Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG

BACKGROUND: Diaphragmatic electromyographic (EMGdi) is a helpful method to reflect the respiratory center’s activity visually. However, the electrocardiogram (ECG) severely affected its weakness, limiting its use. OBJECTIVE: To remove the ECG artifact from the EMGdi, we designed a Morphological ECG subtraction method (MES) based on three steps: 1) ECG localization, 2) morphological tracking, and 3) ECG subtractor. METHODS: We evaluated the MES method against the wavelet-based dual-threshold and stationary wavelet filters using visual and frequency-domain characteristics (median frequency and power ratio). RESULTS: The results show that the MES method can preserve the features of the original diaphragm signal for both surface diaphragm signal (SEMGdi) and clinical collection of diaphragm signal (EMGdi_clinic), and it is more effective than the wavelet-based dual-threshold and stationary wavelet filtering methods. CONCLUSION: The MES method is more effective than other methods. This technique may improve respiratory monitoring and assisted ventilation in patients with respiratory diseases.
The FomYjeF Protein Influences the Sporulation and Virulence of Fusarium oxysporum f. sp. momordicae

Fusarium oxysporum causes vascular wilt in more than 100 plant species, resulting in massive economic losses. A deep understanding of the mechanisms of pathogenicity and symptom induction by this fungus is necessary to control crop wilt. The YjeF protein has been proven to function in cellular metabolism damage-repair in Escherichia coli and to play an important role in Edc3 (enhancer of the mRNA decapping 3) function in Candida albicans, but no studies have been reported on related functions in plant pathogenic fungi. In this work, we report how the FomYjeF gene in F. oxysporum f. sp. momordicae contributes to conidia production and virulence. The deletion of the FomYjeF gene displayed a highly improved capacity for macroconidia production, and it was shown to be involved in carbendazim’s associated stress pathway. Meanwhile, this gene caused a significant increase in virulence in bitter gourd plants with a higher disease severity index and enhanced the accumulation of glutathione peroxidase and the ability to degrade hydrogen peroxide in F. oxysporum. These findings reveal that FomYjeF affects virulence by influencing the amount of spore formation and the ROS (reactive oxygen species) pathway of F. oxysporum f. sp. momordicae. Taken together, our study shows that the FomYjeF gene affects sporulation, mycelial growth, pathogenicity, and ROS accumulation in F. oxysporum. The results of this study provide a novel insight into the function of FomYjeF participation in the pathogenicity of F. oxysporum f. sp. momordicae.
Living in a Desert: Examining Scorpion Beta Diversity in Egyptian Drylands from a Macroecological Perspective

Drylands correspond to ca. 40% of the world's land surface. Because of their ecological importance, these areas are regularly considered for agricultural purposes. Scorpion assemblages often exhibit higher levels of species diversity in dry habitats and are beneficial indicators in ecological studies in such environments. In this study, we investigated the effects of climatic and spatial predictors on beta diversity patterns among scorpion assemblages distributed in the drylands of Egypt. Scorpion occurrences were compiled from the scientific literature. For each location, we created a set of climatic variables related to precipitation, temperature, and solar irradiation, as well as spatial predictors. A total of 134 scorpion occurrences were obtained, comprising 21 species grouped into three families. Climatic and spatial variables together influenced the patterns of scorpion diversity in Egyptian landscapes. Species replacement accounted for 69% of the total beta diversity. In addition, species replacement was positively affected by climatic and spatial variables. Our results suggest a reciprocal link between the region's ecological history and the patterns of beta diversity observed in scorpion assemblages from Egyptian drylands.
A person-centred approach to ethnic and national identity and its relation to subjective well-being among Korean New Zealanders

ABSTRACT This paper examined 1,270 Korean New Zealanders in terms of the patterns of their Korean ethnic and New Zealand national identities and how these orientations relate to their subjective well-being. This study revealed the four profiles of identity orientations: (1) strong levels of both ethnic and national identity (Integrated Identity); (2) strong ethnic and weak national identity (Separated Identity); (3) weak ethnic and strong national identity (Assimilated Identity); and (4) weak ethnic and weak national identity (Marginalised Identity). The separated identity orientation was slightly more prevalent among the Korean New Zealander sample, followed by integrated and marginalised identity orientations, with assimilation being the least common. Korean New Zealanders in the integrated identity profile reported the highest levels of subjective well-being, while those in the marginalised identity profile reported the lowest. The levels of subjective well-being between the separated and the assimilated identity profiles were similar. These findings underscore the importance of fostering a sense of belonging to the ethnic group and/or the host society as a booster to enhance life satisfaction and positive affect and also as a buffer against negative affect. This paper also discussed implications for New Zealand immigration policies, and future research directions.
Optimization of stack filters based on mirrored threshold decomposition

Optimizing stack filters is the most pivotal issue of the study of stack filters theory.The threshold decomposition is one of stack filters property and has two modes: traditional threshold decomposition and mirrored threshold decomposition.The stack filters defined in the binary domain of mirrored threshold decomposition have been empowered not only with lowpass filtering characteristics but with bandpass and highpass characteristics as well.In this paper,under MAE criterion,a fast adaptive optimization algorithm based on mirrored threshold decomposition is presented.This algorithm restricts stacking properties of cost vector and estimates its astringency in order to attain positive Boolean function of optimal stack filters.The performance of optimal stack filters is illustrated by simulations.The results of experiments show that the optimal stack filters can suppress noise and protect the details of image effectively,which improve filtering capability.
Comparative Aspects of Ricin Toxicity by Inhalation

The pathogenesis of ricin toxicity following inhalation has been investigated in many animal models, including the non-human primate (predominantly the rhesus macaque), pig, rabbit and rodent. The toxicity and associated pathology described in animal models are broadly similar, but variation appears to exist. This paper reviews the published literature and some of our own unpublished data and describes some of the possible reasons for this variation. Methodological variation is evident, including method of exposure, breathing parameters during exposure, aerosol characteristics, sampling protocols, ricin cultivar, purity and challenge dose and study duration. The model species and strain used represent other significant sources of variation, including differences in macro- and microscopic anatomy, cell biology and function, and immunology. Chronic pathology of ricin toxicity by inhalation, associated with sublethal challenge or lethal challenge and treatment with medical countermeasures, has received less attention in the literature. Fibrosis may follow acute lung injury in survivors. There are advantages and disadvantages to the different models of pulmonary fibrosis. To understand their potential clinical significance, these factors need to be considered when choosing a model for chronic ricin toxicity by inhalation, including species and strain susceptibility to fibrosis, time it takes for fibrosis to develop, the nature of the fibrosis (e.g., self-limiting, progressive, persistent or resolving) and ensuring that the analysis truly represents fibrosis. Understanding the variables and comparative aspects of acute and chronic ricin toxicity by inhalation is important to enable meaningful comparison of results from different studies, and for the investigation of medical countermeasures.
Maximum General Sum-Connectivity Index for Trees with Given Independence Number 1

Das, Xu and Gutman [MATCH Commun. Math. Comput. Chem. 70(2013) 301-314] proved that in the class of trees of order n and independence number s, the spur Sn,s maximizes both first and second Zagreb indices and this graph is unique with these properties. In this paper, we show that in the same class of trees T , Sn,s is the unique graph maximizing zeroth-order
Optimization of observer trajectories for bearings-only target localization

The problem of bearings-only target localization is to estimate the location of a fixed target from a sequence of noisy bearing measurements. Although, in theory, this process is observable even without an observer maneuver, estimation performance (i.e., accuracy, stability and convergence rate) can be greatly enhanced by properly exploiting observer motion to increase observability. This work addresses the optimization of observer trajectories for bearings-only fixed-target localization. The approach presented herein is based on maximizing the determinant of the Fisher information matrix (FIM), subject to state constraints imposed on the observer trajectory (e.g., by the target defense system). Direct optimal control numerical schemes, including the recently introduced differential inclusion (DI) method, are used to solve the resulting optimal control problem. Computer simulations, utilizing the familiar Stansfield and maximum likelihood (ML) estimators, demonstrate the enhancement to target position estimability using the optimal observer trajectories.
SDG26 Is Involved in Trichome Control in Arabidopsis thaliana: Affecting Phytohormones and Adjusting Accumulation of H3K27me3 on Genes Related to Trichome Growth and Development

Plant trichomes formed by specialized epidermal cells play a role in protecting plants from biotic and abiotic stresses and can also influence the economic and ornamental value of plant products. Therefore, further studies on the molecular mechanisms of plant trichome growth and development are important for understanding trichome formation and agricultural production. SET Domain Group 26 (SDG26) is a histone lysine methyltransferase. Currently, the molecular mechanism by which SDG26 regulates the growth and development of Arabidopsis leaf trichomes is still unclear. We found that the mutant of Arabidopsis (sdg26) possessed more trichomes on its rosette leaves compared to the wild type (Col-0), and the trichome density per unit area of sdg26 is significantly higher than that of Col-0. The content of cytokinins and jasmonic acid was higher in sdg26 than in Col-0, while the content of salicylic acid was lower in sdg26 than in Col-0, which is conducive to trichome growth. By measuring the expression levels of trichome-related genes, we found that the expression of genes that positively regulate trichome growth and development were up-regulated, while the negatively regulated genes were down-regulated in sdg26. Through chromatin immunoprecipitation sequencing (ChIP-seq) analysis, we found that SDG26 can directly regulate the expression of genes related to trichome growth and development such as ZFP1, ZFP5, ZFP6, GL3, MYB23, MYC1, TT8, GL1, GIS2, IPT1, IPT3, and IPT5 by increasing the accumulation of H3K27me3 on these genes, which further affects the growth and development of trichomes. This study reveals the mechanism by which SDG26 affects the growth and development of trichomes through histone methylation. The current study provides a theoretical basis for studying the molecular mechanism of histone methylation in regulating leaf trichome growth and development and perhaps guiding the development of new crop varieties.
Hallux Partial Necrosis Associated with Antiphospholipid Syndrome: The Importance of Early Accurate Diagnosis

This study highlights the importance of having a high clinical suspicion of hypercoagulopathy such as antiphospholipid syndrome (APS) in podiatric patients with normal foot pulses and normal standard coagulation tests. APS is an autoimmune disease that is characterized by inflammatory thrombosis in the arteries and veins and obstetric complications such as pregnancy loss. APS usually affects vessels of the lower extremities. We report herein the case of a 46-year-old woman with previous episodes of pre-eclampsia who suffered from partial ischemic necrosis of the hallux of the left foot. After several ischemic episodes of the hallux, with increased risk of toe amputation, the patient was finally diagnosed with APS and treated with specific anticoagulant medication. The patient’s symptoms subsided, and toe amputation was prevented. Early accurate diagnosis and appropriate clinical management are critical to providing optimal outcomes and reducing the risk of amputation.
Plasma Cytokeratin-18 Fragment Level Reflects the Metabolic Phenotype in Obesity

There is growing interest in the non-invasive identification and monitoring of the outcome of liver damage in obese patients. Plasma cytokeratin-18 (CK-18) fragment levels correlate with the magnitude of hepatocyte apoptosis and have recently been proposed to independently predict the presence of non-alcoholic steatohepatitis (NASH). The aim of the study was to analyze the associations of CK-18 with obesity and related complications: insulin resistance, impaired lipid metabolism and the secretion of hepatokines, adipokines and pro-inflammatory cytokines. The study involved 151 overweight and obese patients (BMI 25–40), without diabetes, dyslipidemia or apparent liver disease. Liver function was assessed based on alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and the fatty liver index (FLI). CK-18 M30 plasma levels, FGF-21, FGF-19 and cytokines were determined by ELISA. CK-18 values >150 U/l were accompanied by high ALT, GGT and FLI, insulin resistance, postprandial hypertriglyceridemia, elevated FGF-21 and MCP-1 and decreased adiponectin. ALT activity was the strongest independent factor influencing high CK-18 plasma levels, even after an adjustment for age, sex and BMI [β coefficient (95%CI): 0.40 (0.19–0.61)]. In conclusion, the applied CK-18 cut-off point at 150 U/l allows to distinguish between two metabolic phenotypes in obesity.
AVA from prestack 3D VSP images

While walkaways have been used to measure AVO for a long time (Coulombe et al., 1991; Leaney, 1994) and elastic properties have been recovered by inversion under an assumption of lateral invariance (Malinverno and Leaney, 2005), the recovery of elastic properties away from the well has remained elusive due to the limited angular illumination provided by the typical multi-offset VSP geometry. Previous work on using walkaway VSPs for pre-stack elastic inversion (Ahmad et al., 2012) made use of a 2D assumption and wavefield extrapolation to mimic a surface seismic geometry (e.g. Fuller and Sterling, 2008) but such approaches break down in 3D (Du et al., 2014). The advent of elastic full waveform inversion (Podgornova et al., 2013), however promising, is presently only 2D and computationally expensive so an efficient process to recover elastic properties from 3D VSPs is needed.
Sampling and Assignment Mechanisms in Experiments, Surveys and Observational

Summary A general framework is given for examining the role of mechanisms for treatment assignment and unit selection in experiments, surveys and observational studies. Conditions are established under which these mechanisms can be ignored for model-based inference. Examples are presented to show how inference can incorporate the mechanisms when the conditions do not hold. Two of the most important tasks facing an applied statistician are the design and analysis of sample surveys, and the design and analysis of experiments. Despite the many apparent links between surveys and experiments identified by Fienberg & Tanur (1987), and the contributions to both subjects by statisticians such as Yates and Cochran, the theory and methods of these two subjects appear quite different. Why should this be? Sample survey design and analysis has grown from the need for descriptive statistics in the government and commercial stores. In contrast experiments use statistics analytically to test hypotheses for example, and are carried out most frequently in the industrial and scientific sectors. Government surveys are still used primarily to describe the properties of a finite population at a fixed point in time but many commercial surveys attempt to explain relationships between variables that will hold in the future, so they are explanatory or analytic rather than descriptive. In the analysis of an explanatory survey or of an experiment one aim is to find evidence for a law-like relationship, for causal explanations rather than descriptions. Wold (1967) addressed the problems of reaching causal conclusions from nonexperimental data. He argued that experimental knowledge is reproducible knowledge, the reproducibility arising from the control exerted by the scientist over the assignment of treatments. It is the scientist's control over his material that is the most important distinction between surveys and experiments; in surveys there is control over sampling of units while in experiments there is control over the assignment of treatments to units. From this difference in control flows the difference in the approaches to the design and, more importantly, the analysis of surveys and experiments. Experiments can be carried out within surveys. Brewer et al. (1977) give examples of experimental designs at the pilot stage of a survey for testing questionnaire layouts, diary
Incidence of HIV Infection among HIV-Exposed Iinfants at Gondar University Hospital from 2019-2021: A Prospective Cohort Study

Background Mother-to-child transmission (MTCT) of human immunodeficiency virus (HIV) is decreasing worldwide; however, achieving the MTCT elimination target of 2% by 2020 and 0% by 2030 is challenging in resource-limited countries. Preventing mother-to-child transmission (PMTCT) is a key strategy in eliminating new pediatric human immunodeficiency virus (HIV) infection Strengthening PMTCT program is one of the key mechanisms for the elimination of Pediatric HIV infection and improving maternal and newborn survival. Assessing the incidence of HIV infection among HIV exposed infants is critical to devise an important preventive strategy which was the main objective of this study. Methods A prospective Cohort study was conducted at Gondar University Comprehensive Specialized Hospital, PMTCT clinic to assess the incidence of HIV infection among HIV exposed infants from 2019-2021. Results The overall incidence of HIV infection among HIV exposed infants was 3.6%. HIV infection rate was significantly increased among HIV exposed infants coming out of Gondar, Infants with developmental failure and Infants with Unknown fathers' HIV status compared to their counterpart. Conclusions The incidence of HIV infection among 307 HIV-exposed infants was 3.6% which is higher than the expected standard. The lost to follow up rate was also significant (9.4%). These finding showed that strengthening the PMCT service is mandatory.
Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

As unmanned vehicles become smaller and more autonomous, it is becoming feasible to use them in large groups with comparatively few human operators. Design and analysis of such distributed systems are complicated by the many interactions among agents and phenomena of human behavior. In particular, human susceptibility to fatigue and cognitive overload can introduce errors and uncertainty into the system. In this paper, we demonstrate how advanced computational tools can help to overcome these engineering difficulties by optimizing multirobot, multioperator surveillance systems for cost, speed, accuracy, and stealth according to diverse user preferences in multiple case studies. The tool developed is a graphical user interface that returns the optimal number and mix of diverse agent types as a function of the user's trade‐off preferences. System performance prediction relies on a multiagent simulation with submodels for human operators, fixed‐wing unmanned aerial vehicles (UAVs), quadrotor UAVs, and flapping wing UAVs combined in different numbers.
Defogging Image Restoration Based on Four Order Partial Differential Equation

The fog image contrast is reduced with may gray areas. In order to effectively remove the image of the mist and the effect of image in the vision. An image degradation model is built based on the fog image attenuation model and atmospheric optical model. The energy functions are constructed using the scene depth and image gradient,and the energy function minimum calculated using the four order partial differential equation and some known information. The fog image restoration algorithm is achieved with the four order partial differential equation by finite difference numerical method. The experimental results that better image defogging effect.
Artificial calibration source for ALMA radio interferometer

The ALMA (Atacama Large Millimeter/submillimeter Array) radio interferometer has some different types of antennas which have a variation of gain and leakages across the primary beam of an individual antenna. We have been developing an artificial calibration source which is used for compensation of individual difference of antennas. In a high-frequency antenna, using astronomical sources to do calibration measurement would be extremely time consuming, whereas with the artificial calibration source becomes a realistic possibility. Photonic techniques are considered to be superior to conventional techniques based on electronic devices in terms of wide bandwidth and high-frequency signals. Conversion from an optical signal to a millimeter/sub-millimeter wave signal is done by a photo-mixer.
Abnormal Operating Condition Identification of Industrial Processes Based on Deep Learning With Global-Local Slow Feature Analysis

Ensuring long-term safe and efficient operation of industrial processes relies on real-time identification of abnormal operating conditions. However, industrial processes frequently switch among diverse operating conditions and face harsh production environments. As a result, some extreme cases exist in historical abnormal samples can mask some slight anomalies, making them show similar process dynamics to normal operating conditions. To address this issue, this study proposes a global-local slow-feature-analysis-based convolutional neural network (GLSFA-CNN). A global slow feature analysis (SFA) model extracts coarse-scale slow features at a macroscopic level to distinguish anomalies with different process dynamics, while a local SFA algorithm extracts real-time and fine-scale slow features at a microscopic level to identify anomalies with similar process dynamics. By combining global and local slow features, anomalies with similar or different dynamics can be simultaneously identified. The one-dimensional convolutional neural network (1-D-CNN) is then used to automatically extract deep features from the global-local slow features and identify abnormal operating conditions. The industrial experiment shows that the proposed method outperforms other traditional methods and achieves high anomaly identification accuracy for the industrial process with switching conditions and extreme cases.