Size Discrimination Research Articles

Comparison of Dorsoulnar Artery Perforator, Superficial Palmar Branch of the Radial Artery, and Superficial Circumflex Iliac Artery Perforator Flaps in Volar Finger Defects.

Volar finger defects can sometimes be challenging for plastic surgeons. There are many reconstruction options from local flaps to free flaps. Therefore, the aim of this study was to present a functional and cosmetic comparison of the results of using dorsoulnar artery perforator (DUAP), superficial palmar branch of the radial artery (SPBRA), and superficial circumflex iliac artery perforator (SCIP) flaps for repairing volar finger defects. Thirty-two patients were included in the study. The age and sex of the patients, cause of injury, defect location, defect size, and presence or absence of nerve damage were noted. The patients' defects were reconstructed with DUAP, SCIP, or SPBRA flaps. The flap size, flap elevation time, vessels, and early postoperative complications were noted. During the postoperative follow-up period, the Michigan Hand Outcomes Questionnaire scale was used to evaluate hand function, and the modified Vancouver Scar Scale was used to assess aesthetic appearance. Two-point discrimination tests and cold intolerance tests were performed to measure sensory outcomes. Donor site improvements were also noted. There was no significant difference between the groups in terms of age, defect size, flap size, follow-up time, and 2-point discrimination. It was observed that the elevation time was significantly shorter in the SCIP flap group, and the Michigan Hand Outcomes Questionnaire score was significantly lower in the DUAP flap group compared with the other 2 groups (P < 0.01). In addition, the modified Vancouver Scar Scale score was significantly higher in the DUAP flap group (P < 0.01). The findings of this study show that the use of SPBRA flaps has more advantages than the use of DUAP and SCIP flaps in many respects.

The Influences of Pore Blockage by Natural Organic Matter and Pore Dimension Tuning on Pharmaceutical Adsorption onto GO-Fe3O4.

The ubiquitous presence of pharmaceutical pollution in the environment and its adverse impacts on public health and aquatic ecosystems have recently attracted increasing attention. Graphene oxide coated with magnetite (GO-Fe3O4) is effective at removing pharmaceuticals in water by adsorption. However, the myriad compositions in real water are known to adversely impact the adsorption performance. One objective of this study was to investigate the influence of pore blockage by natural organic matter (NOM) with different sizes on pharmaceutical adsorption onto GO-Fe3O4. Meanwhile, the feasibility of pore dimension tuning of GO-Fe3O4 for selective adsorption of pharmaceuticals with different structural characteristics was explored. It was shown in the batch experiments that the adsorbed pharmaceutical concentrations onto GO-Fe3O4 were significantly affected (dropped by 2-86%) by NOM that had size ranges similar to the pore dimensions of GO-Fe3O4, as the impact was enhanced when the adsorption occurred at acidic pHs (e.g., pH 3). Specific surface areas, zeta potentials, pore volumes, and pore-size distributions of GO-Fe3O4 were influenced by the Fe content forming different-sized Fe3O4 between GO layers. Low Fe contents in GO-Fe3O4 increased the formation of nano-sized pores (2.0-12.5 nm) that were efficient in the adsorption of pharmaceuticals with low molecular weights (e.g., 129 kDa) or planar structures via size discrimination or inter-planar π-π interaction, respectively. As excess larger-sized pores (e.g., >50 nm) were formed on the surface of GO-Fe3O4 due to higher Fe contents, pharmaceuticals with larger molecular weights (e.g., 296 kDa) or those removed by electrostatic attraction between the adsorbate and adsorbent dominated on the GO-Fe3O4 surface. Given these observations, the surface characteristics of GO-Fe3O4 were alterable to selectively remove different pharmaceuticals in water by adsorption, and the critical factors determining the adsorption performance were discussed. These findings provide useful views on the feasibility of treating pharmaceutical wastewater, recycling valuable pharmaceuticals, or removing those with risks to public health and ecosystems.

Artificial intelligence for the prevention and prediction of colorectal neoplasms

BackgroundColonoscopy is a useful as a cancer screening test. However, in countries with limited medical resources, there are restrictions on the widespread use of endoscopy. Non-invasive screening methods to determine whether a patient requires a colonoscopy are thus desired. Here, we investigated whether artificial intelligence (AI) can predict colorectal neoplasia.MethodsWe used data from physical exams and blood analyses to determine the incidence of colorectal polyp. However, these features exhibit highly overlapping classes. The use of a kernel density estimator (KDE)-based transformation improved the separability of both classes.ResultsAlong with an adequate polyp size threshold, the optimal machine learning (ML) models’ performance provided 0.37 and 0.39 Matthews correlation coefficient (MCC) for the datasets of men and women, respectively. The models exhibit a higher discrimination than fecal occult blood test with 0.047 and 0.074 MCC for men and women, respectively.ConclusionThe ML model can be chosen according to the desired polyp size discrimination threshold, may suggest further colorectal screening, and possible adenoma size. The KDE feature transformation could serve to score each biomarker and background factors (health lifestyles) to suggest measures to be taken against colorectal adenoma growth. All the information that the AI model provides can lower the workload for healthcare providers and be implemented in health care systems with scarce resources. Furthermore, risk stratification may help us to optimize the efficiency of resources for screening colonoscopy.

Digital finance and enterprise financing constraints: Structural characteristics and mechanism identification

Using the panel data of A-share listed companies from 2011 to 2020, we demonstrate that the WW index can characterize the level of enterprise financing constraints in China more effectively. We investigate the effect of regional digital finance (DF) development on enterprise financing constraints. This study found that DF can significantly alleviate enterprise financing constraints, and the effect is greater for small and medium-sized enterprises (SMEs) and private enterprises. DF can partially correct the size discrimination and ownership discrimination of traditional finance on private SMEs, as well as the mismatch of financial resources. Further, the results revealed that DF can alleviate information asymmetry in the securities market and between banks and enterprises and improve the external financing capabilities of enterprises. Moreover, DF can increase the enterprise's total factor productivity (TFP) and optimize the internal financing capacity of enterprises. Overall, DF will significantly ease enterprise financing constraints.

A Novel Method Determining the Size and Angle of an Object Using a Depth Camera Without Reference

In traditional methods, a fixed object is taken as a reference for size determination. The size of the other object is calculated by comparing the dimensions of this reference object. However, when it is desired to measure objects at different heights, the measurement of the reference object must also be changed. In the study carried out, the size and angle of the products flowing through the line were determined by using a depth camera. The data set was created by taking the measurements of an object of known dimensions from 34 different distances. The mentioned data set consists of the ratio of the number of pixels of the edges of the object to the lengths of the edges. By comparing the correlation between the obtained data set and the distance values, a mathematical equation was extracted with the help of the MATLAB program. With the help of this equation, regardless of the height and color of the object, only the distance to the camera and all 3 dimensions can be calculated. In addition, the angle of the object with the software-generated reference line was calculated by taking the long side of the object as a reference. In this way, the size and angle of the products flowing through the line were determined with a single camera without the need for a reference object and without any color and size discrimination.

Macroporous Epoxy-Based Monoliths Functionalized with Anti-CD63 Nanobodies for Effective Isolation of Extracellular Vesicles in Urine

Extracellular vesicles (EVs) have enormous potential for the implementation of liquid biopsy and as effective drug delivery means, but the fulfilment of these expectations requires overcoming at least two bottlenecks relative to their purification, namely the finalization of reliable and affordable protocols for: (i) EV sub-population selective isolation and (ii) the scalability of their production/isolation from complex biological fluids. In this work, we demonstrated that these objectives can be achieved by a conceptually new affinity chromatography platform composed of a macroporous epoxy monolith matrix functionalized with anti-CD63 nanobodies with afflux of samples and buffers regulated through a pump. Such a system successfully captured and released integral EVs from urine samples and showed negligible unspecific binding for circulating proteins. Additionally, size discrimination of eluted EVs was achieved by different elution approaches (competitive versus pH-dependent). The physical characteristics of monolith material and the inexpensive production of recombinant nanobodies make scaling-up the capture unit feasible and affordable. Additionally, the availability of nanobodies for further specific EV biomarkers will allow for the preparation of monolithic affinity filters selective for different EV subclasses.

Investigation of the multiple characteristics of the self-mixing effect subject to a single particle.

As a compact interferometry technique, self-mixing interferometry (SMI) is a promising tool for micro particle detection in biochemical analysis and the monitoring of laser manufacturing processing, and currently SMI based micro particle detection is attracting increasing attention. However, unlike the typical displacement or vibration measurement driven by a macro target, only a small amount of literature has targeted the SMI effect induced by a single micro moving particle. In this paper, two numerical models were investigated to describe the characteristics of the signal sparked by individual particle. We compared the measurement results with the two models' simulations in three signal characteristic aspects: the temporal waveform, frequency spectrum, and phase profile. From these results, we established that both amplitude modulation and frequency modulation effects apply under different conditions in the self-mixing process. And for the first time, we analyzed the effect of the laser illumination spot size on the particle-induced SMI signal features with two optical arrangements. When the laser beam size is larger than the particle size, the signal bursts are likely to result from frequency modulation, and vice versa. Our results can improve the capability of SMI technology in particle size discrimination and particle sorting.

Performance of high-resolution CT for detection and discrimination tasks related to stenotic lesions - A phantom study using model observers.

Accurate detection and grading of atheromatous stenotic lesions within the cardiac, renal, and intracranial vasculature is imperative for early recognition of disease and guiding treatment strategies. In this work, a stenotic lesion phantom was used to compare high resolution and normal resolution modes on the same CT scanner in terms of detection and size discrimination performance. The phantom is comprised of three acrylic cylinders (each 15.0cm in diameter and 1.3cm thick) with a matching array of holes in each module. The outer two modules contain holes that are slightly larger than the corresponding hole in the central module to simulate stenotic narrowing in vasculature. The stack of modules was submerged in an iodine solution simulating contrast-enhanced stenotic lesions with a range of lumen diameters (1.32-10.08mm) and stenosis severity (0%, 50%, 60%, 70%, and 80%). The phantom was imaged on the Canon Aquilion Precision high-resolution CT scanner in high-resolution (HR) mode (0.25mm × 0.50mm detector element size) and normal-resolution (NR) mode (0.50mm × 0.50mm) using 120 kV and two dose levels (14 and 21mGy SSDE) with 30 repeat scans acquired for each combination. Filtered back-projection (FBP) and a hybrid-iterative reconstruction (AIDR) were used with the FC18 kernel, as well as a deep learning algorithm (AiCE) which is only available for HR. A non-prewhitening model observer with an eye filter was implemented to quantify performance for detection and size discrimination tasks in the axial plane. Detection performance improved with increasing diameter, dose, and for AIDR in comparison to FBP for a fixed resolution mode. Performance in the HR mode was generally higher than NR for the smaller lumen diameters (1-5mm) with decreasing differences as the diameter increased. Performance in NR mode surpassed HR mode for lumen diameters greater than ∼4mm and ∼5mm for 14mGy and 21mGy, respectively. AiCE provided consistently higher detection performance compared with AIDR-FC18 (48% higher for a 6mm lumen diameter). Discrimination performance increased with increasing nominal diameter, dose, and for larger differences in stenosis severity. When comparing discrimination performance in HR to NR modes, the largest relative differences occur at the smallest nominal diameters and smallest differences in stenosis severity. The AiCE reconstruction algorithm produced the highest overall discrimination performance values, and these were significantly higher than AIDR-FC18 for nominal diameters of 7.14 and 10.08mm. HR mode outperforms NR for detection up to a specific diameter and the results improve with AiCE and for higher dose levels. For the task of size discrimination, HR mode consistently outperforms NR if AIDR-FC18 is used for dose levels of at least 21mGy, and the results improve with AiCE and for the smallest differences in stenosis severity investigated (50% vs. 60%). High-resolution CT appears to be beneficial for detecting smaller simulated lumen diameters (<5mm) and is generally advantageous for discrimination tasks related to stenotic lesions, which inherently contain information at higher frequencies, given the right reconstruction algorithm and dose level.

Alternative metrics for characterizing longer-term clinical outcomes in difficult-to-treat depression: I. Association with change in quality of life.

In difficult-to-treat depression (DTD) the outcome metrics historically used to evaluate treatment effectiveness may be suboptimal. Metrics based on remission status and on single end-point (SEP) assessment may be problematic given infrequent symptom remission, temporal instability, and poor durability of benefit in DTD. Self-report and clinician assessment of depression symptom severity were regularly obtained over a 2-year period in a chronic and highly treatment-resistant registry sample (N = 406) receiving treatment as usual, with or without vagus nerve stimulation. Twenty alternative metrics for characterizing symptomatic improvement were evaluated, contrasting SEP metrics with integrative (INT) metrics that aggregated information over time. Metrics were compared in effect size and discriminating power when contrasting groups that did (N = 153) and did not (N = 253) achieve a threshold level of improvement in end-point quality-of-life (QoL) scores, and in their association with continuous QoL scores. Metrics based on remission status had smaller effect size and poorer discrimination of the binary QoL outcome and weaker associations with the continuous end-point QoL scores than metrics based on partial response or response. The metrics with the strongest performance characteristics were the SEP measure of percentage change in symptom severity and the INT metric quantifying the proportion of the observation period in partial response or better. Both metrics contributed independent variance when predicting end-point QoL scores. Revision is needed in the metrics used to quantify symptomatic change in DTD with consideration of INT time-based measures as primary or secondary outcomes. Metrics based on remission status may not be useful.

Sizeism in Education: What School Counselors Need to Know

This conceptual article explains how school counselors can increase awareness of size discrimination and address sizeist attitudes and biases in U.S. schools. Sizeism can begin in early childhood and continue into young adulthood, with damaging effects on student wellness. Sizeist biases in society are reflected in school systems. We suggest actions school counselors can take to promote equity in education for students of size, including implementing size-inclusive prevention strategies within a comprehensive school counseling program.

Simultaneous Localization and Size Discrimination Modeling via Convolutional Neural Network

Simultaneous Localization and Size Discrimination Modeling via Convolutional Neural Network

Improving quantitation of nanoparticle concentrations in mixtures of known components using single particle inductively coupled plasma mass spectrometry with kernel density estimation

Accurate quantification of nanoparticle fractions in polydisperse mixture is challenging for many analytical techniques. For single particle inductively coupled plasma mass spectrometry (spICP-MS) where pulse signals are correlated to nanoparticles size and number concentration, data processing is crucial. The state-of-the-art algorithms distinguish particulate components with size difference of more than about 20 nm. In this work, a Bayes discriminant analysis based on a finite mixture model consisting of kernel density estimation (FMKDE) has been applied for spICP-MS, resulting in an unprecedented improvement in size resolution. Compared to existing data processing methods, the FMKDE model provides highly accurate contents due to the flexibility of the kernel density estimation for probability density. The gold nanoparticle mixtures have been used to verify the comparison. The size discrimination limit for gold mixtures can be decreased to about 5 nm with resolvable component content of <10% using the FMKDE model. The quantified number concentrations are also consistent with the designed values for the prepared mixtures with absolute biases of <3%. This study improves the size resolution of spICP-MS which could broaden its applicability in particle mixtures.

Comprehensive structural assignment of glycosaminoglycan oligo- and polysaccharides by protein nanopore

Glycosaminoglycans are highly anionic functional polysaccharides with information content in their structure that plays a major role in the communication between the cell and the extracellular environment. The study presented here reports the label-free detection and analysis of glycosaminoglycan molecules at the single molecule level using sensing by biological nanopore, thus addressing the need to decipher structural information in oligo- and polysaccharide sequences, which remains a major challenge for glycoscience. We demonstrate that a wild-type aerolysin nanopore can detect and characterize glycosaminoglycan oligosaccharides with various sulfate patterns, osidic bonds and epimers of uronic acid residues. Size discrimination of tetra- to icosasaccharides from heparin, chondroitin sulfate and dermatan sulfate was investigated and we show that different contents and distributions of sulfate groups can be detected. Remarkably, differences in α/β anomerization and 1,4/1,3 osidic linkages can also be detected in heparosan and hyaluronic acid, as well as the subtle difference between the glucuronic/iduronic epimers in chondroitin and dermatan sulfate. Although, at this stage, discrimination of each of the constituent units of GAGs is not yet achieved at the single-molecule level, the resolution reached in this study is an essential step toward this ultimate goal.

Rotational remanent magnetization as a magnetic mineral diagnostic tool at low rotation rates

SUMMARY Prior work on rotational remanent magnetization (RRM) and rotational anhysteretic remanent magnetization (ARMROT) has demonstrated promise for magnetic mineral identification in earth materials. One challenge has been to calibrate the measurements to magnetic mineral types and microstructural controls, since previous studies have used differing spin rates, alternating field (AF) intensities and decay times, which hinders a comparison of data sets. Using a RAPID magnetometer we show that the range of usable practical rotation rates is 0.25–3 Hz [rps] which allows a wide range of RRM and ARMROT characteristics to be utilized (at 100 mT AF field, 100 μT bias field). Sets of magnetic mineral extracts from sediments, and well characterized rock samples that contain the key magnetic minerals magnetite, pyrrhotite and greigite are used for a calibration of the RRM-ARMROT behaviour. Detrital pyrrhotite and pyrrhotite-bearing phyllites have largely small positive effective field (Bg) values (up to 6 μT), with differences in Bg and ARMROT ratios at 0.5 and 2.5 Hz [rps] allowing grain size discrimination. The positive Bg values, and changes in RRM and ARMROT with rotation rates allow distinction of pyrrhotite from magnetite and diagenetic greigite. Diagenetic greigite has Bg values of –83 to –109 μT (at 0.5 Hz [rps]) and unusual RRM variation at low rotation rates caused by anisotropy affects. In contrast to previous work, based on crushed and sized natural magnetite at high spin rates, Bg for single domain magnetite from intact bacterial magnetofossils from Upper Cretaceous Chalk has some of the lowest Bg (0–1 μT) and displays a steep decline in ARMROT with increasing rotation rates. A simple tool for particle size characterization of magnetite may be the ratio of ARMROT at spin rates 2.5 and 0.5 Hz [rps]. Stability of RRM is better studied using RRM acquisition with increasing AF field intensity, since static demagnetization imparts a nuisance gyroremanence along the field axis. Mineral microstructure, dislocations and particle interactions are likely additional effects on RRM behaviour that need more investigation.

Legal Evolution of a Law Against Weight Discrimination in the United States: A Focus on Massachusetts.

Weight discrimination heightens health inequalities, particularly among racial and ethnically diverse populations. We aim to research the legal evolution of the law against weight discrimination (S.2495) and raise awareness among lawmakers in the Commonwealth of Massachusetts. We invited officials (n = 199) to attend a legislative briefing, and 25.6% completed a 14-question anonymous survey upon arrival. Contrary to our hypothesis, this first-of-its-kind study found that most policymakers are aware of weight biases. While S.2495 did not pass, the current bill S.2669, prohibiting body size discrimination, has recently been reported favorably by the Joint Committee on the Judiciary and referred to the committee on Senate Ways and Means.

Nanoparticle sizing by focused-beam dynamic ultrasound scattering method

When nanoparticles in Brownian motion in liquid are irradiated with ultrasonic waves in the megahertz frequency range, scattering from the particles occurs, albeit at a very low intensity. The diffusion coefficient and the corresponding particle size can be calculated by analyzing the time correlation function of the ultrasound pulses. Since ultrasonic waves with long wavelengths in comparison with the particle size are unfavorable for detecting such small particles, increasing the energy of the ultrasonic waves is a primary solution. Increasing the energy, conversely, causes an unexpected acoustic flow. Consequently, a method using a strong ultrasound pulse while suppressing this acoustic flow field is required. In this study, we apply (1) a focused transducer with high ultrasonic energy, (2) a high-frequency sensor enhancing scattering performance, and (3) a short pulse repetition time to achieve high-speed and high-precision nanoparticle measurement while confining the sample in a narrow space to eliminate the acoustic flow. This enables direct tracking of nanoparticle motion by observing diffusive motion without perturbation particle dynamics. We specifically investigated a suspension of silica particles with a hydrodynamic radius of 15 nm and also achieved particle size discrimination in mixtures. The time correlation analysis using megahertz ultrasound pulses also takes advantage of ultrasonic waves’ inherent advantages, such as high-speed, high-precision particle size analysis in the submicron range beyond the wavelength of visible light.

Losing a parent in early-life impairs flock size discrimination and lowers oxytocin receptor abundance in a medial amygdala homologueof adult zebra finches.

Experiencing inadequate parental care during early-life diminishes adult social competencies. For example, low parental care impairs adult socio-cognitive abilities (e.g., recognizing familiar conspecifics) and affiliation (e.g., close social proximity); outcomes attributed to diminished medial amygdala nonapeptide functioning in rodents. Whether parental care has effects beyond familiarity, and if siblings have similar effects to parents, is unclear. Here, zebra finches were used to explore if parent and/or sibling number shape adult recognition and preference of small versus large flocks and nonapeptide (oxytocin, vasotocin) receptor expression in an avian homologue of the mammalian medial amygdala. Chicks were raised by single mothers or fathers in small broods or paired parents in small or large broods matched to single parents for chicks per nest or per parent, respectively. Pair-raised birds had preferred flock sizes as adults, but birds raised by single parents had equal preference for either size. Oxytocin receptor expression was lower in birds raised by single parents versus paired parents, but vasotocin receptor levels were unaffected. Such results highlight parents as formative antecedents of their offspring's social competencies related to group size preference and their nonapeptide mechanisms, outcomes that influence an animal's ability to live in social groups.

Visual context processing and its development in gamers and non-gamers.

Visual context processing was investigated in both action video game players and nonplayers using the Ebbinghaus illusion task (N=312, 39.4% female) in a cross-sectional study design. When presented in context, players showed markedly poorer target size discrimination accuracy compared with nonplayers in the 6-, 7-, 8-, and 9-years old age groups, but this difference was reduced in 10-years old group and diminished in adults. When presented in isolation (no-context), the two groups displayed similar performance in all age groups. Furthermore, nonplayers (linear) and players (bell curve) showed profoundly different age-related differences in context processing. These findings provide evidence that players might have enhanced perceptual bias to process visual context in the transition from early childhood to early adolescence, and the differences between the two groups start at early ages and continue with distinct developmental profiles.

Triple-ligand zeolitic imidazolate frameworks for highly CO2 selective mixed matrix membranes

• A series of triple ligand-coordinated ZIF-8s (TAZIF-8s) were successfully prepared. • The TAZIF-8s enhanced chemical interaction and molecular sieving ability toward CO 2 . • A high dispersibility of TAZIF-8s enabled high TAZIF-8 loading (40 wt%) mixed matrix membranes (MMMs). • TAZIF-8 MMMs effectively suppressed both the physical aging and CO 2 -induced plasticization. • High CO 2 separation performance of TAZIF-8 MMMs was retained even after water vapor exposure. Here, we report a new class of highly CO 2 selective ZIF nanoparticles, TAZIF-8, consisting of zinc metals and triple ligands, including 2-methylimidazole (MIm), tributylamine (TBA), and 3-amino-1,2,4-triazole (Atz). The Zn-MIm coordination retains an open porous sodalite topology, while the Zn-TBA analogue contributes to high processability. Lastly, the Zn-Atz coordination enables favorable CO 2 permeation via a combination of enhanced size discrimination and specific chemical interactions. A high loading 6FDA-DAM/TAZIF-8 (40 wt%) mixed matrix membrane consequently exhibits an almost threefold increase in CO 2 permeability and a twofold increase in CO 2 selectivity over other light gases (N 2 , CO, or CH 4 ) compared to high performance 6FDA-DAM membrane. Furthermore, it maintains excellent CO 2 separation performance over 90 days and even after exposure to water vapor. Our multiple hybrid modification technique enables the fine-tuning of the physical structure and textural properties of ZIF for enhanced CO 2 separation performance.

Does social distancing affect the processing of brand logos?

Social distancing and isolation have been imposed to contrast the spread of COVID‐19. The present study investigates whether social distancing affects our cognitive system, in particular the processing of different types of brand logos in different moments of the pandemic spread in Italy. In a size discrimination task, six different logos belonging to three categories (letters, symbols, and social images) were presented in their original format and spaced. Two samples of participants were tested: one just after the pandemic spread in Italy, the other one after 6 months. Results showed an overall distancing effect (i.e., spaced stimuli are processed slower than original ones) that interacted with the sample, revealing a significant effect only for participants belonging to the second sample. However, both groups showed a distancing effect modulated by the type of logo as it only emerged for social images. Results suggest that social distancing behaviors have been integrated in our cognitive system as they appear to affect our perception of distance when social images are involved.