Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous fault diagnosis for aircraft engine using multi-label learning

Fault detection and isolation system is crucial for the safety and reliability of aircraft engine. Traditional techniques of data-driven fault diagnosis for aircraft engine mainly focus on single fault diagnosis problems by means of the single-label learning strategy. However, the simultaneous fault diagnosis problems cannot be ignored in reality. In this research, two data-driven approaches based on multi-label learning and support vector machine are proposed to address the simultaneous fault diagnosis for an aircraft engine. Given that the simultaneous fault data are more difficult to obtain than single fault data, the proposed approaches have the ability to diagnose both single fault and simultaneous fault for aircraft engine when the fault diagnosis system is trained using single fault data only. The experimental results show that the proposed approaches can diagnose the simultaneous fault for an aircraft engine with high accuracy requiring low computation burden and a small number of single fault training data. In addition, the supplementary experiment confirms that the diagnosis accuracy of the proposed methods can be further improved by adding a small amount of the simultaneous fault data into the training dataset.
Effects of Adipose-Derived Stem Cells and Their Conditioned Medium in a Human Ex Vivo Wound Model

Adult stem cells have been extensively investigated for tissue repair therapies. Adipose-derived stem cells (ASCs) were shown to improve wound healing by promoting re-epithelialization and vascularization as well as modulating the inflammatory immune response. In this study, we used ex vivo human skin cultured in a six-well plate with trans-well inserts as a model for superficial wounds. Standardized wounds were created and treated with allogeneic ASCs, ASCs conditioned medium (ASC-CM), or cell culture medium (DMEM) supplemented with fetal calf serum (FCS). Skin viability (XTT test), histology (hematoxylin and eosin, H and E), β-catenin expression as well as inflammatory mediators and growth factors were monitored over 12 days of skin culture. We observed only a moderate time-dependent decrease in skin metabolic activity while skin morphology was preserved, and re-epithelialization occurred at the wound edges. An increase in β-catenin expression was observed in the newly formed epithelia, especially in the samples treated with ASC-CM. In general, increased growth factors and inflammatory mediators, e.g., hepatocytes growth factor (HGF), platelet-derived growth factor subunit AA (PDGF-AA), IL-1α, IL-7, TNF-α, and IL-10, were observed over the incubation time. Interestingly, different expression profiles were observed for the different treatments. Samples treated with ASC-CM significantly increased the levels of inflammatory cytokines and PDGF-AA with respect to control, whereas the treatment with ASCs in DMEM with 10% FCS resulted in significantly increased levels of fibroblast growth factor-basic (FGF-basic) and moderate increases of immunomodulatory cytokines. These results confirm that the wound microenvironment can influence the type of mediators secreted by ASCs and the mode as to how they improve the wound healing process. Comparative investigations with pre-activated ASCs will elucidate further aspects of the wound healing mechanism and improve the protocols of ACS application.
Design idea of air conditioning for energy-saving textile enterprises

To meet the requirement of energy saving,some major energy-saving design concepts are summed as: selcetion of energy-saving and efficient cooling equipments,reasonable set of environmental standards and airflow in the workshop,strengthening of air heat and moisture treatment effect,use of thermal transfer technology and application of automatic control technology.In the paper are summarized major effective energy-saving methods,counter measures and effects in energy saving design concepts.
In Vivo Investigation of (2-Hydroxypropyl)-β-cyclodextrin-Based Formulation of Spironolactone in Aqueous Solution for Paediatric Use

Spironolactone (SPL), a potent anti-aldosterone steroidal drug used to treat several diseases in paediatric patients (e.g., hypertension, primary aldosteronism, Bartter’s syndrome, and congestive heart failure), is not available in child-friendly dosage forms, and spironolactone liquids have been reported to be unpalatable. Aiming to enhance SPL solubility in aqueous solution and overcome palatability, herein, the effects of (2-hydroxypropyl)-β-cyclodextrin (HP-β-CyD) were thoroughly investigated on solubilisation in water and on masking the unpleasant taste of SPL in vivo. Although the complexation of SPL with HP-β-CyD was demonstrated through phase solubility studies, Job’s plot, NMR and computational docking studies, our in vivo tests did not show significant effects on taste aversion. Our findings, on the one hand, suggest that the formation of an inclusion complex of SPL with HP-β-CyD itself is not necessarily a good indicator for an acceptable degree of palatability, whereas, on the other hand, they constitute the basis for investigating other cyclodextrin-based formulations of the poorly water-soluble steroidal drug, including solid dosage forms, such as spray-dried powders and orodispersible tablets.
Pharmacogenetics of Osteoporosis: A Pathway Analysis of the Genetic Influence on the Effects of Antiresorptive Drugs

Osteoporosis is a skeletal disorder defined by a decreased bone mineral density (BMD) and an increased susceptibility to fractures. Bisphosphonates and selective oestrogen receptor modulators (SERM) are among the most widely used drugs. They inhibit bone resorption by targeting the mevalonate and oestrogen pathways, respectively. The aim of this study was to determine if common variants of genes in those pathways influence drug responses. We studied 192 women treated with oral aminobisphosphonates and 51 with SERMs. Genotypes at 154 SNPs of the mevalonate pathway and 806 in the oestrogen pathway were analyzed. Several SNPs located in genes FDPS and FNTA were associated with the bisphosphonate-induced changes in hip bone mineral density (BMD), whereas polymorphisms of the PDSS1, CYP19A1, CYP1A1, and CYP1A2 genes were associated with SERM-induced changes in spine BMD. After multivariate analyses, genotypes combining genes FDPS and FNTA showed a stronger association with bisphosphonate response (r = 0.34; p = 0.00009), whereas the combination of CYP19A1 and PDSS1 genotypes was associated with the response to SERMs (r = 0.62, p = 0.0003). These results suggest that genotyping genes in these pathways may help predict the response to antiresorptive drugs and hence make personalized therapeutic choices.
Perceived Stress and Coping Behavior of Nurses Caring for Critical Patients with COVID-19 Outbreak in Taiwan: A Mixed-Methods Study

Severe pneumonia with novel pathogens, also called COVID-19, caused a pandemic in Taiwan as well as in the rest of the world in May 2021. Nurses are under great stress when caring for critically ill patients with COVID-19. This study aimed to explore the perceived stress and coping behaviors of nurses caring for critically ill patients with COVID-19 using a mixed-methods approach. We recruited 85 nurses from a special intensive care unit (ICU) of a medical center in Taiwan between May and June 2021. To gather data, we used a questionnaire on basic characteristics, the perceived stress scale (PSS-14), and the brief coping orientation to problems experienced inventory (B-COPE), then conducted a qualitative interview. The results showed that the average perceived stress level among nurses was 25.4 points, and most of them perceived moderate stress. The top three coping behaviors practiced by the nurses were active coping, planning, and acceptance. Nurses who received less perceived support from their friends or families and who had shorter working experience in nursing had significantly higher stress levels. The qualitative results revealed that the nurses’ perceived stress came from fear, worry, and the increased burden caused by caring for critical patients with COVID-19. Coping behaviors included rest, seeking support, and affirmative fighting. Based on these findings, it is suggested that the support nurses receive from their families is an important predictor of perceived stress. Therefore, it is suggested that nurses be provided with more support in dealing with stress caused by caring for critical patients with COVID-19 in special ICUs.
The Application of Technology, Pedagogy, Content, Knowledge (TPACK) During The COVID-19 Pandemic

This study aims to explore the application of TPACK during the Covid-19 pandemic in online learning. This research used narrative interviewing to analysis data. The participants were students and lecture who participated in online learning, with data collection interview with some lecture and student. The student’s participants in this study were willing to respond utilized Google Forms with open questions for collecting data. The research findings that students’ responses to the learning plan, learning content, learning strategies, class management, learning assessments, and supporting skills. It can be seen that student responses to the application of TPACK were based on online learning during the pandemic. The results showed three issues i.e. pedagogy knowledge, content knowledge and technical knowledge which were described in several indicators i.e. lesson plan, content material, teaching strategies, assessment, class management, and supporting skills. The mastery of TPACK itself was still not fully understood and conducted by lecturers in integrating technology-based material due to time constraints, lack of creativity in designing, and lecturers are more comfortable using conventional methods in delivering material, namely PowerPoint. This research implied that online learning changes not yet increased the lecturers’ creativity in designing teaching materials. Even though they obtained knowledge from attending workshops on teaching material design, lecturers still need assistance designing teaching materials according to the TPACK consept.
Deep Learning-Based Indoor Localization Using Multi-View BLE Signal

In this paper, we present a novel Deep Neural Network-based indoor localization method that estimates the position of a Bluetooth Low Energy (BLE) transmitter (tag) by using the received signals’ characteristics at multiple Anchor Points (APs). We use the received signal strength indicator (RSSI) value and the in-phase and quadrature-phase (IQ) components of the received BLE signals at a single time instance to simultaneously estimate the angle of arrival (AoA) at all APs. Through supervised learning on simulated data, various machine learning (ML) architectures are trained to perform AoA estimation using varying subsets of anchor points. In the final stage of the system, the estimated AoA values are fed to a positioning engine which uses the least squares (LS) algorithm to estimate the position of the tag. The proposed architectures are trained and rigorously tested on several simulated room scenarios and are shown to achieve a localization accuracy of 70 cm. Moreover, the proposed systems possess generalization capabilities by being robust to modifications in the room’s content or anchors’ configuration. Additionally, some of the proposed architectures have the ability to distribute the computational load over the APs.
Detection of surface defection of solder on flexible printed circuit

In order to detect the surface defect on the solder of a Flexible Printed Circuit(FPC),an in-specting technology based on image processing was presented.Firstly,all the defects on the FPC were classified into several defection sorts according to their defection characters.Then,the maximum en-tropy was used to locate the solder and extract the square and color characters.After estimating the effectness of the Grey Level Co-occurrence Matrix(GLCM)on the quantification for color and struc-ture characters,it was introduced to quantify and extract colorific and structural textures for solders. An analysis on experiments indicates that the defective solder is obviously different from the non-de-fective solder in several kinds of quantified charaters.On the basis of the result obove,the BP neural network was established and four kinds of characters were selected as the input of neural network.Af-ter all neural network weight parameters were adjusted to the optimization through sample training, the performance of the proposed defect detection algorithm was finally evaluated in an on-line testing. Test shows that 50inspecting targets cost 300ms,and the inspecting accuracy can reach 94.6%. The experi-mental result demonstrates that proposed method can detect accurately the solder defect with low false alarms, and the efficiency can satisfy the requirement of defect inspection in online and real time.
Effect of Crack Length on Stresses in a Plate with a Hole

The field of mechanics concerned with studying the propagation of cracks in materials is Fracture Mechanics. Technology systems are meant to withstand the loads to which they are likely to be exposed when in use. Material imperfections arising at the time of production or use of the material are, however, unavoidable and must therefore be taken into account. A stress intensity factor is a fracture parameter that defines the part failure. This paper study’s the effect of cracks on the stresses of rectangular plates having a hole in the center. The plate was subjected to tensile pressure at the top side while maintaining the bottom side fixed. The plate had four cracks distributed around the centered hole at 45o at each side. The effect of the length of the cracks on the resulted stresses and strains was investigated. Also, the effect of the position of the crack on the resulted stresses and strains was studied. Finite element models for the different plate cases were built using ANSYS software. The results showed that increasing the crack length resulted to increase the stresses and strains. The dimension of the plate width, height and thickness were 150 mm, 300 mm and 1 mm respectively, and the crack position was investigated for different crack lengths (5, 10, 15, 20, 25 mm) however the results were not steady as it looks that the crack lengths have changed the stress distribution over the plate.
Photodegradation of Azathioprine in the Presence of Sodium Thiosulfate

The effect of sodium thiosulfate (ST) on the photodegradation of azathioprine (AZA) was analyzed by UV-VIS spectroscopy, photoluminescence (PL), FTIR spectroscopy, Raman scattering, X-ray photoelectron (XPS) spectroscopy, thermogravimetry (TG) and mass spectrometry (MS). The PL studies highlighted that as the ST concentration increased from 25 wt. % to 75 wt. % in the AZA:ST mixture, the emission band of AZA gradual downshifted to 553, 542 and 530 nm. The photodegradation process of AZA:ST induced: (i) the emergence of a new band in the 320–400 nm range in the UV-VIS spectra of AZA and (ii) a change in the intensity ratio of the photoluminescence excitation (PLE) bands in the 280–335 and 335–430 nm spectral ranges. These changes suggest the emergence of new compounds during the photo-oxidation reaction of AZA with ST. The invoked photodegradation compounds were confirmed by studies of the Raman scattering, the FTIR spectroscopy and XPS spectroscopy through: (i) the downshift of the IR band of AZA from 1336 cm−1 to 1331 cm−1, attributed to N-C-N deformation in the purine ring; (ii) the change in the intensity ratio of the Raman lines peaking at 1305 cm−1 and 1330 cm−1 from 3.45 to 4.57, as the weight of ST in the AZA:ST mixture mass increased; and (iii) the emergence of a new band in the XPS O1s spectrum peaking at 531 eV, which was associated with the C=O bond. Through correlated studies of TG-MS, the main key fragments of ST-reacted AZA are reported.
Synthetic Design and Biological Evaluation of New p53-MDM2 Interaction Inhibitors Based on Imidazoline Core

The use of p53-MDM2 inhibitors is a prospective strategy in anti-cancer therapy for tumors expressing wild type p53 protein. In this study, we have applied a simple approach of two-step synthesis of imidazoline-based alkoxyaryl compounds, which are able to efficiently inhibit p53-MDM2 protein–protein interactions, promote accumulation of p53 and p53-inducible proteins in various cancer cell lines. Compounds 2l and 2k cause significant upregulation of p53 and p53-inducible proteins in five human cancer cell lines, one of which possesses overexpression of MDM2.
Study on strength of carburized gear for mining gearbox based on dynamics

The common failure forms of carburized gear in mining gearbox were researched,and the internal relations between failure mechanisms and gear strength were deeply analyzed.Aimed at the defects of traditional static analysis on accurately determining the worst engaging location and exerting inertial force,the dynamic meshing theory for carburized gears was studied and the corresponding kinetic equations were derived.Based on the transient dynamic analysis module of ANSYS,the simulation analysis of a pair of carburized spur gears in a mining gearbox was preformed.The comparative analysis of simulation results between dynamics and statics was carried out.The results show that dynamic analysis affords reliable assurance for accurately calculating strength and fatigue life of the carburized gear.
Applying Protein–Protein Interactions and Complex Networks to Identify Novel Genes in Retinitis Pigmentosa Pathogenesis

Retinitis Pigmentosa (RP) is a hereditary retinal disorder that causes the atrophy of photoreceptor rod cells. Since individual defective genes converge on the same disease, we hypothesized that all causal genes of RP belong in a complex network. To explore this hypothesis, we conducted a gene connection analysis using 161 genes attributed to RP, compiled from the Retinal Information Network, RetNet. We then examined the protein interaction network (PIN) of these genes. In line with our hypothesis, using STRING, we directly connected 149 genes out of the recognized 159 genes. To uncover the association between the PIN and the ten unrecalled genes, we developed an algorithm to pinpoint the best candidate genes to connect the uncalled genes to the PIN and identified ten such genes. We propose that mutations within these ten genes may also cause RP; this notion is supported by analyzing and categorizing the known causal genes based on cellular locations and related functions. The successful establishment of the PIN among all documented genes and the discovery of novel genes for RP strongly suggest an interconnectedness that causes the disease on the molecular level. In addition, our computational gene search protocol can help identify the genes and loci responsible for genetic diseases, not limited to RP.
Genome-Wide Analysis of the LRR-RLP Gene Family in a Wild Banana (Musa acuminata ssp. malaccensis) Uncovers Multiple Fusarium Wilt Resistance Gene Candidates

Banana is the most popular fruit in the world, with a relevant role in food security for more than 400 million people. However, fungal diseases cause substantial losses every year. A better understanding of the banana immune system should facilitate the development of new disease-resistant cultivars. In this study, we performed a genome-wide analysis of the leucine-rich repeat receptor-like protein (LRR-RLP) disease resistance gene family in a wild banana. We identified 78 LRR-RLP genes in the banana genome. Remarkably, seven MaLRR-RLPs formed a gene cluster in the distal part of chromosome 10, where resistance to Fusarium wilt caused by Foc race 1 has been previously mapped. Hence, we proposed these seven MaLRR-RLPs as resistance gene candidates (RGCs) for Fusarium wilt. We also identified seven other banana RGCs based on their close phylogenetic relationships with known LRR-RLP proteins. Moreover, phylogenetic analysis of the banana, rice, and Arabidopsis LRR-RLP families revealed five major phylogenetic clades shared by these plant species. Finally, transcriptomic analysis of the MaLRR-RLP gene family in plants treated with Foc race 1 or Foc TR4 showed the expression of several members of this family, and some of them were upregulated in response to these Foc races. Our study provides novel insights into the structure, distribution, evolution, and expression of the LRR-RLP gene family in bananas as well as valuable RGCs that will facilitate the identification of disease resistance genes for the genetic improvement of this crop.
The correlated expression of COX-2 and keratin 15 in radicular cysts

Background The expression of cyclooxygenase-2 (COX-2) and Keratin-15 (K15) in radicular cysts (RCs) is poorly understood. Identifying the expression of these two markers may modify the current treatment of RC. The objective of this study was to evaluate the expression of COX-2 and its relationship to K15 expression in the odontogenic epithelial cells of the RC. Material and Methods A total of 18 RCs were immunohistochemically analyzed for COX-2 and K15 expression. The cellular inflammatory reaction in the cyst wall was also assessed by measuring the percentage of inflammatory cells to the total number of cells. Results COX-2 expression in the odontogenic epithelium of RC was absent in 11.1 % (n=2), mild in 27.8 % (n=5), moderate in 22.2% (n=4) and strong in 38.9% (n=7). Meanwhile, K15 expression was absent in 27.8% (n=5), mild in 16.7% (n=3), moderate in 44.4% (n=8), and strong in 11.1% (n=2) of the cases. The inflammatory infiltrate was mild in 2 cases (11.1%), moderate in 6 cases (33.3%), and high in 10 cases (55.6%). Spearman’s correlation test revealed significant correlation (rho= .533; p= .023) between COX-2 and K15 expression in the odontogenic epithelium of RC. However, no correlation was noted between inflammation and expression of COX-2 (rho= 0.248, p=.321) or K15 (rho= -0.162, p= .520). Conclusions There is high and correlated expression of COX-2 and K15 in the odontogenic epithelium of RC. COX-2 could therefore be involved in epithelial cell differentiation of the cyst. Additionally, the expression of K15 in RC may be an indicator of epithelial cell differentiation. Key words:Cyclooxygenase, COX-2, Keratin-15, K15, Radicular cyst.
Teaching Descriptive Writing via Google Classroom Stream: Perception Among Year 6 Primary Students

Technology is very much pervasive in today's world and the educational systems are rapidly adjusting to technology to the extent that it contributed to the advancement of education. Information, communication, and technology (ICT) are significant now by seeing it being introduced into a wide range of schooling activities like Google Classroom. Google Classroom is a technology that connects educators and students, allowing them to communicate with one another through a virtual online class with the various feature. This study intends to investigate students' perception toward Google Classroom Stream, one of the GC's features, as well as the difficulties they faced when utilising it in a writing class. The research involved 35 participants consisting of Year 6 primary students in SJK(C) Shih Chung Cawangan, a Chinese Primary school located in Penang Island, Malaysia. This research study used a descriptive qualitative method and the data were collected through questionnaires and interviews. The questionnaire is made up of nine questions divided into two themes: the first is about students' acceptance while the second is regarding their performance about Google Classroom Stream. Fifteen students were interviewed to seek more information about their challenges using the platform. The findings of this study demonstrated that students have positive opinions of learning through Google Classroom Stream, owing to the availability of feedback and quick access to learning materials. The main issues that arose were the lack of internet access, as well as the varying displays on different devices and preferences on a private chat section.