Standard Setup Research Articles

Reconfigurable nonlocal thin film nano-cavity for image processing

A combination of optical analog computing and nanophotonic design is attractive due to its fast-processing times, large data processing rates, and high integration with modern imaging systems. However, most of the proposed nano-photonics designs for this purpose have static functionality, which limits their applicability. By modulating the Green's function response of the thin film nanocavity using phase change properties of Sb2S3, we propose tunable bright and dark-field imaging. We optimize the nano-cavity for the bright field in a crystalline and dark field in the amorphous phase of Sb2S3. The proposed design shows a near-unity numerical aperture which enables the resolution of the system to ∼500 nm. Lastly, we examine the potential integration of this cavity into a standard interferometric setup and scattering microscopy, leveraging the tunable modulation capability of the proposed cavity as a substrate in reflection mode scheme. This ultrathin, on-chip, and real-time tunable lithographic-free imaging system can play a crucial role in a host of applications such as machine vision, medical imaging, and sensing.

Optimized signal of calcifications in wide-angle digital breast tomosynthesis: a virtual imaging trial.

Evaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach. Medio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers. For DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography. A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography. This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol. • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.

Dynamic, IPSC-derived hepatic tissue tri-culture system for the evaluation of liver physiology in vitro

Availability of hepatic tissue for the investigation of metabolic processes is severely limited. While primary hepatocytes or animal models are widely used in pharmacological applications, a change in methodology towards more sustainable and ethical assays is highly desirable. Stem cell derived hepatic cells are generally regarded as a viable alternative for the above model systems, if current limitations in functionality and maturation can be overcome. By combining microfluidic organ-on-a-chip technology with individually differentiated, multicellular hepatic tissue fractions, we aim to improve overall functionality of hepatocyte-like cells, as well as evaluate cellular composition and interactions with non-parenchymal cell populations towards the formation of mature liver tissue. Utilizing a multi-omic approach, we show the improved maturation profiles of hepatocyte-like cells maintained in a dynamic microenvironment compared to standard tissue culture setups without continuous perfusion. In order to evaluate the resulting tissue, we employ single cell sequencing to distinguish formed subpopulations and spatial localization. While cellular input was strictly defined based on established differentiation protocols of parenchyma, endothelial and stellate cell fractions, resulting hepatic tissue was shown to comprise a complex mixture of epithelial and non-parenchymal fractions with specific local enrichment of phenotypes along the microchannel. Following this approach, we show the importance of passive, paracrine developmental processes in tissue formation. Using such complex tissue models is a crucial first step to develop stem cell-derived in vitro systems that can compare functionally with currently used pharmacological and toxicological applications.

Prospective evaluation of patient-reported outcomes of invisible ink tattoos for the delivery of external beam radiation therapy: the PREFER trial.

Invisible ink tattoos (IITs) avoid cosmetic permanence of visible ink tattoos (VITs) while serving as more reliable landmarks for radiation setup than tattooless setups. This trial evaluated patient-reported preference and feasibility of IIT implementation. In an IRB-approved, single institution, prospective trial, patients receiving proton therapy underwent IIT-based treatment setup. A survey tool assessed patient preference on tattoos using a Likert scale. Matched patients treated using our institutional standard tattooless setup were identified; treatment times and image guidance requirements were evaluated between tattooless and IIT-based alignment approaches. Distribution differences were estimated using Wilcoxon rank-sum tests or Chi-square tests. Of 94 eligible patients enrolled, median age was 58 years, and 58.5% were female. Most common treatment sites were breast (18.1%), lung (17.0%) and pelvic (14.9%). Patients preferred to receive IITs versus VITs (79.8% pre-treatment and 75.5% post-treatment, respectively). Patients were willing to travel farther from home to avoid VITs versus IITs (p<0.01). Females were willing to travel (45.5% vs. 23.1%; p=0.04) and pay additional money to avoid VITs (34.5% vs. 5.1%; p<0.01). Per-fraction average +treatment time and time from on table/in room to first beam were shorter with IIT-based vs. tattooless setup (12.3min vs. 14.1min; p=0.04 and 24.1min vs. 26.2min; p=0.02, respectively). In the largest prospective trial on IIT-based radiotherapy setup to date, we found that patients prefer IITs to VITs. Additionally, IIT-based alignment is an effective and efficient strategy in comparison with tattooless setup. Standard incorporation of IITs for patient setup should be strongly considered.

Design and analysis of frequency selective surface embedded broadband high gain miniaturized antenna

SummaryIncorporating the better impedance matching capability of planar curved radiating patch, a miniaturized broadband planar antenna has been designed, analyzed, and integrated with frequency selective surface (FSS) to accomplish higher gain for various short‐range and long‐range modern wireless communication applications. Physical and electrical volume of the presented antenna is 25 × 20 × 1.6 and 0.25 × 0.20 × 0.016, respectively. The proposed radiating patch is constructed from a conventional rectangular patch by transforming the upper side of the patch into a semi‐circular shape and the lower side of the patch into a staircase‐like shape. Measured outcomes of the designed antenna show a very large operating bandwidth of 19.8 GHz (3–22.8 GHz) with a fractional bandwidth (FBW) of 153.5% and bandwidth dimension ratio (BDR) of 3070. An equivalent circuit model (ECM) of the proposed antenna is developed using an advanced design system (ADS) circuit simulator. The frequency responses of the ECM are compared with the simulation done by CST Microwave Studio Suite software and measurement results, which show good agreement. An FSS structure with stop band from 2–28 GHz is positioned beneath the proposed antenna at optimal position (27 mm below the antenna) to enhance the gain up to 8.9 dBi. The presented antenna and FSS are fabricated on FR4 substrate and experimentally verified using standard microwave measurement setup.

A unifying perspective on non-stationary kernels for deeper Gaussian processes

The Gaussian process (GP) is a popular statistical technique for stochastic function approximation and uncertainty quantification from data. GPs have been adopted into the realm of machine learning (ML) in the last two decades because of their superior prediction abilities, especially in data-sparse scenarios, and their inherent ability to provide robust uncertainty estimates. Even so, their performance highly depends on intricate customizations of the core methodology, which often leads to dissatisfaction among practitioners when standard setups and off-the-shelf software tools are being deployed. Arguably, the most important building block of a GP is the kernel function, which assumes the role of a covariance operator. Stationary kernels of the Matérn class are used in the vast majority of applied studies; poor prediction performance and unrealistic uncertainty quantification are often the consequences. Non-stationary kernels show improved performance but are rarely used due to their more complicated functional form and the associated effort and expertise needed to define and tune them optimally. In this perspective, we want to help ML practitioners make sense of some of the most common forms of non-stationarity for Gaussian processes. We show a variety of kernels in action using representative datasets, carefully study their properties, and compare their performances. Based on our findings, we propose a new kernel that combines some of the identified advantages of existing kernels.

Impact of Local Microenvironments on the Selectivity of Electrocatalytic Nitrate Reduction in a BPM‐MEA System

AbstractElectrochemical nitrate reduction reaction (NO3RR) has garnered increasing attention as a pathway for converting a harmful pollutant (nitrate) into a value‐added product (ammonia). However, high selectivity toward ammonia (NH3) is imperative for process viability. Optimizing proton availability near the catalyst is important for achieving selective NH3 production. Here, the aim is to systematically examine the impacts of proton availability on NO3RR selectivity in a bipolar membrane (BPM)‐based membrane electrode assembly (MEA) system. The BPM generates a proton flux from the membrane toward the catalyst during electrolysis. Thus, the BPM‐MEA system can modulate the proton flux during operation. The impact of interposer layers, proton scavenging electrolytes (CO32−), and catalyst configurations are also examined to identify which local microenvironments favor ammonia formation. It is found that a moderate proton supply allows for an increase in ammonia yield by 576% when compared to the standard MEA setup. This also results in a high selectivity of 26 (NH3 over NO2−) at an applied current density of 200 mA cm−2.

Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups.

Artificial intelligence (AI) has shown promise in the early detection of various cardiac conditions from a standard 12-lead electrocardiogram (ECG). However, the ability of AI to identify abnormalities from single-lead recordings across a range of pathological conditions remains to be systematically investigated. This study aims to assess the performance of a convolutional neural network (CNN) using a single-lead (D1) rather than a standard 12-lead setup for accurate identification of ECG abnormalities. We designed and trained a lightweight CNN to identify 20 different cardiac abnormalities on ECGs, using data from the PTB-XL dataset. With a relatively simple architecture, the network was designed to accommodate different combinations of leads as input (<100,000 learnable parameters). We compared various lead setups such as the standard 12-lead, D1 alone, and D1 paired with an additional lead. This has been corrected to “The CNN based on single-lead ECG (D1) achieved satisfactory performance compared to the standard 12-lead framework (average percentage AUC difference: −8.7%). Notably, for certain diagnostic classes, there was no difference in the diagnostic AUC between the single-lead and the standard 12-lead setups. When a second lead was detected in the CNN in addition to D1, the AUC gap was further reduced to an average percentage difference of -2.8% compared with that of the standard 12-lead setup. A relatively lightweight CNN can predict different classes of cardiac abnormalities from D1 alone and the standard 12-lead ECG. Considering the growing availability of wearable devices capable of recording a D1-like single-lead ECG, we discuss how our findings contribute to the foundation of a large-scale screening of cardiac abnormalities.

The Small-Amplitude Dynamics of Spontaneous Tropical Cyclogenesis. Part I: Experiments with Amplified Longwave Radiative Feedback

Abstract What determines the vortex size at the small-amplitude stage of spontaneous tropical cyclogenesis remains unclear. A doubly periodic domain is a standard setup for numerically studying this problem, but the convectively coupled standing waves inherent to the setup could directly trigger vortices, rendering an unrealistic path for tropical cyclogenesis. We increase the Coriolis parameter to suppress the wave and double the longwave radiative feedback to make the more realistic moisture–radiation instability dominant. Experiments show that the moisture–radiation instability has a short-wavelength cutoff due to the smoothing effect of convective dynamics, which includes the nonlocal convective triggering by cold pools and the nonlocal longwave radiative effect of anvil clouds. By approximating the spread of convective activity as a Gaussian filter on the column humidity, we derive a bulk convective spreading length lcp+av to parameterize the combined effect of cold pools and anvils. Using a novel diagnostic method, lcp+av is shown to be around 10 km. The contribution of cold pools and anvil clouds to convective spreading is comparable in the doubled radiative feedback experiments. An extrapolation to the normal radiative feedback state shows the anvil clouds play a smaller yet nonnegligible role.

Real-Time Patient Indoor Health Monitoring and Location Tracking with Optical Camera Communications on the Internet of Medical Things

Optical Camera Communication (OCC) is an emerging technology that has attracted research interest in recent decades. Unlike previous communication technologies, OCC uses visible light as the medium to transmit data from receivers and cameras to receive the data. OCC has several advantages that can be capitalized in several implementations. However, the Internet of Things (IoT) has emerged as a technology with immense potential. Numerous research endeavors support the IoT’s prospective technology that can be implemented in various sectors, including the healthcare system. This study introduces a novel implementation of the Internet of Medical Things (IoMT) system, using OCC for real-time health monitoring and indoor location tracking. The innovative system uses standard closed-circuit television CCTV setups, integrating deep learning-based OCC to monitor multiple patients simultaneously, each represented by an LED matrix. The effectiveness of the system was demonstrated through two scenarios: the first involves dual transmitters and a single camera, highlighting real-time monitoring of vital health data; the second features a transmitter with dual cameras, focusing patient movement tracking across different camera fields of view. To accurately locate and track the position of LED arrays in the camera, the system used YOLO (You Only Look Once). Data are securely transmitted to an edge server and stored using the REST API, with a web interface providing real-time patient updates. This study highlights the potential of OCC in IoMT for advanced patient care and proposes future exploration in larger healthcare systems and other IoT domains.

The Atmospheric Stability Dependence of Far Wakes on the Power Output of Downstream Wind Farms

Stability-dependent far-field offshore wind-farm wakes are detected in Supervisory Control and Data Acquisition (SCADA) wind power records from wind farms located in the North Sea. The results are used to assess the strengths and weaknesses of the Openwind engineering model, which in turn enables understanding of the wake signal captured by the SCADA data. Two experimental model set-ups are evaluated, the current standard set-up considering a neutral atmosphere and extended for stable conditions, and the other using a new atmospheric stability implementation called the far-wake atmospheric stability model (ASM) previously reported in Energies. The ASM approach enables the identification within wind power records of wakes of length at least 30 km depending on the atmospheric stability. The ASM approach would be useful for assessing which neighboring wind farms are likely to affect the wind turbine power output and to what extent the power output is affected by stability.

Statistical inference for wavelet curve estimators of symmetric positive definite matrices

In this paper we treat statistical inference for a wavelet estimator of curves of symmetric positive definite (SPD) using the log-Euclidean distance. This estimator preserves positive-definiteness and enjoys permutation-equivariance, which is particularly relevant for covariance matrices. Our second-generation wavelet estimator is based on average-interpolation (AI) and allows the same powerful properties, including fast algorithms, known from nonparametric curve estimation with wavelets in standard Euclidean set-ups. The core of our work is the proposition of confidence sets for our AI wavelet estimator in a non-Euclidean geometry. We derive asymptotic normality of this estimator, including explicit expressions of its asymptotic variance. This opens the door for constructing asymptotic confidence regions which we compare with our proposed bootstrap scheme for inference. Detailed numerical simulations confirm the appropriateness of our suggested inference schemes.

Recording Cilia Activity in Ctenophores.

Pelagic ctenophores swim in the water with the help of eight rows of long fused cilia. Their entire behavioral repertoire is dependent to a large degree on coordinated cilia activity. Therefore, recording cilia beating is paramount to understanding and registering the behavioral responses and investigating its neural and hormonal control. Here, we present a simple protocol to monitor and quantify cilia activity in semi-intact ctenophore preparations (using Pleurobrachia and Bolinopsis as models), which includes a standard electrophysiological setup for intracellular recording.

Improving CPAP Therapy with Superimposed Pressure Oscillation

Background: Continuous positive airway pressure (CPAP) is considered the gold standard therapy for Obstructive Sleep Apnea (OSA); however, many side effects, such as uncomfortable high titration pressure (TP) and mouth dryness, are associated with this treatment. This work proposes using pressure oscillations superimposed on a mean pressure to modulate the upper airways, reduce TP, and stimulate the salivary glands to reduce mouth dryness. Methods: Two nonconsecutive overnight randomized controlled clinical trials were designed, one with a standard CPAP setup but reduced TP and the other by adding superimposed pressure oscillations (SIPO) to the reduced TP CPAP setup. 33 OSA patients who usually received CPAP treatment with predetermined TP settings participated in the two trials. Complete polysomnography was performed for sleep and patient assessments. However, a spitting technique protocol was used on 15 randomly selected patients from the same group to investigate the effect of SIPO on mouth dryness. These trials are registered under ACTRN12622001518752. Results: The apnea-hypopnea index (AHI) was significantly reduced from 25.08 ± 2.32 to 17.56 ± 2.11 (p = 0.020*) with SIPO, indicating a 29.95% reduction in AHI and a decrease in breathing obstructions during enhanced therapy. Additionally, SIPO significantly decreased the oxygen desaturation index (ODI) (p = 0.002), maintaining the blood oxygen level within the normal range during the trials. ODI≥3 decreased significantly by 38.04% with SIPO. Saliva test results demonstrated that SIPO significantly increased saliva volume by 23.13% in non-stimulation and by 39.09% during stimulation compared to the CPAP trial. Conclusions: This work demonstrates that SIPO reduces the TP to 70% of its standard clinical setting and stimulates salivary secretion to reduce mouth dryness. Further, significant improvements in AHI, respiratory arousal index (RAI), Arousal index (AI), and sleep efficiency (SE) are observed. This work is proof of concept, and further trials should be undertaken to generalize the proposed technique.

Проточная ячейка для исследования кристаллизации на подложках

Recently, a flow-type cell has been innovatively designed for the detailed study of the precipitation process on various substrates. This unique cell allows the manipulation of critical parameters involved in biomineralization processes. Notably, the cell design permits 3D printing in a standard lab setup. It is equipped with transparent windows that enable the use of ex situ techniques to analyze precipitates once they have been extracted from the cell due to its convenient disassembling feature. Furthermore, the cell supports in situ methods of studying such as optical microscopy and X-ray diffraction. Two versions of the cell are available: one with passive mixing and the other with active mixing of reactant solutions. Through the case study focusing on the biomimetic precipitation of calcium carbonate on eggshell membranes, the cell demonstrated its functionality by enabling the precipitation of vaterite and calcite mixtures with changes in CaCO3 polymorph ratios depending on the mixing mode. This versatile cell is not limited to studying calcium carbonate; it can be used to investigate the precipitation of various other substances. It holds potential for modeling biomineral formation processes and pathological mineral formation in organisms. Additionally, the cell can be adapted for the study of antisolvent and other precipitation techniques.

Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels.

Multiplexed fluorescence imaging is typically limited to three- to five-plex on standard setups. Sequential imaging methods based on iterative labeling and imaging enable practical higher multiplexing, but generally require a complex fluidic setup with several rounds of slow buffer exchange (tens of minutes to an hour for each exchange step). We report the thermal-plex method, which removes complex and slow buffer exchange steps and provides fluidic-free, rapid sequential imaging. Thermal-plex uses simple DNA probes that are engineered to fluoresce sequentially when, and only when, activated with transient exposure to heating spikes at designated temperatures (thermal channels). Channel switching is fast (<30 s) and is achieved with a commercially available and affordable on-scope heating device. We demonstrate 15-plex RNA imaging (five thermal × three fluorescence channels) in fixed cells and retina tissues in less than 4 min, without using buffer exchange or fluidics. Thermal-plex introduces a new labeling method for efficient sequential multiplexed imaging.

Concerns on the Effects of Electrode Positions in Electrolyte Container for the Oxygen Evolution Reaction.

Water electrolysis is currently a major technique to produce clean hydrogen, which is regarded as a promising and sustainable energy carrier. The efficiency of water electrolysis is highly dependent on the oxygen evolution reaction (OER) on the anode. The evaluation of an OER electrocatalyst is frequently carried out on a three-electrode system in a container of electrolyte. Herein, we found that the electrode positions in the electrolyte container could significantly affect the data acquisition of OER performance. After a detailed investigation, we reveal that the difference of the OER activity of an electrocatalyst at a different position is originated from their different iRu drop and the gas diffusion resistance. For the first time, this work evokes concerns on the accurate evaluation of electrocatalysts regarding the electrode position. For fair comparisons and reliable results, it is strongly suggested to keep the electrode position unchanged in the electrochemical measurements. In addition, the establishment of a standard electrolyzer setup for electrocatalysis evaluation in the electrochemical community is also called for.

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation.

High-resolution retinotopic blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) with a wide-view presentation can be used to functionally map the peripheral and central visual cortex. This method for measuring functional changes of the visual brain allows for functional mapping of the occipital lobe, stimulating >100° (±50°) or more of the visual field, compared to standard fMRI visual presentation setups which usually cover <30° of the visual field. A simple wide-view stimulation system for BOLD fMRI can be set up using common MR-compatible projectors by placing a large mirror or screen close to the subject's face and using only the posterior half of a standard head coil to provide a wide-viewing angle without obstructing their vision. The wide-view retinotopic fMRI map can then be imaged using various retinotopic stimulation paradigms, and the data can be analyzed to determine the functional activity of visual cortical regions corresponding to central and peripheral vision. This method provides a practical, easy-to-implement visual presentation system that can be used to evaluate changes in the peripheral and central visual cortex due to eye diseases such as glaucoma and the vision loss that may accompany them.

"Single-Surgeon" versus "Dual-Surgeon" Robot-Assisted Radical Prostatectomy and Pelvic Lymph-nodes Dissection: Comparative Analysis of Perioperative Outcomes.

To compare the perioperative outcomes of robot-assisted radical prostatectomy (RARP) with pelvic lymph-nodes dissection (PLND) when the same surgeon performs RARP and PLND versus one surgeon performs RARP and another surgeon performs PLND. From January 2022 to March 2023, data of consecutive patients who underwent RARP with PLND were prospectively collected. The surgeries were performed by two "young" surgeons with detailed profile. Specifically for the study purpose, one surgeon performed RARP, and the other surgeon performed PLND. A set of surgeries performed according to the standard setup (i.e., the same surgeon performing both RARP and PLND) was retrieved from the institutional database and used as comparator arm. To test the study hypothesis, patients were divided into two groups: "dual-surgeon" versus "single-surgeon". Fifty patients underwent RARP and PLND performed according to dual-surgeon setup and were compared to the last 50 procedures performed according to the standard single-surgeon setup. Patients in the groups had comparable baseline characteristics. Dual-surgeon interventions had significantly shorter median total operative (194 [IQR 178-215] versus 174 [IQR 146-195] minutes, p<0.001) and console time (173 [IQR 158-194] versus 154 [IQR 129-170] minutes, p<0.001). No significant differences were found in terms of blood loss, intraoperative complications, postoperative outcomes, and final pathology results. The present analysis found that when RARP and PLND are split onto two surgeons, the operative time is shorter by 20 minutes compared to when a single surgeon performs RARP and PLND. This is an interesting finding that could sponsor further studies.

An Experimental Study on Some Thermophysical Characteristics of CuO-Water Nanofluid

This study presents the effects of the volume fraction of nanoparticles (0.15% ≤ Φ ≤ 0.74%) with ascorbic acid additive on some thermophysical characteristics of water based CuO nanofluids, such as thermal conductivity and viscosity, as well as agglomeration by analyzing microstructure, adhesion and precipitation time. The CuO nanofluids have been prepared and examined for five different volume fractions by using appropriate mixers. The microstructure of the samples, which are prepared with ascorbic acid additive in order to prevent the agglomeration of CuO nanoparticles and to ensure a homogeneous distribution, has been analyzed on the SEM images. In the adhesion experiments, an observational test was performed for 0.23% CuO-water sample. The samples prepared have been kept about 100 hours for observational examination of precipitation similar to the adhesion test. Thermal conductivity measurements have been conducted in a standard experimental set-up and a correlation equation has been proposed based on data acquired. The viscosity measurements have been carried out using a calibrated “falling-piston viscometer” and a correlation equation was also defined for thermal conductivity. The thermal conductivity measurements of the study have been compared to experiments given in the literature and a good agreement has been obtained at low volume fractions (less than 0.5%).