7.4 ± 1.8 versus 6.5 ± 1.5 degrees, P = 0.006). There was a significant slowing of saccades and saccades became less accurate with worsening SAP sensitivity. Slower saccades were associated with increased odds of glaucoma; however, the AUC for saccade latency was only 0.635 compared to 0.914 for SVOP sensitivity.ConclusionPatients with glaucoma had significant differences in eye movements compared to healthy subjects, with a relationship between slower and less accurate eye movements and worse glaucoma severity. However, in a multivariable model, eye movement parameters were not of additional benefit in differentiating eyes with glaucoma from healthy controls.

Nonequilibrium Thermodynamics of Turbulence-Driven Rotors.

We characterize a process of energy extraction via rectification of strongly turbulent flow by using tools of stochastic thermodynamics. We study the dynamics of an asymmetric autonomous rotor that shows biased direction of rotation when placed in a stream. We give experimental evidence that a fluctuation theorem can be used to describe the work injected in the rotor via its coupling with the turbulent flow structure. This approach allows to measure the mean power extracted from the chaotic fluid motion over a broad range of turbulent kinetic energy. A nontrivial dependence of the rotor power on flow kinetic energy is identified. This observation is described by a model taking into account the dissipation of the rotor energy and the temporal memory of coherent structures present in the turbulent flow.

Deformation behavior of auxetic woven fabric made of foldable geometry in different tensile directions

Auxetic woven fabrics made with special geometrical structures have gained the interest of textile scientists in recent years. This paper reports a study on auxetic woven fabric based on a double-directional parallel in-phase zig-zag foldable geometrical structure. Such a fabric has been already produced and investigated for its negative Poisson's ratio effect in two principal directions (weft and warp directions). However, its negative Poisson's ratio effect in biased tensile directions as well as under repeated tensile loading conditions has not been studied yet. Therefore, in this paper, these two limitations are addressed. The auxetic woven fabric was firstly fabricated, and then subjected not only to tensile tests in different tensile directions, including two principle directions and three biased directions, but also to repeated tensile loading. It was found that both the negative Poisson's ratio effect and the resistance to tensile deformation are dependent upon the tensile direction, and the highest negative Poisson's ratio effect and higher resistance to tensile deformation are obtained in two principal directions.

Speed and directedness predict colonization sequence post-disturbance.

Foundational ecological models characterize dispersal with two behavioral traits, speed and directional bias. We hypothesized that these two traits can predict the order of colonization by fishes in a heterogenous landscape. Colonization patterns following hydrological disturbance were documented from a 20-year multi-site time series of marsh fish, and we evaluated the ability of a two-parameter model to predict these patterns. The maximum aerobic swimming speed (UCRIT) for six coexisting fish species were estimated using endurance tests; field estimates of directedness and swimming speed were previously documented using encounter samplers. We incorporated interspecific variation in speed, direction, and density into several Agent Based Modelsto simulate dispersal following disturbance. Six virtual "species" with varying levels of directedness, "swam" in an artificial environment to reach a refuge habitat. The time of first arrival for each species was saved at the end of each run and used to calculate the probability of arrival order. Our simulated results generated predictions on order of arrival consistent with observed colonization patterns in our long-term dataset. Swim tunnel results revealed that fast (high UCRIT) estimates were characteristic of early colonizing species; whereas, slow (low UCRIT) estimates were characteristic of late colonizing species. Directional bias better predicted order of arrival than speed and was robust to inter-specific variation in density. This study demonstrated that two parameters were adequate to predict the order of species colonization in a complex landscape. These results support the use of relatively simple trait-based models to generate realistic community assembly dynamics.

Abstract 34: Improve decision making in clinical trials through machine learning and EHR

Abstract One of the key contributors to the failure of oncology trials is patient selection bias. A bias that results in a lower observed efficacy in phase II may lead to a premature decision to abort a trial, whereas a bias in the positive direction may result in an expensive failure in phase III. We propose an approach in which RWE is used to model a proxy endpoint that is available in RWE but is also related to the endpoint in clinical trial, on patient profile; the model is then used on clinical trial patients to predict their proxy endpoints, which in turn is used to quantitatively assess selection bias and infer the effect of bias on the observed efficacy of the trial. We used an ongoing metastatic breast cancer trial to demonstrate this approach. Medication, demography, vital signs, and time of death of the target patient population were extracted from Optum Humetica. These data were then used to train a ML survival model to predict OS based on patient profiles in a virtual trial. For this oncology trial, we chose OS as a proxy endpoint as it has a well-established strong correlation with the observed efficacy in terms of PFS and time on drug duration. OS is an endpoint. The term proxy is used here in the sense that it is not the endpoint used in the earlier-phase trial. The model is then used to predict risk profiles for patients in the actual trial, and the difference between risk profile of the trial patients and that of the RWE target population provides a quantitative assessment of selection bias of the trial population. The effectiveness of this approach depends on the predictive power of the model. A nonpredictive model obviously cannot detect bias even when it is present. To quantitatively assess the predictive power of the model, we subsampled the RWE population to simulate a trial population with different risk profiles and use the model to determine a threshold in risk difference beyond which the model can detect a significant difference. In this context, we also compared Cox PH, decision tree, and a neural network model with respect to their predictive power in term of concordance score. We then compared the risk profile of the clinical trial patients with that of the target patient population. As RWE data become more abundant and data interoperability and quality improve, the prediction model will become more accurate and bias detection will become more sensitive. We believe this approach will lead to an effective framework whereby RWE data can be used to improve the success rate of oncology clinical trials. Citation Format: LiMing Shen, Tao Sheng, Xaiodong Luo. Improve decision making in clinical trials through machine learning and EHR [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 34.

Estimating prevalence and test accuracy in disease ecology: How Bayesian latent class analysis can boost or bias imperfect test results.

Obtaining accurate estimates of disease prevalence is crucial for the monitoring and management of wildlife populations but can be difficult if different diagnostic tests yield conflicting results and if the accuracy of each diagnostic test is unknown. Bayesian latent class analysis (BLCA) modeling offers a potential solution, providing estimates of prevalence levels and diagnostic test accuracy under the realistic assumption that no diagnostic test is perfect.In typical applications of this approach, the specificity of one test is fixed at or close to 100%, allowing the model to simultaneously estimate the sensitivity and specificity of all other tests, in addition to infection prevalence. In wildlife systems, a test with near‐perfect specificity is not always available, so we simulated data to investigate how decreasing this fixed specificity value affects the accuracy of model estimates.We used simulations to explore how the trade‐off between diagnostic test specificity and sensitivity impacts prevalence estimates and found that directional biases depend on pathogen prevalence. Both the precision and accuracy of results depend on the sample size, the diagnostic tests used, and the true infection prevalence, so these factors should be considered when applying BLCA to estimate disease prevalence and diagnostic test accuracy in wildlife systems. A wildlife disease case study, focusing on leptospirosis in California sea lions, demonstrated the potential for Bayesian latent class methods to provide reliable estimates under real‐world conditions.We delineate conditions under which BLCA improves upon the results from a single diagnostic across a range of prevalence levels and sample sizes, demonstrating when this method is preferable for disease ecologists working in a wide variety of pathogen systems.

Theoretical predictions for the rheology of dispersions of highly deformable particles under large amplitude oscillatory shear

This work is concerned with the oscillatory rheology of non-colloidal suspensions of highly deformable viscoelastic particles in Newtonian fluids under simple shear loading. To this end, use is made of the homogenization model of Avazmohammadi & Ponte Castaneda (J. Fluid Mech., vol. 763, 2015, pp. 386–432) accounting for the time evolution of the average particle shape and orientation. For small excitation amplitudes, the equations reduce to the small-strain Oldroyd model with expressions for the storage and loss moduli, and , that recover those of Roscoe (J. Fluid Mech., vol. 28 (2), 1967, pp. 273–293) for small particle concentrations. However, at sufficiently large concentrations, and may intersect, such that in a given frequency range. In the large amplitude oscillatory shear (LAOS) regime, the behaviour of and with increasing strain amplitude is consistent with type I or type III behaviour, in the terminology of Hyun et al. (J. Non-Newtonian Fluid Mech., vol. 107 (1–3), 2002, pp. 51–65), depending on the particle properties and concentration. In addition, the rheology is characterized by means of stress waveforms and Lissajous–Bowditch cycles in a Pipkin diagram. By accounting for the microstructure evolution, the model captures a number of nonlinear features commonly observed in the LAOS rheology of complex fluids, including a variety of distorted stress waveforms that manifest themselves in complex intracycle behaviour, as well as secondary loops. Furthermore, as a consequence of directional biases associated with the large deformations of the particles, the model predicts non-vanishing normal stress differences whose characteristic limit cycles are also presented in Pipkin space and reveal the formation of secondary loops for suspensions of Gent particles. However, it should be emphasized that the sources of these nonlinear rheological features for soft particle suspensions are very different from those for rigid particle colloidal systems and, in contrast to the colloidal systems, manifest themselves at dilute volume fractions of the particles.

Requirements of epitaxially grown InGaAs channel layers for tunnel field-effect transistors

The requirements of the epitaxially grown InGaAs channel layers for tunnel field-effect transistors (TFETs) have been studied by a comparison between the experimental results and technology computer-aided design (TCAD) simulations. It is observed that the threshold voltage (Vth) of InGaAs TFETs with high In contents is shifted more toward the negative bias direction and the off-characteristics are degraded more than that expected in simulation results. These results are attributable to the increase in n-type effective carrier concentration (Nch) in the InGaAs and InAs channels, which can be caused by lattice relaxation because of the large lattice mismatch between the epitaxial layer and the substrate. The use of a thin channel layer with high In content InGaAs and/or InAs can be a solution for achieving high on-current and low off-current simultaneously. It is found that p-type doping in the InGaAs and InAs channels can mitigate the degradation of the cut-off properties. Moreover, it is observed that increased Nch by unintentional Si impurity atoms at the epitaxial layer and the substrate interface can affect the performance of TFETs with thin InGaAs channels, which can be suppressed by introducing an insertional undoped buffer layer. The impact of Nch is also studied for the short channel devices by TCAD simulations. The p-type doping in InGaAs channels can also mitigate short channel effects in comparison to the n-type doping. The carefully controlled epitaxial growth of InGaAs and InAs channel layers with Nch <1 × 1017 cm−3 is required to realize superior performance InGaAs TFETs.

Using the Implicit Relational Assessment Procedure (IRAP) to Examine Implicit Gender Stereotypes in Science, Technology, Engineering and Maths (STEM)

Women are often subject to gender stereotyping in the fields of science, technology, engineering, and mathematics (STEM). The Implicit Relational Assessment Procedure (IRAP) was used to determine directionality of any implicit gender-STEM bias detected. In addition, the IRAP was used to explore the possibility of implicit ageism bias, because there is anecdotal evidence of high levels of ageism in the STEM areas. Thus two IRAPs (one with adult pictorial stimuli and one with child pictorial stimuli) were employed to assess implicit gender bias toward STEM with a sample of undergraduates (N = 33). Results indicated a gender STEM bias in both IRAPs and the directionality in both IRAPs was pro-male and not anti-female. Participant gender was not shown to impact results in either IRAP. Gender bias effects were more pronounced in the Adult-IRAP results. Comparison of bias toward older versus young pictorial stimuli was exploratory thus findings are preliminary but may suggest ageism and potential negative interaction effects between age and gender warrant further research.

An investigation on shear properties of woven fabrics by bias-extension test

External forces cause deformations on fabrics and define their mechanical properties. . In this study, woven fabrics having different weave types with different weft settings and their shear properties such as shear angle, breaking load, and extension at bias direction were investigated by bias-extension test. A new geometrical model was proposed to predict the shear angle of deformed fabrics from bias-extension test results. An experimental study was also carried out and shear angle of fabrics was measured on captured images of deformed fabrics. It was found that the shear angle results found by the new geometrical model were close to experimental results. Besides, tensile properties of fabrics along warp and weft directions were tested. Breaking load and extension results of bias-extension and tensile tests were discussed statistically depending on the structural parameters. It was observed that the direction of the force and structural properties of fabrics affect the load-extension results.

Superior accuracy and precision of SEEG electrode insertion with frame-based vs. frameless stereotaxy methods

Stereotactic electroencephalography (SEEG) has largely become the preferred method for intracranial seizure localization in epileptic patients due to its low morbidity and minimally invasive approach. While robotic placement is gaining popularity, many centers continue to use manual frame-based and frameless methods for electrode insertion. However, it is unclear how these methods compare in regard to accuracy, precision, and safety. Here, we aim to compare frame-based insertion using a CRW frame (Integra®) and frameless insertion using the StealthStation™ S7 (Medtronic®) navigation system for common temporal SEEG targets. We retrospectively examined electrode targets in SEEG patients that were implanted with either frame-based or frameless methods at a level 4 epilepsy center. We focused on two commonly used targets: amygdala and hippocampal head. Stealth station software was used to merge pre-operative MR with post-operative CT images for each patient, and coordinates for each electrode tip were calculated in relation to the midcommissural point. These were compared to predetermined ideal coordinates in regard to error and directional bias. A total of 81 SEEG electrodes were identified in 23 patients (40 amygdala and 41 hippocampal head). Eight of 45 electrodes (18%) placed with the frameless technique and 0 of 36 electrodes (0%) placed with the frame-based technique missed their target and were not clinically useful. The average Euclidean distance comparing actual to ideal electrode tip coordinates for frameless vs. frame-based techniques was 11.0mm vs. 7.1mm (p< 0.001) for the amygdala and 12.4mm vs. 8.5mm (p< 0.001) for the hippocampal head, respectively. There were no hemorrhages or clinical complications in either group. Based on this series, frame-based SEEG insertion is significantly more accurate and precise and results in more clinically useful electrode contacts, compared to frameless insertion using a navigation guidance system. This has important implications for centers not currently using robotic insertion.

Caloric Vestibular Stimulation Reduces the DirectionalBias in Representational Neglect.

Caloric vestibular stimulation (CVS) can temporarily reduce visuospatial neglect and related symptoms. The present study examined the effect of CVS on representational neglect during free exploration of the map of France. We asked patients to name cities they could mentally “see” on the map of France, without giving them any directional instructions related to the left or right sides of the map. In right brain damaged patients with left visuospatial neglect, the mental representation of the map was asymmetrical (favoring the right side). After stimulation, neglect patients named more towns on the left side of the map, leading to a significant reduction in map representation asymmetry. Our findings are consistent with previous studies on visuospatial neglect and are in favor of a central effect of vestibular stimulation on mechanisms involved in space representation.

Insight into interface behavior and microscopic switching mechanism for flexible HfO2 RRAM

A high-performance flexible HfO2 resistive random access memory (RRAM) device is fabricated herein on a polyimide (PI) substrate, and the effect of different top electrodes (TE) on RRAM characteristics were investigated with the same TiN bottom electrode. Compared with Al or Ni TEs, the switching characteristics of devices with indium tin oxide (ITO) TEs are improved, producing a low power consumption (50 µA@0.5 V for SET and 15 µA@-0.2 V for RESET) and high DC endurance cycles (>3 × 105). The flexible devices show stable resistive properties under different bending radii of up to 4 mm, and over 1.5 × 105 writing/erasing cycles are confirmed after bending the device 1,000 times. The switching mechanism based on ITO/HfO2 interfacial reactions is constructed, and the microscopic oxygen vacancies distribution under directional external biases is elaborated according to the C-V test under various frequencies, HRTEM and XPS data. Furthermore, it is revealed that the interface layer between the TE and the switching layer is the key role, which can maintain switching behaviors and improve electronic properties with the presence of a mechanical stress because of the stable interfacial reactions caused by Sn4+ in ITO film.