Miracle-dz/UniFAR-FTUs huggingface dataset:
Elevated liver enzymes in hospitalized patients with COVID-19 in Singapore

Abstract Liver dysfunction in patients with COVID-19 (coronavirus disease 2019) has been described. However, it is not clear if the presence of abnormal liver function tests at presentation was related to underlying undiagnosed liver disease, or a result of the viral infection. We retrospectively examined the first 554 consecutive polymerase chain reaction positive SARS-CoV-2 patients admitted from February 2020 to April 2020 to our academic medical centre. We reviewed their clinical data, chest radiography and laboratory studies obtained within 24 hour of admission. Despite similar hemodynamic parameters, we found significant aspartate transaminase elevation (64 ± 141 vs 35 ± 23 U/L, P < .001) in those with pneumonia compared to those without. Elevated liver enzymes were seen in 102 patients (18.4%). They presented with higher temperatures (38.5 ± 0.9 vs 37.5 ± 0.8 degC, P = .011), higher total white cell counts (6.95 ± 2.29 vs 6.39 ± 2.19 x109/L, P = .021), serum ferritin (240 ± 274 vs 165 ± 198 ng/ml, P = .002) and lactate dehydrogenase (632 ± 912 vs 389 ± 107 U/L, P < .001). These patients were more likely to require intensive care (6.9% vs 2.7% P = .036) and mechanical ventilation (5.9% vs 2.2%, P = .046). Migrant workers from dormitories had a higher rate of baseline liver function test abnormalities (88/425 vs 14/129, P = .01), which were more likely to persist at the time of discharge. Despite relatively mild COVID-19 disease, there was a significant prevalence of liver dysfunction, particularly amongst migrant workers. Elevated liver enzymes were associated with more severe disease, despite similar haemodynamic characteristics. Future studies should explore whether pre-existing liver disease may predispose to more severe COVID-19 disease.
Aberrant PTEN, PIK3CA, pMAPK, and TP53 expression in human scalp and face angiosarcoma

Abstract Angiosarcoma is a rare, highly aggressive malignant tumor originating from endothelial cells that line the lumen of blood or lymphatic vessels. The molecular mechanisms of scalp and face angiosarcoma still need to be elucidated. This study aimed to investigate the expression of phosphatase and tensin homolog (PTEN), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), phosphorylated mitogen-activated kinase-like protein (pMAPK), and tumor protein p53 (TP53) in scalp and face angiosarcoma and to assess tumor tissue apoptosis. The expression and intracellular distribution of PTEN, PIK3CA, pMAPK, and TP53 proteins in 21 specimens of human scalp and face angiosarcoma and 16 specimens of human benign hemangioma were evaluated using immunohistochemistry. Tumor cell apoptosis was assessed by terminal deoxyribonucleotide transferase-mediated dUTP nick end-labeling staining. Significantly lower PTEN but higher PIK3CA, pMAPK, and TP53 immunostaining were detected in the angiosarcoma specimens than in the benign hemangioma specimens(P < .01). The angiosarcoma tissues exhibited significantly higher apoptosis indices than the benign hemangioma tissues (P < .01). The positive expression rates of PIK3CA, pMAPK, and TP53 were correlated with the degree of tumor differentiation in the human scalp and face angiosarcoma. The PI3K, MAPK, and TP53 pathways might be involved in angiosarcoma tumorigenesis in humans and may serve as therapeutic targets for the effective treatment of this malignancy.
Association of cystatin C with coronary artery calcification in patients undergoing multidetector computed tomography

Abstract Cystatin C is associated with atherosclerosis, but the relationship between cystatin C and coronary artery calcification (CAC) is uncertain. The purpose of this study was to evaluate the predictive value of cystatin C on the occurrence and severity of CAC. A total of 1447 hospitalized patients with coronary computed tomography angiography were selected in this study. According to the CAC score (CACS), patients were divided into calcification group (with CAC, n = 749) and control group (without CAC, n = 698). The calcification group was further divided into low calcification group (CACS < 100, n = 407), medium calcification group (CACS 100–400, n = 203), and high calcification group (CACS≥400, n = 139). Patients with CAC had higher cystatin C level than those in control group (P < .05). With the increase of calcification score, the cystatin C level showed an upward trend. The cystatin C level in the high calcification group was significantly higher than those in the low and medium calcification group (P < .05). ROC curve analysis showed that cystatin C had a high predictive value for the occurrence of CAC [area under the curve 0.640, 95% confidence interval (95% CI) 0.591–0.690, cut-off value 0.945 mg/L, sensitivity 0.683, specificity 0.558, P < . 05] and severe CAC (area under the curve 0.638, 95% CI 0.550–0.762, cut-off value 0.965 mg/L, sensitivity 0.865, specificity 0.398, P < .05). Multivariate logistic regression analysis showed that cystatin C was an independent predictor of severe CAC (AOR 3.748, 95% CI 1.138–10.044, P < .05). Cystatin C was significantly associated with the occurrence and severity of CAC, suggesting that cystatin C had the potential as a predictor of CAC.
STUDIES ON EOS OF SHOCK GENERATED ARGON PLASMAS

Argon plasmas with uniform density and temperature are generated by passage of a planar shock wave through argon gas. The EOS of argon plasma, covering the thermodynamic states at temperature of 1.4eV～2.2eV and in density of 0.0083～0.015g/cm 3, are investigated through measuring the emitted radiance versus time records . Comparisons of the measured EOS with the calculated ones demonstrate the Saha model can be used to describe well the essential behavior of argon plasma under the thermodynamic condition above mentioned. Authors' method of determining the EOS is different from Erskine's.
Improving Adversarial Robustness in 3D Point Cloud Classiﬁcation via Self-Supervisions

3D point cloud data is increasingly used in safety-critical applications such as autonomous driving. Thus, robustness of 3D deep learning models against adversarial attacks is a major consideration. In this paper, we systematically study the impact of various self-supervised learning proxy tasks on different architectures and threat models for 3D point clouds. Speciﬁcally, we study MLP-based (PointNet), convolution-based (DGCNN), and transformer-based (PCT) 3D architectures. Through comprehensive experiments, we demonstrate that appropriate self-supervisions can signiﬁcantly enhance the robustness in 3D point cloud recognition, achieving considerable improvements compared to the standard adversarial training baseline. Our analysis reveals that local feature learning is desirable for adversarial robustness since it limits the adversarial propagation between the point-level input perturbations and the model’s ﬁnal output. It also explains the success of DGCNN and the jigsaw proxy task in achieving 3D robustness.
Correlation between Partition Coefficients Polymer/Food Simulant, KP,F, and Octanol/Water, Log POW ― a New Approach in support of Migration Modeling and Compliance Testing

An investigation on the migration of various migrants from low-density polyethylene (LDPE) into food simulants was undertaken to determine the correlation of partition coefficients between LDPE/food simulants, K P,F , and octanol/water, P OW . The migration tests were carried out using four simulants (10 %, 50 %, 95 % ethanol and olive oil) in contact with a LDPE film which was spiked with 15 compounds. These model migrants cover a wide range of potential migrants in plastics food packaging materials and can be characterized by octanol/water partition coefficients ranging from log P OW = 0.36 to 18.08. In all simulants a correlation of increasing log P OW with increasing log K P,F was found. Assuming a linear relationship, correlation coefficients (R) for 10 %, 50 %, 95 % ethanol and olive oil were 0.98, 0.65, 0.80 and 0.68, respectively. Using the correlation line as a calibration curve, log K P,F can be predicted from the log P OW values of the migrants for a given food simulant and, hence, migrating amounts can be estimated by migration modelling provided the migrant concentration in the polymer is known. This approach is a new estimation procedure to obtain K P,F values from easily accessible P OW values which can significantly reduce the efforts for compliance assessment by minimizing time and costs to be spent compared to carrying out an enormous number of specific migration test. Furthermore, this approach will support experimental migration testing since it provides a method to determine which simulant is appropriate for a given foodstuff.
Turkish Patronymic Surnames Ending with -oğlu ‘Son of

This study examines Turkish patronymic surnames ending with the suffix -oglu ‘son of. ’ For this examination, this investigation compiled three corpora of Turkish surnames (N = 10,369) representative of the Turkish population. The aim of this corpus analysis was the identification of the conceptual and grammatical functional elements of these surnames as markers of linguistic and cultural diversity within Turkey. The findings reveal that the Turkish patronymic surnames did not merely denote the name of someone’s father. They also reflect manifold cognitive diversity and express meta-language awareness of Turkey’s intercultural richness. Consequently, this article contends that integrating insights gained from surname research into the foreign language classroom may assist learners of Turkish in overcoming language and cultural barriers. As this study concludes, the findings presented here and in analogous research can help language learners gain a better understanding of the meanings and cultural symbolism embedded in names.
Energy Efficient Scheduling Techniques for Real-time Embedded Systems Energy Efficient Scheduling Techniques for Real-time Embedded Systems Energy Efficient Scheduling Techniques for Real-time Embedded Systems

Energy Efficient Scheduling Techniques for Real-Time Embedded Systems. (May 2004) Rajesh Babu Prathipati, B.Tech., R.E. C. Warangal, India Chair of Advisory Committee: Dr. Rabi N. Mahapatra Battery-powered portable embedded systems have been widely used in many applications. These embedded systems have to concurrently perform a multitude of complex tasks under stringent time constraints. As these systems become more complex and incorporate more functionality, they became more power-hungry. Thus, reducing power consumption and extending battery lifespan while guaranteeing the timing constraints has became a critical aspect in designing such systems. This gives rise to three aspects of research: (i) Guaranteeing the execution of the hard real-time tasks by their deadlines, (ii) Determining the minimum voltage under which each task can be executed, and (iii) Techniques to take advantage of run-time variations in the execution times of tasks. In this research, we present techniques that address the above aspects in single and multi processor embedded systems. We study the performance of the proposed techniques on various benchmarks in terms of energy savings.
Effects of chlorogenic acid on mouse insulin resistance development induced by high fat emulsion

Aim To investigate the effects and mechanisms of chlorogenic acid(CGA) against insulin resistance(IR) enduced by high-fat emulsion.Methods SPF grade female Kunming mice were randomly divided into 3 groups,10 mice for each group.All groups were free to normal diet and water,besides,the control group received saline as placebo by gastric perfusion.Model group was given high-fat emulsion(HFE) by gastric perfusion,and the CGA interference group(CGA+HFE) was given both high-fat emulsion and CGA(20 mg·kg-1 body weight) by gastric perfusion at the same time.Oral glucose tolerance(OGT) was tested with glucose meter,the serum content of fasting blood glucose(FBG) was detected by ELISA.Total cholesterol(TC),high density lipoprotein cholesterol(HDL-C),low density lipoprotein cholesterol(LDL-C) and triglycerides(TG) were determined with automatic biochemical analyzer.The expression of G-6-Pase mRNA in the liver and GLUT-4 mRNA in the skeletal muscle were detected by RT-PCR.Pathological changes of kidney and pancreas were observed by HE dying,and the distribution and quantities of β-cell in the pancreas were analyzed by immunohistochemistry.Results The HFE group mice showed obvious IR,but CGA relieved these symptoms.The CGA interference group mice had better glucose tolerance,higher ISI and lower HOMA-IR index.And the contents of TG,TC and LDL-C in serum were decreased in the CGA interference group.Compared with HFE group,the expression of G-6-Pase mRNA was down-regulated and GLUT-4 transcript was up-regulated in the CGA interference group.At the tissue level,CGA reduced the lesion of kidney and pancreas by high-fat emulsion.Conclusion CGA has hypoglycemic and hypolipidemic function,and can relieve the mouse IR development significantly.
Communicating with the Deaf and Hard of Hearing through Automatic Arabic Sign Language Translator

The needs of persons with disabilities are still being undermined even though persons with disabilities have proven to be productive members of the community when given the right education, support, and tools. Assistive devices are being designed, developed, and sold to provide persons with disabilities the tools to be able to become productive members. With the advent of new technologies, software development has also concentrated on the needs of persons with disabilities. With the widespread of software’s especially on mobile devices, researchers can now develop tools for the community to communicate, work, collaborate and deal normally with persons with disabilities. In this paper, an automatic Artificial Intelligence (AI) based Arabic Sign Language Translator is proposed. The system is able to capture the picture of the sign language performed by a person who is deaf or hard of hearing and provide real-time translation of the hand gestures. Novel features are proposed to be extracted from the images to be input to the four different classifiers namely; Random Forest (RF), Bagging classifier, Regression, and Random Tree (RT). The result shows that the Random Forest classifier with proposed extract features performs better by achieving 92.15% accuracy as compared using input image directly with classifiers.
A statistical reconstruction model for absorption CT with source uncertainty

Reconstruction methods for computed tomography are often based on the assumption that the source intensity and the detector response are known and static. In practice, however, both are unknown and must be estimated. An estimate of the combined source intensity and detector response is typically obtained by acquiring a number of so-called flat-field measurements, but this approach is oblivious to intensity drift, e.g. due to source instabilities, vibrating beamline components, etc. Discrepancies between the estimated response and true response can lead to severe artifacts in the reconstruction, especially for dose- and/or time-limited experiments. We propose a new, extended reconstruction model that jointly estimates the reconstruction, the detector response, and the (possibly time-varying) source intensity. We demonstrate through simulated experiments that the proposed reconstruction model leads to reconstructions with significantly reduced artifacts.
Phytotoxicity of Carbon Nanotubes Assessed by Brassica Juncea and Phaseolus Mungo

Two agronomic plant species were evaluated for the phytotoxicity of multi-walled carbon nanotubes (CNTs) using germination and seedling growth of Brassica juncea and Phaseolus mungo. Both B. juncea and P. mungo seeds showed 100% germination with the application of CNTs, which indicated their non-hazardous nature for the germination of the seeds. As the B. juncea seed was grown with CNTs at 10 � g/ml, 20 � g/ml, and 40 � g/ml, the enhancement of root growth was evidenced up to 138%, 202%, and 135%, respectively, compared to the control. In the case of B. juncea, the heights of the shoot and root were not affected at all by the studied CNTs’ concentrations; however, phytotoxicity was evidenced at 40 � g/ml CNTs by optical microscopy of the hairy root system, since a severe reduction in both the number of root hairs and their length was observed.
The association between postpartum depression and air pollution during pregnancy and postpartum period: a national population study in Taiwan

Epidemiological evidence shows the association between air pollutants and several mental health outcomes, including depression, sleep disturbance, dementia, childhood neurodevelopment and suicide. Pregnant women are believed to be more susceptible and vulnerable to environmental pollutants, and postpartum depression (PPD) is a prevalent debilitating mental disorder. However, data on the effects of exposure to air pollution during pregnancy and postpartum period on the risk of PPD remain limited. This study aimed to evaluate the association between exposure to ambient air pollution during pregnancy and postpartum period and the incidence of PPD. The Taiwan Birth Cohort Study recruited representative 12% of all newborn in 2005 and their mothers by two-stage stratified sampling, including 21 248 mother–infant pairs. The occurrence of PPD was assessed by a self-reported questionnaire. Exposure to air pollutants during pregnancy and postpartum period was estimated using hybrid kriging/land-use regression (LUR) and integrated LUR-machine learning model based on data from the air monitoring stations. Logistic regression was then conducted to determine adjusted odds ratios (aORs) of PPD in relation to air pollutants. A total of 21 188 women were included in the final analysis, among whom 3,648 (17.2%) developed PPD within 6 months postpartum. The occurrence of PPD was significantly related to exposure to ambient concentrations of nitrogen dioxide (NO2) during first trimester after adjustment [aOR: 1.081 per interquartile range (10.67 ppb), 95% confidence interval: 1.003, 1.165], but not to particulate matter ⩽2.5 µm in diameter or carbon monoxide. Exposure to ambient NO2 during early pregnancy was significantly related to the occurrence of PPD among the women investigated in this population-based study.
IOT Smart Guidance Parking Search System for Open Space Parking Area

Open parking facilities can be automated and parking spaces can be easily operated by the implementation of IoT technology (Internet of Things). In this article, we present the evolution and prototyping of the open space smart guidance-parking search system, an IoT-based smart parking search system. The Smart Guidance Parking Searches System consists of i) An IOT module to monitor the availability of a parking slot and to update the parking lot status; and (ii) A web-based software allows users to view parking spaces available for a specific open space area. This paper addresses the existing system, device description, its functional specifications, the methods, and technologies used, the development/deployment of prototypes, along with the findings from the demonstration. This device serves as a guide for the user/driver to search for the parking slot occupancy in open/outdoor environments.
A hybrid technique for intelligent bank security system based on blink gesture recognition

Enhancement of bank security system plays an important role at the present time due to increasing attempts to expose it to many infringements by criminals. This paper proposes a hybrid technique of amplitude and duration to recognize its blink gestures to increase the accuracy of the human security system’s interaction for intelligent bank security, as this hybrid technique implemented analyzing of face, facial landmark detection, and the duration of the eye aspect ratio (EAR) for blink processes. The proposed hybrid technique is evaluated by experimenting a number of blink gesture with two eyes obtained from web camera and the results shows better and more effective analysis and provide high security bank system.
Identifying the Impact of Noise-Levels on Mental Stress: An EEG-fNIRS Study

Stress is a complex response that begins when people are exposed to various stressors, including psychological and environmental factors, which are associated with negative cognitive effects. However, little is known about their interactions within the brain. This research aimed to examine the influence of low and high noise levels in the workplace on changes in brain activity in the prefrontal cortex (PFC) during stressful psychological tasks by measuring synchronized functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG). The results showed a decreased oxygenated haemoglobin (HbO) concentrations in the right dorsolateral PFC and part of the frontopolar area when exposed to higher noise levels compared to lower levels. Results also showed a higher correlation between fNIRS-HbO and EEG-alpha power under stress conditions compared to other EEG bands. We suggest that higher levels of noise in the workplace may be directly related to increased psychological stress.
Successful Factors Determining the user behaviour in information system

The aim of this research is to investigation and explore the factors that drive the e-governance implementation and affect the government performance further because the government-citizen relationship in Syria. In this respect it is important to embrace the e-governance system to decide how effective it can be. There is also query if the previously established IS recognition frameworks can be used to determine the acceptance by Syrian citizens of the e-governance system. The survey issued a total of 600 questionnaires to the citizens of Syria. The research obtained approximately 385 responses, indicating a return rate of 62.83%. In the analysis of the results, Structural equation model (SEM) was used with AMOS version 21.0 to analyse the data. The findings indicate that five core determinants, namely, performance expectancy, effort expectancy, system flexibility, Citizens-Centricity, and facilitating conditions significantly influenced user intention to use E-governance system.
Effect on the Model of Government-Subsidized Dual-Channel Closed-loop Supply Chain: Taking Automobile Tire Recycling as an example

The speed of product updating iteration is getting faster and faster, which leads to more and more serious problems of waste of resources and carbon emissions, and the increasing attention to the sustainable use of resources in all countries of the world, and from the concept of sustainable development, many new ideas have been formed. At present, China’s economy is facing severe environmental pollution and resource shortage, and recycling waste resources is the key for enterprises to obtain better development prospects, so the closed-loop supply chain model has become the focus of enterprises. For enterprises, the problem of recycling and manufacturing is also quite cumbersome and complex, the government can intervene to solve the problem, with subsidies to promote the recycling of waste goods. Therefore, this study mainly from the two-channel supply chain, closed-loop supply chain and government intervention three angles, to car tire recovery as the research object, using the relevant theory of the Stackelberg game to study the differences between channels. By constructing the model without government subsidy and the model with government subsidy, this paper studies the role of government subsidies in the recycling process of waste tires, and analyzes the influence of government intervention measures on the game among manufacturers, retailers and consumers. The results show that the government subsidy will improve the overall profit level, increase the total demand for tires in the market, and reduce the environmental impact of used tires. By using the theory of dual-channel closed-loop supply chain and other relevant knowledge, the concrete application of closed-loop supply chain in waste material recovery will be promoted.