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A 13-bit Time to Digital Converter is implemented using multiphase clock technique. Xilinx’s Virtex 5 FPGA platform is used to realize the TDC architecture. One PLL within the FPGA works as a clock synthesizer to multiply the reference clock to 500 MHz. Then the combination of PLL and DLL topologies are used to generate 16 phases of the clock, separated by 11.25°. Further, 16 phases are generated by inverting the first 16 phases. A resolution of 62.5 ps has been recorded. Measured INL and DNL are within 1 LSB. The present work is suitable for many critical applications due to its PVT insensitive and robust properties.

This study examines how the market share of dark venues changes at earnings announcements. Our analysis shows a statistically significant increase in dark market share in the weeks prior to, during, and following the earnings announcement. We also predict and find evidence that increases in dark market share around earnings announcements are higher for firms with high-quality accounting information. In addition, we find a positive relation between the change in dark market share and the speed of resolution of investor disagreement—a key dimension of informational efficiency, which suggests that dark trading is associated with an improvement in market quality. How market fragmentation changes around news events, the role accounting information plays in market fragmentation, and how changes in market fragmentation relate to market quality can help provide insights to securities regulators. JEL Classifications: G12; G14; D47; M41.

In this paper, a novel optical rotary sensor based on laser self-mixing interferometry is developed for the full-circle rotation measurement. The proposed sensor is convenient to use for it does not need any contact with the target or a cooperative mirror. A prototype is fabricated and tested. The measured results demonstrate a good performance compared with other optical rotary sensors, in terms of the 0.1 μrad resolution, the 2.33×10-4 linearity and 2 μrad stability over one hour. Additionally, the repeatability error is below 14.66 mrad under 9-group full-circle tests, which exhibits the potential to be instrumentalized reliably. Error analysis and limitation discussion have been also carried out. Although the accuracy needs further improvement compared with the best rotary sensor, this method has its unique advantages of high resolution, non-cooperative target sensing and electromagnetic immunity. Hence, the proposed optical rotary sensor provides a promising alternative in precise rotation measurement, tremor tracing and nano-motion monitoring.In this paper, a novel optical rotary sensor based on laser self-mixing interferometry is developed for the full-circle rotation measurement. The proposed sensor is convenient to use for it does not need any contact with the target or a cooperative mirror. A prototype is fabricated and tested. The measured results demonstrate a good performance compared with other optical rotary sensors, in terms of the 0.1 μrad resolution, the 2.33×10-4 linearity and 2 μrad stability over one hour. Additionally, the repeatability error is below 14.66 mrad under 9-group full-circle tests, which exhibits the potential to be instrumentalized reliably. Error analysis and limitation discussion have been also carried out. Although the accuracy needs further improvement compared with the best rotary sensor, this method has its unique advantages of high resolution, non-cooperative target sensing and electromagnetic immunity. Hence, the proposed optical rotary sensor provides a promising alternative in precise rotation measurement, tremor tracing and nano-motion monitoring.

Tomographic imaging with radionuclides commonly used in nuclear medicine, such as $^{111}$In (171 and 245 keV) and $^{131}$I (364 keV), is in high demand for medical applications and small animal imaging. The Si/CdTe Compton camera with its high angular and high energy resolutions is an especially promising detector to extend the energy coverage for imaging to the range that covers gamma-ray emitted from these radionuclides. Here, we take the first steps towards short-distance imaging by conducting experiments using three-dimensional phantoms composed of multiple sphere-like solutions of $^{111}$In and $^{131}$I with a diameter of 2.7 mm, placed at a distance of 41 mm. Using simple back-projection methods, the positions of the sources are reproduced with a spatial resolution of 11.5 mm and 9.0 mm (FWHM) for $^{111}$In and $^{131}$I, respectively. We found that a LM-MLEM method gives a better resolution of 4.0 mm and 2.7 mm (FWHM). We resolve source positions of a tetrahedron structure with a source-to-source separation of 28 mm. These findings demonstrate that Compton Cameras have the potential of close-distance imaging of radioisotopes distributions in the energy range below 400 keV.

Understanding of nanoplastic prevalence and toxicology is limited by imaging challenges resulting from their small size. Fluorescence microscopy is widely applied to track and identify microplastics in laboratory studies and environmental samples. However, conventional fluorescence microscopy, due to diffraction, lacks the resolution to precisely localize nanoplastics in tissues, distinguish them from free dye, or quantify them in environmental samples. To address these limitations, we developed techniques to label nanoplastics for imaging with Stimulated Emission Depletion (STED) microscopy to achieve resolution at an order of magnitude superior to conventional fluorescence microscopy. These techniques include (1) passive sorption; (2) swell incorporation; and (3) covalent coupling of STED-compatible fluorescence dyes to nanoplastics. We demonstrate that our labeling techniques, combined with STED microscopy, can be used to resolve nanoplastics of different shapes and compositions as small as 50 nm. The longevity of the dye labeling is demonstrated in different media and conditions of biological and environmental relevance. We also test STED imaging of nanoplastics in exposure experiments with the model worm C. elegans. These techniques will allow more precise localization and quantification of nanoplastics in complex matrices.SynopsisWe show that Stimulated Emission Depletion (STED) microscopy can be used to image single nanoplastics of different compositions and shapes. This will allow researchers to study environmentally-relevant nanoplastics and their interactions with organisms in relevant exposure scenarios.TOC Graphic

This paper presents a temperature sensor suitable for heavily duty-cycled wireless sensor node. To achieve both a fine resolution and a fast conversion time, the proposed temperature sensor embeds a RC network in a 16-bit residue-integrated successive approximation register (SAR) analog-to-digital conversion (ADC). A poly resistor is connected in series with the capacitor digital-to-analog converter (DAC) to develop a temperature-dependent ADC input. The proposed temperature sensor, implemented in 180nm CMOS, achieves a resolution of 20mK in a range of -30-to-100∘C. It shows a resolution figure-of-merit of 3pJ∙K2 while supporting a burst operation in a conversion time of 12μs after wake-up.

This paper reports a high-performance, low-power temperature sensor suitable for wireless IoT devices/RFID tags. The system utilizes a mostly digital approach to achieve energy-efficient, sub-μW operation with a resistor-based temperature sensor. A sampled, incomplete-settling, switched-capacitor-based Wheatstone bridge is read out using a digital frequency-locked loop (DFLL) while harnessing the quasi-periodic limit cycles to reduce in-band noise. Implemented in a 65 nm CMOS process, it consumes 310 nW and achieves 9.8 mK resolution in a 10 ms conversion time. This results in a 297 fJ∙K2 figure-of-merit (FoM) and low energy (3.1 nJ/meas.).

This work aims to assess the performance of state-of-the-art global climate models in representing the upper-tropospheric Rossby wave pattern in the Northern Hemisphere and over the European–Atlantic sector. A diagnostic based on finite-amplitude local wave activity is used as an objective metric to quantify the amplitude of Rossby waves in terms of Rossby wave activity. This diagnostic framework is applied to a set of coupled historical climate simulations at different horizontal resolutions, performed in the framework of the PRIMAVERA project and compared with observations (ERA5 reanalysis). At first, the spatio-temporal characteristics of Rossby wave activity in the Northern Hemisphere are examined in the multimodel mean of the whole PRIMAVERA set. When examining the spatial distribution of transient wave activity, only a minimal improvement is found in the high-resolution ensemble. On the other hand, when examining the temporal variability of wave activity, a higher resolution is beneficial in all models apart from one. In addition, when examining the Rossby wave activity time series, no evident trends are found in the historical simulations (at both standard and high resolutions) and in the observations. Finally, the spatial distribution of Rossby wave activity is investigated in more detail focusing on the European–Atlantic sector, examining the wave activity pattern associated with weather regimes for each model. Results show a marked inter-model variability in representing the correct spatial distribution of Rossby wave activity associated with each regime pattern, and an increased horizontal resolution improves the models' performance only for some of the models and for some of the regimes. A positive impact of an increased horizontal resolution is found only for the models in which both the atmospheric and oceanic resolution is changed, whereas in the models in which only the atmospheric resolution is increased, a worsening model performance is detected.

Massive data growth is accelerating the need for storage. Hard Disk Drive read/write technology continues to advance to support this demand. This Advanced Storage Research Consortium report combines a top-down (system) and bottom-up (micromagnetic) approach to define a reader technology roadmap for 2.4, 4.0 and 6.0 Tbpsi including dimensional and performance targets. We examine the resolution, SNR, stability and manufacturing requirements, challenges, and gaps. We show that the extension of today’s Spin Valve-based reader designs may enable 4Tbpsi, but significant gaps must be closed. For higher Areal Densities, we review future reader designs, challenges, and discuss potential solution paths.

It is challenging to investigate fast supramolecular processes due to the lack of appropriate characterization methods with high structural resolution. In thisstudy, microfluidic nuclear magnetic resonance (μFNMR) spectroscopy was employed to monitor the kinetics of threading and dethreading of a pseudo[6]rotaxane system. By employing high time resolution μF-NMR, 1H and two-dimensional (2D) rotating frame nuclear Overhauser effect spectroscopy (ROESY) NMR spectra were recorded at any timepoint within 1.5 s after the onset of the process. This technique enabled the successful identification of kinetic intermediates and rate-determining steps,usually impossible to determine by other spectroscopic techniques. Thus, our study demonstrates the capability of μF-NMR in investigating the mechanismof complex supramolecular systems.

Osteolytic lesions (OL) characterize symptomatic multiple myeloma. The mechanisms of how malignant plasma cells (PC) cause OL in one region while others show no signs of bone destruction despite subtotal infiltration remain unknown. We report on a single-cell RNA sequencing (scRNA-seq) study of PC obtained prospectively from random bone marrow aspirates (BM) and paired imaging-guided biopsies of OL. We analyze 148,630 PC from 24 different locations in 10 patients and observe vast inter- and intra-patient heterogeneity based on scRNA-seq analyses. Beyond the limited evidence for spatial heterogeneity from whole-exome sequencing, we find an additional layer of complexity by integrated analysis of anchored scRNA-seq datasets from the BM and OL. PC from OL are characterized by differentially expressed genes compared to PC from BM, including upregulation of genes associated with myeloma bone disease like DKK1, HGF and TIMP-1 as well as recurrent downregulation of JUN/FOS, DUSP1 and HBB. Assessment of PC from longitudinally collected samples reveals transcriptional changes after induction therapy. Our study contributes to the understanding of destructive myeloma bone disease.

Optical anti-counterfeiting and encryption have become a hotspot in information security. However, the advanced optical anti-counterfeiting technology still suffers from low security by single-luminescent mode. Herein, we present a novel multi-mode anti-counterfeiting strategy based on K3LuSi2O7: Tb3+/Bi3+ (KLSO: Tb3+/Bi3+) phosphors for the first time. KLSO not only provides various lattice sites for Bi3+ ions occupying to achieve tunable luminescence but can also be non-equivalently substituted by Tb3+ ions to produce persistent or thermo-luminescence. Furthermore, in the pattern "8888" constructed by the mixture of polyacrylic acid (PAA) with KLSO: Tb3+/Bi3+ phosphors, we selectively trigger the three luminescent modes of Bi3+ and Tb3+ ions to realize the design of differential display in the fields of thermal response, time resolution, and luminescence color for optical anti-counterfeiting. The differentiated display can only be presented under specific multi-stimuli response, which further improves the security of information. Our work provides a new insight for designing advanced materials and can be expected to inspire future studies to explore optical anti-counterfeiting technology.

This article presents a torsional harmonic Kelvin probe force microscopy (TH-KPFM) working in amplitude modulation (AM) mode for high-sensitivity mapping of surface potential (SP). Compared with frequency modulation KPFM with higher spatial resolution, AM-KPFM has higher potential sensitivity and scanning speed. However, the traditional AM-KPFM is usually limited in the crosstalk from topography measurement and cantilever homogenization effect which causes the measured SP to be seriously affected by the substrate. TH-KPFM can effectively suppress the artifacts induced by the cantilever homogenization effect, and the coupling crosstalk caused by the topography measurement. The torsional harmonic cantilever suitable for TH-KPFM is fabricated and calibrated using the nanorobotic system first. Then, this technique is applied to determine the SP of the tobacco mosaic virus (TMV), and detect surface contaminants of a silicon wafer. Experimental results show that TH-KPFM has a 3 $\sim$ 4 mV energy resolution and sub-20 nm spatial resolution. Compared with the proposed TH-KPFM, the energy level of TMV obtained by the traditional AM-KPFM is pulled down by 80 meV. TH-KPFM is a powerful and useful technique to study the SP on the nanoscale, and greatly simplifies the difficulty of high-sensitivity measurement of the actual SP of many important nanoscale systems.

This study analyzes a relatively high resolution (15km grid spacing), regional coupled ocean-atmosphere simulation configured over Central America. The simulation is forced with global atmospheric and oceanic reanalysis for a period of 25 years (1986-2010). The spatial resolution and the time period of the Regional Climate Model (RCM) simulation are both unprecedented for the region. The highlights of the RCM simulation include the verifiable seasonal cycle of mesoscale features like the low level jets, the mid-summer drought and the seasonal tropical cyclone activity both in the Pacific and in the Atlantic Oceans. Similarly, the seasonal cycle of the robust surface ocean currents in the eastern Pacific and the Costa Rica Dome is also well captured in the RCM simulation. The RCM simulation also resolves the seasonal cycle of the Panama-Colombia Gyre, the Gulf of Papagayo and the Gulf of Tehuantepec Gyre. In many instances we find the RCM improves upon the global reanalysis forcing the simulation, indicating the potential value of dynamic downscaling. Furthermore, the co-evolving components of the atmosphere and ocean in the RCM is an added benefit to the atmosphere only and ocean only global reanalysis forcing the simulation. However, the model displays significant biases that manifest in precipitation, precipitable water, SST and winds which could potentially be improved.

Coreference resolution systems aim to recognize and cluster together mentions of the same underlying entity. While there exist large amounts of research on broadly spoken languages such as English and Chinese, research on coreference in other languages is comparably scarce. In this work we first present SentiCoref 1.0 - a coreference resolution dataset for Slovene language that is comparable to English-based corpora. Further, we conduct a series of analyses using various complex models that range from simple linear models to current state-of-the-art deep neural coreference approaches leveraging pre-trained contextual embeddings. Apart from SentiCoref, we evaluate models also on a smaller coref149 Slovene dataset to justify the creation of a new corpus. We investigate robustness of the models using cross-domain data and data augmentations. Models using contextual embeddings achieve the best results - up to 0.92 average F1 score for the SentiCoref dataset. Cross-domain experiments indicate that SentiCoref allows the models to learn more general patterns, which enables them to outperform models, learned on coref149 only.

Thin interbeds, which are made of several thin layers, are critical geological structures in seismic exploration. Due to the limited seismic resolution, thin interbeds cannot be easily analyzed with the standard time analysis or frequency analysis from a seismic dataset. Time-frequency analysis is a powerful technique for analyzing a non-stationary signal in the time and frequency domains simultaneously. Although it is tough to use the time-frequency tool to estimate the thin layer’s thickness, time-frequency analysis still has much potential for analyzing seismic thin interbeds from seismic data. The high-order synchrosqueezing transform has a significantly higher time-frequency resolution than the linear time-frequency transform and some commonly-used synchrosqueezing transforms. In this study, we propose to utilize the high-order synchrosqueezing transform to extract the TF features of thin interbeds’ seismic response. The TF analysis on the seismic response of cyclic thin interbeds shows that the thickness variation in thin interbeds causes a clear increasing (or decreasing) frequency curve in the TF plane. A seismic data example based on the Marmousi2 model demonstrates the proposed method can reflect the thickness variation with the depth. One real seismic data example has shown that the high-order synchrosqueezing transform can specifically extract the frequency component and be used to characterize the thickness variation, which is verified by two well’s velocity logs.

In this paper, we report design and preliminary performance evaluation of a CdTe detector module for use in an MR-compatible preclinical SPECT system. The detector module consists of four CdTe detectors. Each of them has a CdTe crystal with a dimension of 1.125 cm × 2.25 cm × 2 mm (thickness). The crystal anode side is divided into 32 × 64 square pixels with a width of 350 μm and attached to a custom-designed energy-resolved photon-counting (ERPC) ASIC. The ERPC CdTe detector module has a median energy resolution of 7.0 keV across 8192 (4 × 32 × 64 ) pixels and 95% of the pixels have energy resolution better than 9 keV inside a Siemens clinical 3-T MR scanner; it has a median detection efficiency of 0.47 and 95% of the pixels have detection efficiency between 0.44 and 0.49; the detector spatial resolution enables one to observe the point response function (PRF) distortion caused by a 3T magnetic field. An analytical method has been developed to model this distortion and the corresponding modeled PRF has a root of mean square error within 5%, compared to the experimental PRF.

The emerging optical multiplexing within nanoscale shows super-capacity in encoding information by using lifetime fingerprints from luminescent nanoparticles. However, the optical diffraction limit compromises the decoding accuracy and throughput of the nanoparticles during conventional widefield imaging. This, in turn, challenges the quality of nanoparticles to afford the modulated excitation condition and further retain the multiplexed optical fingerprints for super-resolution multiplexing. Here we report a tailor-made multiplexed super-resolution imaging method using the lifetime-engineered upconversion nanoparticles. We demonstrate that the nanoparticles are bright, uniform, and stable under structured illumination, which supports a lateral resolution of 185 nm, less than 1/4th of the excitation wavelength. We further develop a deep learning algorithm to coordinate with super-resolution images for more accurate decoding compared to a numeric algorithm. We demonstrate a three-channel super-resolution imaging based optical multiplexing with decoding accuracies above 93% for each channel and larger than 60% accuracy for potential seven-channel multiplexing. The improved resolution provides high throughput by resolving the particles within the diffraction-limited spots, which enables higher multiplexing capacity in space. This lifetime multiplexing super-resolution method opens a new horizon for handling the growing amount of information content, disease source, and security risk in modern society.

The data fusion technology aims to aggregate the characteristics of different data and obtain products with multiple data advantages. To solves the problem of reduced resolution of PolSAR images due to system limitations, we propose a fully polarimetric synthetic aperture radar (PolSAR) images and single-polarization synthetic aperture radar SAR (SinSAR) images fusion network to generate high-resolution PolSAR (HR-PolSAR) images. To take advantage of the polarimetric information of the low-resolution PolSAR (LR-PolSAR) images and the spatial information of the high-resolution single-polarization SAR (HR-SinSAR) images, we propose a fusion framework for joint LR-PolSAR images and HR-SinSAR images and design a cross-attention mechanism to extract features from the joint input data. Besides, based on the physical imaging mechanism, we designed the PolSAR polarimetric loss functions for constrained network training. The experimental results confirm the superiority of the fusion network over traditional algorithms. The average PSNR is increased by more than 3.6db, and the average MAE is reduced to less than 0.07. Experiments on polarimetric decomposition and polarimetric signature show that it maintains polarimetric information well.

Time-of-Flight positron emission tomography scanners demand fast and efficient photo sensors and scintillators coupled to fast readout electronics. This article presents the high resolution flexible Time-over-Threshold (HRFlexToT), a 16-channel application-specific-integrated circuit for silicon photomultipliers (SiPM) anode readout manufactured using XFAB 0.18- \mu \text{m} CMOS technology. The main features of the HRFlexToT are a linear Time-over-Threshold with an extended dynamic range (10 bits) for energy measurement, low power consumption (≈ 3.5 mW/ch), and an excellent timing response. The experimental measurements show an energy linearity error of ≈ 3% and an energy resolution of about 12% at 511 keV. Single-photon time resolution measurements performed using an Fondazione Bruno Kessler (FBK) SiPM NUV-HD ( 4 \times 4 mm2 pixel, 40- \mu \text{m} cell) and a Hamamatsu SiPM S13360-3050CS are around 142 and 167 ps full width at half maximum (FWHM), respectively. Coincidence time resolution (CTR) measurements with small cross-section pixelated crystals (LSO:Ce,Ca 0.4%, 2 \times 2 \times 5 mm3) coupled to the same Hamamatsu S13360-3050CS and FBK NUV-HD sensors yield a CTR of 117 ps and 119 ps, respectively. Measurements performed with a large cross-section monolithic crystal (LFS crystal measuring 25 \times 25 \times 20 mm3) and a Hamamatsu SiPM array S13361-6050NE-04 show a CTR of 324 ps FWHM after time-walk and time-skew correction.

High resolution surface temperature maps of a slotted surface grating laser operating at approx. 1550 nm are obtained by means of CCD-thermoreflectance imaging. The resolution is such that the temperature of the 2 µm wide ridge can be determined. Experimental temperature profiles along the ridge and in the lateral direction are provided. A 2D numerical model is developed to simulate the steady state thermal distributions in the laser. There is good agreement between the experiment and simulation. This technique allows for high-resolution imaging and will be useful where hot spots occur on laser devices.

Ultrasound localization microscopy (ULM) has been able to overcome the diffraction limit of ultrasound imaging. The resolution limit of ULM has been previously modeled using the Cramér-Rao lower bound (CRLB). While this model has been validated in a homogeneous medium, it estimates a resolution limit, which has not yet been achieved in vivo. In this work, we investigated the effects of three sources of image degradation on the resolution limit of ULM. The Fullwave simulation tool was used to simulate acquisitions of transabdominal contrast-enhanced data at depth. The effects of reverberation clutter, trailing clutter, and phase aberration were studied. The resolution limit, in the presence of reverberation clutter alone, was empirically measured to be up to 39 times worse in the axial dimension and up to 2.1 times worse in the lateral dimension than the limit predicted by the CRLB. While reverberation clutter had an isotropic impact on the resolution, trailing clutter had a constant impact on both dimensions across all signal-to-trailing-clutter ratios (STCR). Phase aberration had a significant impact on the resolution limit over the studied analysis ranges. Phase aberration alone degraded the resolution limit up to 70 and 160 [Formula: see text] in the lateral and axial dimensions, respectively. These results illustrate the importance of phase aberration correction and clutter filtering in ULM postprocessing. The analysis results were demonstrated through the simulation of the ULM process applied to a cross-tube model that was degraded by each of the three aforementioned sources of degradation.

To decipher the organizational logic of complex brain circuits, it is important to chart long-distance pathways while preserving micron-level accuracy of local network. However, mapping the neuronal projections with individual-axon resolution in the large and complex primate brain is still challenging. Herein, we describe a highly efficient pipeline for three-dimensional mapping of the entire macaque brain with subcellular resolution. The pipeline includes a novel poly-N-acryloyl glycinamide (PNAGA)-based embedding method for long-term structure and fluorescence preservation, high-resolution and rapid whole-brain optical imaging, and image post-processing. The cytoarchitectonic information of the entire macaque brain was acquired with a voxel size of 0.32 μm × 0.32 μm × 10 μm, showing its anatomical structure with cell distribution, density, and shape. Furthermore, thanks to viral labeling, individual long-distance projection axons from the frontal cortex were for the first time reconstructed across the entire brain hemisphere with a voxel size of 0.65 μm × 0.65 μm × 3 μm. Our results show that individual cortical axons originating from the prefrontal cortex simultaneously target multiple brain regions, including the visual cortex, striatum, thalamus, and midbrain. This pipeline provides an efficient method for cellular and circuitry investigation of the whole macaque brain with individual-axon resolution, and can shed light on brain function and disorders.

In scanning electron microscopy, the achievable image quality is often limited by a maximum feasible acquisition time per dataset. Particularly with regard to three-dimensional or large field-of-view imaging, a compromise must be found between a high amount of shot noise, which leads to a low signal-to-noise ratio, and excessive acquisition times. Assuming a fixed acquisition time per frame, we compared three different strategies for algorithm-assisted image acquisition in scanning electron microscopy. We evaluated (1) raster scanning with a reduced dwell time per pixel followed by a state-of-the-art Denoising algorithm, (2) raster scanning with a decreased resolution in conjunction with a state-of-the-art Super Resolution algorithm, and (3) a sparse scanning approach where a fixed percentage of pixels is visited by the beam in combination with state-of-the-art inpainting algorithms. Additionally, we considered increased beam currents for each of the strategies. The experiments showed that sparse scanning using an appropriate reconstruction technique was superior to the other strategies., Comment: submitted to Ultramicroscopy as a Full Length Article

Crystallographic twins are critical to the properties of numerous materials from magnesium alloys to piezoelectrics. Since the onset of the twin formation is highly sensitive to the triaxial mechanical boundary conditions, non-destructive bulk microscopy techniques are required. Elastic strains can be mapped via X-ray diffraction with a 100-200 nm resolution. However, the interplay of strains with nanotwins cannot be characterized. Here, a method based on dark-field X-ray microscopy to quantify the density of nanotwin variants with twin lamellae of sizes as small as several tens of nanometers in embedded subvolumes (70x200x600 nm3) in millimeter-sized samples is introduced. The methodology is corroborated by correlating the local density of twin variants to the long-ranging strain fields for a high-performance piezoelectric material. The method facilitates direct, in situ mapping and quantification of nanoscale structural changes together with their elastic driving fields, which is the key towards controlling and engineering material's performance at nanometric scales.

The presence of grain boundaries (GBs) has a great impact on the coefficient of thermal expansion (CTE) of polycrystals. However, direct measurement of local expansion of GBs remains challenging for conventional methods due to the lack of spatial resolution. In this work, we utilized the valence electron energy loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM) to directly measure the CTE of Σ5 and 45°GBs of SrTiO3 at a temperature range between 373 and 973 K. A CTE that was about 3 times larger was observed in Σ5 GB along the direction normal to GB plane, while only a 1.4 time enhancement was found in the 45° GB. Our result provides direct evidence that GBs contribute to the enhancement of CTE in polycrystals. Also, this work has revealed how thermodynamic properties are varied in different GB structures and demonstrated the potential of EELS for probing local thermal properties with nanometer-scale resolution.

Huntingtin-associated protein 1 (HAP1) is abundantly expressed in the neurons of the central nervous system and forms unique intracytoplasmic inclusions of unknown function called ‘stigmoid bodies’ (STBs). Transmission electron microscopy has revealed that the STBs are aggregates of granules containing cavities with a diameter of 0.5–3 µm. Small STBs fuse to form larger STBs, the size of which is said to vary depending on the developmental growth stage and brain region. Light microscopy can only reveal that these STBs have similar circular shapes due to its limited resolution. Therefore, light microscopy is only fit for the study of the STB distribution and quantitative changes. We, herein, suggest the adoption of correlative light and electron microscopy, which combines confocal laser scanning microscopy and scanning electron microscopy as the method allowing us to identify the huntingtin-associated protein 1–positive STBs in formalin-fixed paraffin-embedded (FFPE) sections. This approach allows us to study the three-dimensional morphology of immunolabeled objects in histopathological specimens. The STBs in FFPE sections of murine hypothalami reflected the transmission electron microscopic images of Epon-embedded STBs, although we were not able to observe any organelle covering the STBs of the FFPE sections. Furthermore, we were able to reconstruct the three-dimensional structure of the STB, and we identified it to be of spherical form, covered with mitochondria and rough endoplasmic reticulum, and bearing a cluster of cavities in the centre. In the future, we might gain new insights by comparing the three-dimensional structure of the STB between different neurons and under a variety of conditions.

Micropipette aspiration (MPA) is an essential tool in mechanobiology; however, its potential is far from fully exploited. The traditional MPA technique has limited temporal and spatial resolution and requires extensive post processing to obtain the mechanical fingerprints of samples. Here, we develop a MPA system that measures pressure and displacement in real time with sub-nanometer resolution thanks to an interferometric readout. This highly sensitive MPA system enables studying the nanoscale behavior of soft biomaterials under tension and their frequency-dependent viscoelastic response., Beradi et al. establish a micropipette aspiration platform which enables sensitive real-time viscoelastic measurements of soft biomaterials. They use it to characterize the rheological behavior of cells and soft materials at very small deformations, yielding consistent and reproducible values.

An adequate representation of the interaction between the land surface and the atmosphere is critical for both numerical weather prediction and climate models. The surface energy and mass balances are tightly coupled to the terrestrial water cycle, mainly through the state of soil moisture. An inadequate representation of the terrestrial water cycle will deteriorate the state of the land surface model and introduce biases to the atmospheric model. The validation of land surface models is challenging, as there are very few observations and the soil is highly heterogeneous. In this paper, a validation framework for land surface schemes based on catchment mass balances is presented. The main focus of our development lies in the application to kilometer-resolution numerical weather prediction and climate models, although the approach is scalable in both space and time. The methodology combines information from multiple observation-based datasets. Observational uncertainties are estimated by using independent sets of observations. It is shown that the combination of observation-based datasets and river discharge measurements close the water balance fairly well for the chosen catchments. As a showcase application, the framework is then applied to compare and validate four different versions of TERRA ML, the land surface scheme of the COSMO numerical weather prediction and climate model over five mesoscale catchments in Switzerland ranging from 105 to 1713 km2. Despite large observational uncertainties, validation results clearly suggest that errors in terrestrial storage changes are closely linked to errors in runoff generation and emphasize the crucial role of infiltration processes.

Super‐resolution fluorescence imaging provides critically improved information about the composition, organization, and dynamics of subcellular structures. Quantum dot triexciton imaging (QDTI) has been introduced as an easy‐to‐use sub‐diffraction imaging method that achieves an almost 2‐fold improvement in resolution when used with conventional confocal microscopes. Here, we report an overall 3‐fold increase in lateral and axial resolution compared to conventional confocal microscopes by combining QDTI with state‐of‐the‐art commercial laser scanning microscope systems., We report an overall 3‐fold increase in lateral and axial image resolution for confocal fluorescence microscopy by combining quantum dot triexciton imaging with state‐of‐the‐art commercial laser scanning microscope systems. Based on quantum dots as fluorescent labels, we present an easy‐to‐use super‐resolution method. A single confocal scan with minimal image post‐processing is sufficient to produce a sub‐diffraction image with an image resolution of approx. 80 nm lateral and 200 nm axial.

The use of very high-resolution digital pulse width modulators (DPWMs) for high frequency dc–dc converters has been steadily increasing in recent years. However, the resolution of the DPWM formed by counters and comparators is limited when the switching frequency rise above MHz range. Given this limitation, new strategies for DPWM architectures are being designed to increase the resolution of the signals. This article proposes two new DPWMs architectures with the aim of increasing the resolution of trigger signals using field programmable gate arrays (FPGAs). The first proposed architecture is a hybrid DPWM, which integrates a clock manager and a delay line. For this architecture, the delay line is configured using FPGA intellectual properties (IP) blocks. This delay stage allows a fine resolution in the picosecond scale. In addition, an alternative solution has been implemented to generate two signals, the main signal and its complementary one, including high resolution for the dead time, which is also configurable. Both architectures have been tested through static and dynamic tests on two FPGAs of different costs, an Artix-7 (low-cost) and a Kintex-UltraScale 7 (high-cost) by Xilinx.

We evaluate existing spike sorters and present a new one that resolves many sorting challenges. The new sorter, called “full binary pursuit” or FBP, comprises multiple steps. First, it thresholds and clusters to identify the waveforms of all unique neurons in the recording. Second, it uses greedy binary pursuit to optimally assign all the spike events in the original voltages to separable neurons. Third, it resolves spike events that are described more accurately as the superposition of spikes from two other neurons. Fourth, it resolves situations where the recorded neurons drift in amplitude or across electrode contacts during a long recording session. Comparison with other sorters on ground-truth data sets reveals many of the failure modes of spike sorting. We examine overall spike sorter performance in ground-truth data sets and suggest postsorting analyses that can improve the veracity of neural analyses by minimizing the intrusion of failure modes into analysis and interpretation of neural data. Our analysis reveals the tradeoff between the number of channels a sorter can process, speed of sorting, and some of the failure modes of spike sorting. FBP works best on data from 32 channels or fewer. It trades speed and number of channels for avoidance of specific failure modes that would be challenges for some use cases. We conclude that all spike sorting algorithms studied have advantages and shortcomings, and the appropriate use of a spike sorter requires a detailed assessment of the data being sorted and the experimental goals for analyses. NEW & NOTEWORTHY Electrophysiological recordings from multiple neurons across multiple channels pose great difficulty for spike sorting of single neurons. We propose methods that improve the ability to determine the number of individual neurons present in a recording and resolve near-simultaneous spike events from single neurons. We use ground-truth data sets to demonstrate the pros and cons of several current sorting algorithms and suggest strategies for determining the accuracy of spike sorting when ground-truth data are not available.

The paper presents an analytical model describing the dynamics of ion cloud, taking into account the action of space charge during a motion in ion mobility spectrometer — starting from the reaction region, where the shutter forms an ion pulse, and the further drift of the formed ion pulse towards the collector. The presented model lets to estimate the degree of influence of the space charge on possible ion losses and the resolution of ion mobility spectrometer. The effect of the space charge becomes noticeable, starting with the ion density of 106 cm–3. Comparison of the results obtained using the analytical model with the results of numerical solution of the initial equations shows that they practically coincide.

The weak X-ray capture capability of organic scintillators always leads to poor imaging resolution and detection sensitivity. Here, we realize an efficient and reabsorption-free organic scintillato...

Confocal microscopy1 remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching2. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues. A combination of multiview imaging, structured illumination, reconstruction algorithms and deep-learning predictions realizes spatial- and temporal-resolution improvements in fluorescence microscopy to produce super-resolution images from diffraction-limited input images.

In Taiwan, the heat island effect is the most significant in Taipei City. Thus this research provides a causal explanation for why urban outdoor air temperature has an M-shape EKC pattern for metropolitan areas in a country. Results show that the growth rate change in CO2 concentration can induce changes to the periods of the La Nino effect and EI Nino effect, causing high fluctuations in rain accumulation. The amount of rain then alters A-type evaporation, and so the evaporation amount is the top factor for the diffusion of a city’s heat. This fluctuation plays as a cooling and heating source for the V region of the M shape in the outdoor air temperature EKC pattern. In our previous studies, the growth rate change in CO2 concentration correlates to the energy structure. Therefore, a heat sinking model has been proposed to explain the accumulation of heat in a city, in which a proportion process for the solar irradiation source from buildings and remodeling engineering from a public housing policy and the private sector can play as a heating source of the two peaks of the M shape and present long-term linear growth in the outdoor air temperature EKC pattern.

The electrical double layer (EDL) at solid-liquid interfaces is key to interfacial transport and reaction processes and numerous emerging applications exploiting such processes. Herein, by studying hysteresis ion-transport processes in nanopipettes near charged substrates, we found the resulting cross-point potential (Vcp) to represent the surface potential of both nanopipettes and substrates. After the subtraction of Vcp in bulk solution, the remaining ΔVcp shows excellent exponential decay with respect to the separation distance from the substrates and agrees very well with the classical double-layer theory. The revealed new hysteresis ion transport in nanopipettes would provide a new way for the simple and direct EDL imaging of various interfaces of interest with nanoscale resolution in scanning ion conductance microscopy.

A user-friendly Python-based program has been developed to analyze diffuse scattering from single crystals with the reverse Monte Carlo method. The approach allows for refinement of correlated disorder from atomistic supercells with magnetic or structural (occupational and/or displacive) disorder., A user-friendly program has been developed to analyze diffuse scattering from single crystals with the reverse Monte Carlo method. The approach allows for refinement of correlated disorder from atomistic supercells with magnetic or structural (occupational and/or displacive) disorder. The program is written in Python and optimized for performance and efficiency. Refinements of two user cases obtained with legacy neutron-scattering data demonstrate the effectiveness of the approach and the developed program. It is shown with bixbyite, a naturally occurring magnetic mineral, that the calculated three-dimensional spin-pair correlations are resolved with finer real-space resolution compared with the pair distribution function calculated directly from the reciprocal-space pattern. With the triangular lattice Ba3Co2O6(CO3)0.7, refinements of occupational and displacive disorder are combined to extract the one-dimensional intra-chain correlations of carbonate molecules that move toward neighboring vacant sites to accommodate strain induced by electrostatic interactions. The program is packaged with a graphical user interface and extensible to serve the needs of single-crystal diffractometer instruments that collect diffuse-scattering data.