Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Turner syndrome using hand X-ray using anchor based links segmentation method

Turner Syndrome (TS) is a chromosomal disorder, wherein the female’s growth is impacted. Immature ovaries, low stature, and heart abnormalities are a range of developmental and medical issues due to TS. The condition of TS might be detected prior to birth, throughout infancy or in the early years of life. The diagnosis of TS in girls with modest symptoms and indications is sometimes deferred until they reach adolescence or become young adults. This study presents an algorithm to segment the hand digital X-ray image in children with TS. In medical image and computer vision examination, image segmentation is demanding, and very crucial. Prevailing segmentation algorithms even now suffer from common segmentation issues including under-segmentation, over-segmentation, and spurious or non-closed edges, regardless of the several years of studies. In this paper, Anchor Based Link (ABL) segmentation approach is proposed to detect TS based on fourth Metacarpal bone from left hand X-ray images. The detection of TS is demonstrated based upon the comparison of proposed approach with existing watershed segmentation and Gaussian-Mixture-Model-based Hidden-Markov-Random-Field (GMM-HMRF) method. The proposed approach attains better segmentation based on the ratio of height and width of left fourth finger that is analyzed for normal children and children having TS with the help of edge pixel present in the metacarpal bone that has been segmented. The suggested method is verified on fifty (50) sample X-ray hand images of carpal bones, providing 0.60 ± 0.02 as an average Dice coefficient.
Trabecular Bone Score Reference Values for Children and Adolescents According to Age, Sex, and Ancestry

Trabecular bone score (TBS) is used for fracture prediction in adults, but its utility in children is limited by absence of appropriate reference values. We aimed to develop reference ranges for TBS by age, sex, and population ancestry for youth ages 5 to 20 years. We also investigated the association between height, body mass index (BMI), and TBS, agreement between TBS and lumbar spine areal bone mineral density (aBMD) and bone mineral apparent density (BMAD) Z‐scores, tracking of TBS Z‐scores over time, and precision of TBS measurements. We performed secondary analysis of spine dual‐energy X‐ray absorptiometry (DXA) scans from the Bone Mineral Density in Childhood Study (BMDCS), a mixed longitudinal cohort of healthy children (n = 2014) evaluated at five US centers. TBS was derived using a dedicated TBS algorithm accounting for tissue thickness rather than BMI. TBS increased only during ages corresponding to pubertal development with an earlier increase in females than males. There were no differences in TBS between African Americans and non‐African Americans. We provide sex‐specific TBS reference ranges and LMS values for calculation of TBS Z‐scores by age and means and SD for calculation of Z‐scores by pubertal stage. TBS Z‐scores were positively associated with height Z‐scores at some ages. TBS Z‐scores explained only 27% and 17% of the variance of spine aBMD and BMAD Z‐scores. Tracking of TBS Z‐scores over 6 years was lower (r = 0.47) than for aBMD or BMAD Z‐scores (r = 0.74 to 0.79), and precision error of TBS (2.87%) was greater than for aBMD (0.85%) and BMAD (1.22%). In sum, TBS Z‐scores provide information distinct from spine aBMD and BMAD Z‐scores. Our robust reference ranges for TBS in a well‐characterized pediatric cohort and precision error estimates provide essential tools for clinical assessment using TBS and determination of its value in predicting bone fragility in childhood and adolescence. © 2022 American Society for Bone and Mineral Research (ASBMR).
Noninvasive Prediction of Congenital Cytomegalovirus Infection After Maternal Primary Infection

We developed models to predict congenital cytomegalovirus infection for women with primary infection and absence of ultrasonographic findings. OBJECTIVE: To develop and internally validate a noninvasive method for the prediction of congenital cytomegalovirus (CMV) infection after primary maternal CMV infection. METHODS: We conducted a secondary analysis of a multicenter randomized placebo-controlled trial of CMV hyperimmune globulin to prevent congenital infection. Women were eligible if they had primary CMV infection, defined as detectable plasma CMV-specific immunoglobulin (Ig)M and CMV-specific IgG with avidity less than 50% before 24 weeks of gestation or IgG seroconversion before 28 weeks, and were carrying a singleton fetus without ultrasonographic findings suggestive of CMV infection. Antibody assays were performed in a single reference laboratory. Congenital infection was defined as CMV detection in amniotic fluid, neonatal urine or saliva, or postmortem tissue. Using backward elimination, we developed logit models for prediction of congenital infection using factors known at randomization. The performance of the model was assessed using leave-one-out cross-validation (a method of internal validation). RESULTS: Of 399 women enrolled in the trial, 344 (86%) had informative data for this analysis. Congenital infection occurred in 68 pregnancies (20%). The best performing model included government-assisted insurance, IgM index 4.5 or higher, IgG avidity less than 32%, and whether CMV was detectable by polymerase chain reaction in maternal plasma at the time of randomization. Cross-validation showed an average area under the curve of 0.76 (95% CI 0.70–0.82), indicating moderate discriminatory ability. More parsimonious one-, two-, and three-factor models performed significantly less well than the four-factor model. Examples of prediction with the four-factor model: for a woman with government-assisted insurance, avidity less than 32%, IgM index 4.5 or higher, and detectable plasma CMV, probability of congenital infection was 0.69 (95% CI 0.53–0.82); for a woman with private insurance, avidity 32% or greater, IgM index less than 4.5, and undetectable plasma CMV, probability of infection was 0.03 (95% CI 0.02–0.07). CONCLUSION: We developed models to predict congenital CMV infection in the presence of primary maternal CMV infection and absence of ultrasonographic findings suggestive of congenital infection. These models may be useful for patient counseling and decision making.
Wiener－Basedsic Scheme for ICI Cancellation in OFDM Systems under Time－Varying Channels

The orthogonality among the subcarriers of orthogonal frequency division multiplexing (OFDM) systems may not be preserved under time-varying channels. The system performance becomes degraded due to the loss of orthogonality among the subcarriers, and this effect is called intercarrier interference (ICI). Conventional zero forcing detection scheme can be used to suppress the ICI effect, but noise enhancement also occurs.In order to avoid noise enhancement, a novel Wiener-based successive interference cancellation (SIC) scheme is proposed to detect the OFDM signals in this paper. The Wienerbased SIC scheme provides a good ICI cancellation performance. Simulation results show that the performance of the Wienerbased SIC scheme is better than those of both zero forcing and zero forcing plus SIC schemes.
Lipopolysaccharide Pretreatment Prevents Medullary Vascular Congestion following Renal Ischemia by Limiting Early Reperfusion of the Medullary Circulation

Significance Statement The pathogenesis of medullary vascular congestion—red blood cell (RBC) aggregation in the renal medulla vasculature—after renal ischemia has been uncertain. In a rat model, the authors found that during ischemia, sludging of RBCs occurs in the renal venous vasculature. Because recovery of cortical perfusion is required to displace this stalled blood in the shared venous vessels—which drain both the cortex and medulla—restoration of blood flow to the medulla before restoration to the cortex results in tightly packed RBC congestion of the medullary circulation. This congestion then prevents later reperfusion of the medulla, even after blood flow is restored to the cortex, resulting in tubular injury. These findings support a hemodynamic explanation for the susceptibility of the renal medulla to ischemic injury. Visual Abstract Background Vascular congestion of the renal medulla—trapped red blood cells in the medullary microvasculature—is a hallmark finding at autopsy in patients with ischemic acute tubular necrosis. Despite this, the pathogenesis of vascular congestion is not well defined. Methods In this study, to investigate the pathogenesis of vascular congestion and its role in promoting renal injury, we assessed renal vascular congestion and tubular injury after ischemia reperfusion in rats pretreated with low-dose LPS or saline (control). We used laser Doppler flowmetry to determine whether pretreatment with low-dose LPS prevented vascular congestion by altering renal hemodynamics during reperfusion. Results We found that vascular congestion originated during the ischemic period in the renal venous circulation. In control animals, the return of blood flow was followed by the development of congestion in the capillary plexus of the outer medulla and severe tubular injury early in reperfusion. Laser Doppler flowmetry indicated that blood flow returned rapidly to the medulla, several minutes before recovery of full cortical perfusion. In contrast, LPS pretreatment prevented both the formation of medullary congestion and its associated tubular injury. Laser Doppler flowmetry in LPS-pretreated rats suggested that limiting early reperfusion of the medulla facilitated this protective effect, because it allowed cortical perfusion to recover and clear congestion from the large cortical veins, which also drain the medulla. Conclusions Blockage of the renal venous vessels and a mismatch in the timing of cortical and medullary reperfusion results in congestion of the outer medulla’s capillary plexus and promotes early tubular injury after renal ischemia. These findings indicate that hemodynamics during reperfusion contribute to the renal medulla’s susceptibility to ischemic injury.
Comment on “Efficacy and safety of colchicine in patients with coronary artery disease: A systematic review and meta‐analysis of randomized controlled trials”

Inflammatory biomarkers in the body play critical role in the complex pathophysiology of atherosclerosis which is the main culprit of coronary artery disease. 1 Thus, controlling of pro-inflammatory bio-logical factors is an obvious theoretical target for the prevention and treatment of coronary artery disease. 2 The COLCOT trial recently showed cardiovascular benefits from colchicine treatment. 3 Colchicine is a well-established anti-inflammatory that reduces NLRP3 inflammasome mediated crystal-induced inflammation, which is pre-sent in gout caused by uric acid crystals, and atherosclerosis caused by cholesterol crystals. Furthermore, colchicine may inhibit phagocy-tosis and neutrophil activity. 4 C-reactive thus the persuasiveness of the In addition, manual should be in this affected to some extent by differences in the therapeutic doses and usage time of colchicine among the included studies. Finally, the topics of dosage time need to be further discussed by articles with a larger sample size. important clarify
Improving risk assessment in indeterminate pediatric thyroid FNA biopsies

Pediatric thyroid nodules differ in significant ways from their adult counterparts. Thyroid nodules are less common in children overall, but the relative risk of malignancy is higher. Pediatric cancers are more frequently encountered in the setting of prior radiation exposure, whereas a small subset is associated with inherited syn-dromes, such as those seen with APC , DICER1 , or PTEN mutations. Although a large majority of these cancers are papillary carcinomas, the mutational profile of these tumors differs from the adult population with a lower frequency of BRAF V600E point mutations and a higher incidence of RET/PTC translocations. The clinical management of pediatric thyroid cancer also poses unique challenges. Even in patients with advanced tumors, disease- specific mortality is low. Morbidity is often secondary to treatment and potentially includes long- term effects of radiation therapy. At the same time, there is a natural tension between the desire to avoid excessive treatment and the potential implications of insufficiently aggressive intervention in a young patient with a lengthy anticipated lifespan.
Flow Behaviors of Gas-Solid Injector by 3D Simulation with Kinetic Theory of Granular Flow

由 Eulerian 途径的一个煤气固体的注射者的流动行为上的计算研究被执行。 煤气的阶段与 k- 被建模狂暴的模型和粒子阶段与小粒的流动的运动理论被建模。 由 Eulerian 二液体的模型(TFM ) 的模拟与由分离元素方法(DEM ) 和实验的相应结果相比。 它被看模仿的结果在对的合理同意的那 TFM 试验性并且模仿的 DEM 结果。 基于 TFM 模拟，煤气固体的流动模式，煤气的速度，粒子速度和静电干扰在不同开车喷气速度， backpressure 和会聚的节角度下面的压力被获得。 结果证明平均轴的煤气的速度严厉地减少了然后稍微在水平传送增加了到经常的价值的时间尖叫。 轴的粒子速度开始增加了然后减少的时间一般水准，但是在会聚的节的插头区域，粒子速度显著地再次增加了到最大的价值。 总体上，静态的压力分发变化趋势被发现在驾驶煤气的速度， backpressure 和会聚的节角度上独立。 然而，静态的压力随会聚的节角度和煤气的喷气速度的增加增加了。 到 backpressure 的静态的压力的差别与增加 backpressure 增加了。
Use of machine learning for comparing disease risk scores and propensity scores under complex confounding and large sample size scenarios: a simulation study

Background: The surge of treatments for COVID-19 in the ongoing pandemic presents an exemplar scenario with low prevalence of a given treatment and high outcome risk. Motivated by that, we conducted a simulation study for treatment effect estimation in such scenarios. We compared the performance of two methods for addressing confounding during the process of estimating treatment effects, namely disease risk scores (DRS) and propensity scores (PS) using different machine learning algorithms. Methods: Monte Carlo simulated data with 25 different scenarios of treatment prevalence, outcome risk, data complexity, and sample size were created. PS and DRS matching with 1: 1 ratio were applied with logistic regression with least absolute shrinkage and selection operator (LASSO) regularization, multilayer perceptron (MLP), and eXtreme Gradient Boosting (XgBoost). Estimation performance was evaluated using relative bias and corresponding confidence intervals. Results: Bias in treatment effect estimation increased with decreasing treatment prevalence regardless of matching method. DRS resulted in lower bias compared to PS when treatment prevalence was less than 10%, under strong confounding and nonlinear nonadditive data setting. However, DRS did not outperform PS under linear data setting and small sample size, even when the treatment prevalence was less than 10%. PS had a comparable or lower bias to DRS when treatment prevalence was common or high (10% - 50%). All three machine learning methods had similar performance, with LASSO and XgBoost yielding the lowest bias in some scenarios. Decreasing sample size or adding nonlinearity and non-additivity in data improved the performance of both PS and DRS. Conclusions: Under strong confounding with large sample size DRS reduced bias compared to PS in scenarios with low treatment prevalence (less than 10%), whilst PS was preferable for the study of treatments with prevalence greater than 10%, regardless of the outcome prevalence.
Increase in coercive measures in psychiatric hospitals in Germany during the COVID-19 pandemic

Objective : To examine whether the pandemic in 2020 caused changes in psychiatric hospital cases, the percentage of patients exposed to coercive interventions, and aggressive incidents. Methods ; We used the case registry for coercive measures of the State of Baden-Wuerttemberg, comprising case-related data on mechanical restraint, seclusion, physical restraint, and forced medication in each of the States 31 licensed hospitals treating adults, to compare data from 2019 and 2020. Results: The number of cases in adult psychiatry decreased by 7.6% from 105,782 to 97,761. The percentage of involuntary cases increased from 12.3 to 14.1%, and the absolute number of coercive measures increased by 4.7% from 26,269 to 27,514. The percentage of cases exposed to any kind of coercive measure increased by 24.6% from 6.5 to 8.1%, and the median cumulative duration per affected case increased by 13.1% from 12.2 to 13.8 hrs, where seclusion increased more than mechanical restraint. The percentage of patients with aggressive incidents, collected in 10 hospitals, remained unchanged. Conclusions: While voluntary cases decreased considerably during the pandemic, involuntary cases increased slightly. However, the increased percentage of patients exposed to coercion is not only due to a decreased percentage of voluntary patients, as the duration of coercive measures per case also increased. The changes that indicate a deterioration in treatment quality were probably caused by the multitude of measures to manage the pandemic. The focus of attention has shifted from prevention of coercion to prevention of infection.
High-Strength Cement Composites Modified with a Complex Additive Hyper Plasticizer - Bentonite

The paper presents the results of research on creating a high-strength cement composite using a complex additive. The optimal concentrations of additives of the Odolit-K hyper plasticizer in combination with bentonite have been determined. A significant decrease in the w / c ratio and an increase in the cement stone's strength was obtained. High-strength cement composites have been obtained with the optimal content of the complex additive. The volume-weighted average crystallite sizes were calculated using the Scherrer formula on the basis of X-ray studies. Deformation diagrams of statically loaded samples of prisms of the basic and control compositions of high-strength concrete were obtained. Deformation diagrams are investigated.
Dynamics of ferroelectric polarization and internal electric field in PbTiO3/SrTiO3 superlattices

Abstract We study the dynamics of polarization and internal electric field in the PbTiO3/SrTiO3 (PT/ST) superlattices using the Landau–Khalatnikov equation. Apart from the polarization hysteresis loop, the hysteresis loop of the internal electric field is also observed. The effects of thickness ratio and temperature on the switching dynamics of superlattices are investigated. We found that the dynamics of polarization switching is directly correlated with the internal electric field. The change of sign in the internal electric field implies the occurrence of polarization switching in the ferroelectric superlattices.
Object detection for helmet wearing situation during the process of construction

In the process of construction, it is not uncommon for workers to enter the construction area without wearing safety helmet correctly. In order to reduce the occurrence of such accidents, this paper uses the target detection algorithm to quickly check the situation of construction workers wearing safety helmets. Firstly, the Stochastic Gradient Descent algorithm is used to improve the speed of target detection. Secondly, for different sizes of helmets, the receptive field is increased by dilated convolution to achieve multi-scale target detection. Thirdly, in order to improve the positioning and classification accuracy of the model, the feature fusion method of skip connection is used to improve the feature extraction ability of the network. Finally, the identity of construction personnel is determined according to the color of safety helmet to improve the expression ability of detection results. The experimental results show that the detection speed of this algorithm reaches 32fps, and the MAP reaches 88%, which can meet the detection requirements in the actual engineering scene. At the same time, the matching of helmet type and worker identity is realized.
Reduced Current Distortion of Three-Phase Three-Switch Buck-Type Rectifier using Carrier Based PWM in EV Traction Battery Charging Systems

This study investigates an economic and highly efficient power-converter topology and its modulation scheme for 60 kW rapid EV charger system. The target system is a three-phase three-switch buck-type rectifier topology. A new carrier-based PWM scheme, which is characterized by simple implementation using logic gates, is introduced in this paper. This PWM scheme replaces the diode rectifier equivalent switching state with an active switching state to produce the same effective current flowing path. As a result, the distortion of input current during the polarity reversal of capacitor line voltage can be mitigated. The proposed modulation technique is confirmed through simulation verification. The proposed modulation technique and its implementation scheme can expand the operation range of the three-phase three-switch buck-type rectifier with high-quality AC input and capacitor ripple current.
GrapHD: Graph-Based Hyperdimensional Memorization for Brain-Like Cognitive Learning

Memorization is an essential functionality that enables today's machine learning algorithms to provide a high quality of learning and reasoning for each prediction. Memorization gives algorithms prior knowledge to keep the context and define confidence for their decision. Unfortunately, the existing deep learning algorithms have a weak and nontransparent notion of memorization. Brain-inspired HyperDimensional Computing (HDC) is introduced as a model of human memory. Therefore, it mimics several important functionalities of the brain memory by operating with a vector that is computationally tractable and mathematically rigorous in describing human cognition. In this manuscript, we introduce a brain-inspired system that represents HDC memorization capability over a graph of relations. We propose GrapHD, hyperdimensional memorization that represents graph-based information in high-dimensional space. GrapHD defines an encoding method representing complex graph structure while supporting both weighted and unweighted graphs. Our encoder spreads the information of all nodes and edges across into a full holistic representation so that no component is more responsible for storing any piece of information than another. Then, GrapHD defines several important cognitive functionalities over the encoded memory graph. These operations include memory reconstruction, information retrieval, graph matching, and shortest path. Our extensive evaluation shows that GrapHD: (1) significantly enhances learning capability by giving the notion of short/long term memorization to learning algorithms, (2) enables cognitive computing and reasoning over memorization graph, and (3) enables holographic brain-like computation with substantial robustness to noise and failure.
STUDIES ON THE LIMESTONE FLORA OF JAPAN AND TAIWAN PART I

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