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Purpose To investigate the anterior scleral thickness (AST) and its associations with Schlemm’s canal (SC) area, trabecular meshwork (TM) thickness and length, and scleral spur (SS) length in healthy and primary open-angle glaucoma (POAG) groups. Methods Thirty-five eyes of 35 healthy subjects and 23 eyes of 23 patients with POAG were included. The AST, SC area, TM thickness and length, and SS length were measured using swept-source optical coherence tomography. AST was measured at 0 mm (AST0), 1 mm (AST1), 2 mm (AST2), and 3 mm (AST3) from SS. Associations between AST and SC area, TM thickness and length, and SS length were also estimated. Results AST0 (728.84 ± 99.33 vs. 657.39 ± 67.02 μm, p p = 0.038), AST3 (571.09 ± 79.15 vs. 532.13 ± 59.84 μm, p = 0.009), SC area (6304.26 ± 1238.72 vs. 4755.64 ± 1122.71 μm2, p p = 0.035), TM length (736.20 ± 141.85 vs. 656.43 ± 127.03 μm, p = 0.004), and SS length (219.89 ± 50.29 vs. 174.54 ± 35.58 μm, p Conclusions Compared with the healthy group, AST was significantly thinner in the POAG group, which also had smaller SC and TM dimensions. Moreover, the SC area, TM thickness, and SS length were significantly and positively associated with AST in the healthy group. Thus, AST might play an important role in maintaining TM and SC morphology and further in the pathogenesis of POAG.

Understanding the relationship between probabilistic and deterministic prediction skills is of important significance for the study of seasonal forecasting and verification. Based on the Brier skill score methodology, we have previously found a theoretical relationship between the probabilistic resolution skill and the deterministic correlation (i.e., anomaly correlation; AC) skill and a lack of necessary or consistent relationship between the probabilistic reliability skill and the deterministic skill in dynamical seasonal prediction. Here, we further theoretically investigate the relationship between the probabilistic relative operating characteristic (ROC) skill and the deterministic skill. The ROC measures the discrimination attribute of probabilistic forecast quality, another important attribute besides the resolution and reliability. With some simplified assumptions, we first derive theoretical expressions for the hit and false-alarm rates that are basic ingredients for the ROC curve, then demonstrate a sole dependence of the ROC curve on the AC, and finally analytically derive a relationship between the related ROC score and the AC. Such a theoretically derived ROC-AC relationship is further examined using dynamical models’ ensemble seasonal hindcasts, which is well verified. The finding here along with our previous findings implies that the discrimination and resolution attributes of probabilistic seasonal forecast skill are intrinsically equivalent to the corresponding deterministic skill, while the reliability appears to be the fundamental attribute of the probabilistic skill that differs from the deterministic skill, which constitutes an understanding of the fundamental similarities and difference between the two types of seasonal forecasting skills and predictability and can offer important implications for the study of seasonal forecasting and verification.

Purpose To investigate the diagnostic capability of scleral spur length in discriminating eyes with primary open-angle glaucoma (POAG) from healthy eyes. Methods Seventy-eight eyes of 78 patients with POAG and 93 eyes of 93 age-, sex- and axial length-matched healthy subjects were included. The scleral spur length was measured using swept-source optical coherence tomography. Receiver operating characteristic (ROC) curves were derived based on the measurements. Results The scleral spur length was significantly shorter in POAG eyes compared with healthy eyes (Method I, 164.91 ± 23.36 vs. 197.60 ± 25.32 μm; Method II, 145.15 ± 16.59 vs. 166.95 ± 19.31 μm; Method III, 162.33 ± 22.83 vs. 185.12 ± 23.58 μm, respectively; all p p p = 0.009) groups. Conclusions The scleral spur length had a good discriminating capability between POAG and healthy eyes, and it could be a novel biomarker for POAG evaluation clinically.

Background Lung cancer is one of most common cancers worldwide, with a 5-year survival rate of less than 20%, which is mainly due to late-stage diagnosis. Noninvasive methods using 5-hydroxymethylation of cytosine (5hmC) modifications and fragmentation profiles from 5hmC cell-free DNA (cfDNA) sequencing provide an opportunity for lung cancer detection and management. Results A total of 157 lung cancer patients were recruited to generate the largest lung cancer cfDNA 5hmC dataset, which mainly consisted of 62 lung adenocarcinoma (LUAD), 48 lung squamous cell carcinoma (LUSC) and 25 small cell lung cancer (SCLC) patients, with most patients (131, 83.44%) at advanced tumor stages. A 37-feature 5hmC model was constructed and validated to distinguish lung cancer patients from healthy controls, with areas under the curve (AUCs) of 0.8938 and 0.8476 (sensitivity = 87.50% and 72.73%, specificity = 83.87% and 80.60%) in two distinct validation sets. Furthermore, fragment profiles of cfDNA 5hmC datasets were first explored to develop a 48-feature fragmentation model with good performance (AUC = 0.9257 and 0.822, sensitivity = 87.50% and 78.79%, specificity = 80.65% and 76.12%) in the two validation sets. Another diagnostic model integrating 5hmC signals and fragment profiles improved AUC to 0.9432 and 0.8639 (sensitivity = 87.50% and 83.33%, specificity = 90.30% and 77.61%) in the two validation sets, better than models based on either of them alone and performing well in different stages and lung cancer subtypes. Several 5hmC markers were found to be associated with overall survival (OS) and disease-free survival (DFS) based on gene expression data from The Cancer Genome Atlas (TCGA). Conclusions Both the 5hmC signal and fragmentation profiles in 5hmC cfDNA data are sensitive and effective in lung cancer detection and could be incorporated into the diagnostic model to achieve good performance, promoting research focused on clinical diagnostic models based on cfDNA 5hmC data. Graphical abstract

The von Neumann bottleneck and memory wall have posed fundamental limitations in latency and energy consumption of modern computers based on von Neumann architecture. In-memory computing represents a radical shift in the computer architecture that can address such problems by merging computing functions within the memory itself. In this article, we review the emerging nonvolatile memory devices, such as resistance-based and charge-based memory devices, that are explored for in-memory computing applications. We will provide an overview of the materials, mechanisms, and integration of these devices, and discuss the optimizations at the device and array levels that are required to better support in-memory computing. Recent progress in the application of in-memory computing in artificial neural networks, spiking neural networks, digital logic in memory as well as hardware security will also be discussed. Finally, we will discuss the remaining challenges in this field and potential pathways to address them.

Optimal fingerprinting is a standard method for detecting climate changes. Among the uncertainties taken into account by this method, one is the fact that the response to climate forcing is not known exactly, but in practice is estimated from ensemble averages of model simulations. This uncertainty can be taken into account using an Error-in-Variables model (or equivalently, the Total Least Squares method), and can be expressed through confidence intervals. Unfortunately, the predominant paradigm (likelihood ratio theory) for deriving confidence intervals is not guaranteed to work because the number of parameters that are estimated in the Error-in-Variables model grows with the number of observations. This paper discusses various methods for deriving confidence intervals and shows that the widely-used intervals proposed in the seminal paper by Allen and Stott are effectively equivalent to bias-corrected intervals from likelihood ratio theory. A new, computationally simpler, method for computing these intervals is derived. Nevertheless, these confidence intervals are incorrect in the “weak-signal regime”. This conclusion does not necessarily invalidate previous detection and attribution studies because many such studies lie in the strong-signal regime, for which standard methods give correct confidence intervals. A new diagnostic is introduced to check whether or not a data set lies in the weak-signal regime. Finally, and most importantly, a bootstrap method is shown to give correct confidence intervals in both strong- and weak-signal regimes, and always produces finite confidence intervals, in contrast to the likelihood ratio method which can give unbounded intervals that do not match the actual uncertainty.

The carrier screening effect occurs commonly in dielectric materials. It reduces the electric potential gradient, thus negatively affecting the functionality of resistive random access memory (RRAM) devices. An Au/ZnO film/Al-doped ZnO device fabricated in this work exhibited no resistive switching (RS), which was attributed to the carrier screening effect. Therefore, annealing was used for alleviating the screening effect, significantly enhancing the RS property. In addition, different on/off ratios were obtained for various bias values, and the screening effect was accounted for by investigating electron transport mechanisms. Furthermore, different annealing temperatures were employed to modulate the free carrier concentration in ZnO films to alleviate the screening effect. The maximal on/off ratio reached 105 at an annealing temperature of 600 °C, yielding the lowest number of free carriers and the weakest screening effect in ZnO films. This work investigates the screening effect in RS devices. The screening effect not only modulates the characteristics of memory devices but also provides insight into the mechanism of RS in these devices.

Performance modulation of ZnO optoelectronic devices in the presence of proper piezoelectric polarization charges has been widely reported, whereas relatively less work has been performed about the influence of photoexcitation on piezotronics. In this study, we experimentally investigated the performance evolution of ZnO piezotronic strain sensor under various 365 nm UV irradiation densities. The device demonstrated a response ratio of ~200 under no illumination and under −0.53% compressive strain, and the response time is approximately 0.3 s. However, tremendous performance degradation was observed with the increase in the illumination density, which is attributed to the UV-modulated change in the free electron concentration and Schottky barrier height. It was observed that increased carrier density intensifies the screening effect and thus, the modulation ability of piezo-polarization charges weakens. Meanwhile, the deterioration of rectifying behavior at the interface under UV illumination also jeopardizes the device performance.

Sandwich-style memristor devices were synthesized by electrochemical deposition with a ZnO film serving as the active layer between Al-doped ZnO (AZO) and Au electrodes. The carrier concentration of the ZnO films is controlled by adding HNO3 during the growth process. A resulting increase in carrier concentration from 1017 to 1019 cm–3 was observed, along with a corresponding drop in the on–off ratio from 6,437% to 100%. The resistive switching characteristics completely disappeared when the carrier concentration was above 1019 cm–3, making it unsuitable for a memory device. The decreasing switching ratio is attributed to a reduction in the driving force for oxygen vacancy drift. Systematic analysis of the migration of oxygen vacancies is presented, including the concentration gradient and electrical potential gradient. Such oxygen vacancy migration dynamics provide insight into the mechanisms of the oxygen vacancy drift and provide valuable information for industrial production of memristor devices.

Photoanodes, which are used in photoelectrochemical (PEC) water splitting, have been shown to be applicable in the construction of a PEC biosensing platform. This was realized by replacing water oxidization with oxidation of an appropriate test molecule. Here, we have demonstrated the feasibility of adopting photoanodes consisting of zinc oxide nanorods arrays decorated with plasmonic gold nanoparticles (Au NPs@ZnO NRs) for the self-powered PEC bioanalysis of glutathione (GSH) in phosphate-buffered saline (PBS) at an applied bias potential of 0 V vs. Ag/AgCl. This heterostructure exhibited enhanced PEC properties because of the introduction of the Au/ZnO interface. Under visible light illumination, hot electrons from surface-plasmon resonance (SPR) at the Au NP surface were injected into the adjacent ZnO and subsequently driven to the photocathode. Under ultraviolet (UV) light illumination, the photogenerated electrons in ZnO tended to transfer to the fluorine-doped tin oxide due to the step-wise energy band structure and the upward energy band bending at the ZnO/ electrolyte interface. These results indicate that plasmonic metal/semiconductor heterostructure photoanodes have great potential for self-powered PEC bioanalysis applications and extended field of other photovoltaic beacons.

We developed and demonstrated a ZnO/ZnS/Au composite photoanode with significantly enhanced photoelectrochemical water-splitting performance, containing a ZnS interlayer and Au nanoparticles. The solar-to-hydrogen conversion efficiency of this ZnO/ZnS/Au heterostructure reached 0.21%, 3.5 times that of pristine ZnO. The comparison of the incident photon-to-current efficiency (IPCE) and the photoresponse in the white and visible light regions further verified that the enhancement resulted from contributions of both UV and visible light. The modification of the Au NPs was shown to improve the photoelectrochemical (PEC) performance to both UV and visible light, as modification encouraged effective surface passivation and surface-plasmonresonance effects. The ZnS interlayer favored the movement of photogenerated electrons under UV light and hot electrons under visible light, causing their injection into ZnO; this simultaneously suppressed the electron-hole recombination at the photoanode-electrolyte interface. The optimized design of the interlayer within plasmonic metal/semiconductor composite systems, as reported here, provided a facile and compatible photoelectrode configuration, enhancing the utilization efficiency of incident light for photoelectrochemical applications.

Gold nanoparticle (Au NP)@ZnO nanorod (NR) (Au@ZnO) hybrids with various ZnO:Au molar ratios were developed to enhance the generation of reactive oxygen species (ROS) in photodynamic therapy (PDT) applications. Introducing a metal/semiconductor heterostructure interface between Au NPs and ZnO NRs modulated electron transfer under ultraviolet (UV) irradiation, which dramatically suppressed the electron-hole recombination in ZnO and simultaneously increased the amount of excited electrons with high energy at Au NP surfaces. Hence, the ROS yield of the nanohybrid was considerably improved over those of pristine Au NPs or ZnO NRs alone and demonstrated a “1 + 1 > 2 effect.” This enhancement was strengthened with increases in the proportion of Au in the hybrid. The results showed that the Au@ZnO nanohybrids with a ZnO:Au ratio of 20:1 generated the highest ROS yield because they had the largest interface area between Au and ZnO, which in turn led to the lowest cell viability for HeLa and C2C12 cells during PDT. Furthermore, both ROS generation and cell destruction were positively correlated with nanohybrid dosage. The Au@ZnO hybrid (20:1, 100 μg/mL) resulted in HeLa cell viability as low as 28% after UV exposure for 2 min, which indicated its promising potential to improve the therapeutic efficacy of PDT.

Biosensing has developed tremendously since it was demonstrated by Leland C. Clark Jr. in 1962. ZnO nanomaterials are attractive candidates for fabricating biosensors, because of their diverse range of nanostructures, high electron mobility, chemical stability, electrochemical activity, high isoelectric points which promote enzyme adsorption, biocompatibility, and piezoelectric properties. This review covers ZnO nanostructures applied in enzyme biosensors, in the light of electrochemical transduction and field effect transduction. Different assembly processes and immobilization methods have been used to load enzymes into various ZnO nanostructures, providing enzymes with favorable micro-environments and enhancing their sensing performance. We briefly describe recent trends in ZnO syntheses, and the analytical performance of the fabricated biosensors, summarize the advantages of using ZnO nanostructures in biosensors, and conclude with future challenges and prospects.

Black silicon (b-Si) is a surface-nanostructured Si with extremely efficient light absorption capability and is therefore of interest for solar energy conversion. However, intense charge recombination and low electrochemical stability limit the use of b-Si in photoelectrochemical solar-fuel production. Here we report that a conformal, ultrathin, amorphous TiO2 film deposited by low-temperature atomic layer deposition (ALD) on top of b-Si can simultaneously address both of these issues. Combined with a Co(OH)2 thin film as the oxygen evolution catalyst, this b-Si/TiO2/Co(OH)2 heterostructured photoanode was able to produce a saturated photocurrent density of 32.3 mA cm−2 at an external potential of 1.48 V versus reversible reference electrode (RHE) in 1 M NaOH electrolyte. The enhanced photocurrent relative to planar Si and unprotected b-Si photoelectrodes was attributed to the enhanced charge separation efficiency as a result of the effective passivation of defective sites on the b-Si surface. The 8-nm ALD TiO2 layer extends the operational lifetime of b-Si from less than half an hour to four hours. Nanostructured black silicon can be used as a photoelectrode for solar-driven water splitting, but its high surface area can increase charge recombination and accelerate corrosion. Here the authors show that a thin, conformal film of TiO2 can increase both the photocurrent and the stability of black silicon.

We report on an enzymatic electrochemical glucose biosensor based on the use of zinc oxide nanorods (ZnO NRs) modified with gold nanoparticles (Au-NPs) and arranged in the form of an array. The nanorods were obtained via a hydrothermal method, and the Au-NPs were synthesized by photo-reduction. The surface of the nanoarrays was then modified with Au-NPs via electrostatic self-assembly. GOx was immobilized onto the surface of Au-NPs modified ZnO nanoarrays by electrostatic adsorption. The performance of the resulting glucose biosensors were investigated by cyclic voltammetry and amperometry. Compared to biosensors based on ZnO nanoarrays without Au-NPs, the ones described here exhibit a higher sensitivity (43.7 nA cm−2 mM−1) and a lower K app,M (0.78 mM). It is obvious, therefore, that the Au-NPs play an important role with respect to the performance of this biosensor.

In this study, the potential predictability of the Northern America (NA) surface air temperature (SAT) was explored using an information-based predictability framework and two multiple model ensemble products: a one-tier prediction by coupled models (T1), and a two-tier prediction by atmospheric models only (T2). Furthermore, the potential predictability was optimally decomposed into different modes for both T1 and T2, by extracting the most predictable structures. Emphasis was placed on the comparison of the predictability between T1 and T2. It was found that the potential predictability of the NA SAT is seasonal and spatially dependent in both T1 and T2. Higher predictability occurs in spring and winter and over the southeastern US and northwestern Canada. There is no significant difference of potential predictability between T1 and T2 for most areas of NA, although T1 has higher potential predictability than T2 in the southeastern US. Both T1 and T2 display similar most predictable components (PrCs) for the NA SAT, characterized by the inter-annual variability mode and the long-term trend mode. The first one is inherent to the tropical Pacific sea surface temperature forcing, such as the El Nino-Southern Oscillation, whereas the second one is closely associated with global warming. In general, the PrC modes can better characterize the predictability in T1 than in T2, in particular for the inter-annual variability mode in the fall. The prediction skill against observations is better measured by the PrC analysis than by principal component analysis for all seasons, indicating the stronger capability of PrCA in extracting prediction targets.

The ability to arbitrarily regulate semiconductor interfaces provides the most effective way to modulate the performance of optoelectronic devices. However, less work has been reported on piezo-modulated interface engineering in all-oxide systems. In this paper, an enhanced photoresponse of an all-oxide Cu2O/ZnO heterojunction was obtained by taking advantage of the piezotronic effect. The illumination density-dependent piezoelectric modulation ability was also comprehensively investigated. An 18.6% enhancement of photoresponse was achieved when applying a −0.88% compressive strain. Comparative experiments confirmed that this enhancement could be interpreted in terms of the band modification induced by interfacial piezoelectric polarization. The positive piezopotential generated at the ZnO side produces an increase in space charge region in Cu2O, thus providing an extra driving force to separate the excitons more efficiently under illumination. Our research provides a promising method to boost the performance of optoelectronics without altering the interface structure and could be extended to other metal oxide devices.

ZnO nanomaterials have been shown to have novel applications in optoelectronics, energy harvesting and piezotronics, due to their coupled semiconducting and piezoelectric properties. Here a functional nanogenerator (FNG) based on ZnO nanowire arrays has been fabricated, which can be employed to detect vibration in both self-powered (SP) and external-powered (EP) modes. In SP mode, the vibration responses of the FNG can be measured through converting mechanical energy directly into an electrical signal. The FNG shows consistent alternating current responses (relative error < 0.37%) at regular frequencies from 1 to 15 Hz. In EP mode, the current responses of FNG are significantly enhanced via the piezotronic effect. Under a forward bias of 3 V, the sensor presented a sensitivity of 3700% and an accurate measurement (relative error < 0.91%) of vibration frequencies in the range 0.05–15 Hz. The results show that this type of functional nanogenerator sensor can detect vibration in both SP and EP modes according to the demands of the applications.

We describe the use of individual zinc oxide (ZnO) micro/nanowires in an electrochemical biosensor for uric acid. The wires were synthesized by chemical vapor deposition and possess uniform morphology and high crystallinity as revealed by scanning electron microscopy, X-ray diffraction, and photoluminescence studies. The enzyme uricase was then immobilized on the surface of the ZnO micro/nanowires by physical adsorption, and this was proven by Raman spectroscopy and fluorescence microscopy. The resulting uric acid biosensor undergoes fast electron transfer between the active site of the enzyme and the surface of the electrode. It displays high sensitivity (89.74 μA cm−2 mM−1) and a wide linear analytical range (between 0.1 mM and 0.59 mM concentrations of uric acid). This study also demonstrates the potential of the use of individual ZnO micro/nanowires for the construction of highly sensitive nano-sized biosensors.

One-dimensional zinc oxide nanorods array exhibit excellent electron mobility and thus hold great potential as photoanode for photoelelctrochemical water splitting. However, the poor absorption of visible light and the prominent surface recombination hider the performance improvement. In this work, Au nanoparticles and aluminium oxide were deposited onto the surface of ZnO nanorods to improve the PEC performance. The localized surface plasmon resonance of Au NPs could expand the absorption spectrum to visible region. Simultaneously, the surface of passivation with Au NPs and Al2O3 largely suppressed the photogenerated electron-hole recombination. As a result, the optimal solar-to-hydrogen efficiency of ZnO/Au/Al2O3 with 5 cycles was 6.7 times that of pristine ZnO, ascribed to the synergistic effect of SPR and surface passivation. This research reveals that the synergistic effect could be used as an important method to design efficient photoanodes for photoelectrochemical devices.

We have engineered the electronic structure at the interface between Cu2O and ZnO nanorods (NRs) array, through adjusting the carrier concentration of Cu2O. The electrodeposition of Cu2O at pH 11 acquired the highest carrier concentration, resulting in the largest interfacial electric field between Cu2O and ZnO, which finally led to the highest separation efficiency of photogenerated charge carriers. The optimized Cu2O/ZnO NRs array p-n heterostructures exhibited enhanced PEC performance, such as elevated photocurrent and photoconversion efficiency, as well as excellent sensing performance for the sensitive detection of glutathione (GSH) in PBS buffer even at applied bias of 0 V which made the device self-powered. Besides, the favorable selectivity, high reproducibility and extremely wide detection range, make such heterostructure a promising candidate for PEC biosensing applications, probably for the extended field of PEC water splitting or other solar photovoltaic beacons.

In this work, zinc oxide (ZnO) nanowires-based electrochemical biosensor is designed and fabricated for the detection of L-lactic acid. ZnO nanowires were successfully synthesized via the chemical vapor deposition method. The morphology and structure of the prepared products were characterized, and the average diameter of synthesized ZnO samples was 500 nm. The fluorescence characterization was performed to verify the immobilization of lactate oxidase onto the ZnO surface. Biosensors based on large-area ZnO nanowires were then constructed, and a series of electrochemical experiments showed that ZnO could provide the efficient electron transfer channel between the enzymic active sites and the electrode surface. The proposed electrochemical biosensor exhibited a sensitivity of 15.6 µA cm−2 mM−1, a wide linear range of 12 µM–1.2 mM with a low-detection limit of 12 µM for L-lactic acid detection. This study has indicated the potential applications for ZnO nanowires to construct the simple and economic nano-bio devices for the detection of biological species.

A facile and cost-effective fabrication approach of active strain sensor based on individual ZnO micro/nanowire was demonstrated. By connecting a ZnO micro/nanowire along polar growth direction with two Ag electrodes on flexible polystyrene (PS) substrate, the fabricated strain sensor was obtained as a typical M-S-M structure. The I-V characteristic of the device was highly sensitive to the strain caused by the obvious change of Schottky barrier height (SBH). Furthermore, both of the symmetric and asymmetric changes of the SBH at the source and drain were observed during device testing process. The respective contribution of piezoresistance effect and the piezoelectric effect to the change of SBHs were also systematically investigated.