Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioinformatic analysis of the role of solute carrier-glutamine transporters in breast cancer

Background Breast cancer (BC) is a highly heterogeneous disease. Solute carriers (SLCs) have been involved in the tumor progression of various cancer types. This study aimed to evaluate the role of these SLC-related glutamine transporters in the prognosis of BC patients by bioinformatics analysis. Methods This study examined the transcription and prognostic data for glutamine-related transporters in BC from Oncomine Database, which is currently the largest oncogene microarray database platform in the world. As well as Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier (K-M), and cBioPortal online resources. The Tumor Immune Estimation Resource (TIMER) and GEPIA were also used to examine the relationship between SLCs and immune cell infiltration. Results The expression levels of SLC1A5, SLC3A2, SLC7A5, SLC7A8, and SLC38A1 were higher in BC tissues than normal breast tissues, but the expression level of SLC6A14 was lower. The expression levels of SLC7A5, SLC7A8, SLC6A14, and SLC38A2 were related to a later clinical tumor stage. In the K-M analyses, The K-M curves revealed that patients with high SLC1A5 expression had a poor prognosis (OS HR =1.28, 95% CI: 1.06–1.54; P=0.01). The high expression of SLC3A2 was significantly correlated with a poor prognosis (DMFS HR =1.19, 95% CI: 1.02–1.39; P=0.027). Increased SLC7A5 mRNA levels and decreased SLC7A8 mRNA levels were significantly associated with a poor prognosis in terms of OS, RFS, DMFS and PPS. The high expression of SLC6A14 was significantly correlated with a poor prognosis (PPS HR =1.35, 95% CI: 1.07–1.7; P=0.011). The high expression of SLC38A1 was correlated with a better prognosis than low expression of SLC38A1 (RFS HR =0.84, 95% CI: 0.76–0.93; P=0.00077; DMFS HR =0.78, 95% CI: 0.67–0.91; P=0.0013). The infiltration of immune cells and their marker genes were associated with SLC1A5, SLC3A2, SLC7A5, SLC7A8, SLC6A14, SLC38A1, and SLC38A2 expression. SLC7A5, SLC7A8, SLC38A1, and SLC38A2 have the potential to regulate polarization in tumor-associated macrophages. Conclusions SLC7A5, SLC7A8, SLC38A1, and SLC38A2 may regulate the polarization of tumor-associated macrophages (TAMs). SLC1A5, SLC3A2, SLC7A5, and SLC6A14 may be promising biomarkers for the BC diagnosis and may represent potential therapeutic targets for these patients.
Isolation and Comprehensive in Silico Characterisation of a New 3-Hydroxy-3-Methylglutaryl-Coenzyme A Reductase 4 (HMGR4) Gene Promoter from Salvia miltiorrhiza: Comparative Analyses of Plant HMGR Promoters

Salvia miltiorrhiza synthesises tanshinones with multidirectional therapeutic effects. These compounds have a complex biosynthetic pathway, whose first rate limiting enzyme is 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR). In the present study, a new 1646 bp fragment of the S. miltiorrhiza HMGR4 gene consisting of a promoter, 5′ untranslated region and part of a coding sequence was isolated and characterised in silico using bioinformatics tools. The results indicate the presence of a TATA box, tandem repeat and pyrimidine-rich sequence, and the absence of CpG islands. The sequence was rich in motifs recognised by specific transcription factors sensitive mainly to light, salicylic acid, bacterial infection and auxins; it also demonstrated many binding sites for microRNAs. Moreover, our results suggest that HMGR4 expression is possibly regulated during flowering, embryogenesis, organogenesis and the circadian rhythm. The obtained data were verified by comparison with microarray co-expression results obtained for Arabidopsis thaliana. Alignment of the isolated HMGR4 sequence with other plant HMGRs indicated the presence of many common binding sites for transcription factors, including conserved ones. Our findings provide valuable information for understanding the mechanisms that direct transcription of the S. miltiorrhiza HMGR4 gene.
The Reading Ability Can Be Predicted by a Universal Verbal Working Memory Factor Across Different Writing Systems: Evidence from Reading Span Task

Most Chinese college students have an experience of learning English as second language for more than ten years. To explore whether the ability of reading Chinese script and English script was related to a universal working memory capacity, and whether the working memory capacity can predict a change in reading ability, we measured the general working memory span (via N-back task), verbal working memory span of Chinese and English (via reading span task), and reading comprehension ability of Chinese and English of our participants. We also collected the score of Chinese and English of their College Entrance Exam, which is tested at least half a year before now. Our results showed that both Chinese and English reading ability can be predicted by English reading span, which suggested a universal reading ability across different writing systems. The results also showed that reading span failed to predict the past reading score, and Chinese reading span failed to predict the reading comprehension of either Chinese and English, the possible reasons were discussed.
Load frequency control enhancement of islanded micro-grid considering high wind power penetration using superconducting magnetic energy storage and optimal controller

This article proposes a robust load frequency control using a new optimal proportional–integral–derivative controller–based genetic moth swarm algorithm for islanded microgrids considering high wind power penetration. In such microgrids, the replacement of conventional generator units with a large number of renewable energy sources reduces the system inertia, which in turn causes undesirable influence on microgrid frequency stability, leading to weakening of the microgrid. Furthermore, sudden load shedding, load restoring, and short circuits caused large frequency fluctuations which threaten the system security and could lead to complete blackouts as well as damages to the system equipment. In order to solve this challenge, this study proposes a new coordinated optimal load frequency control plus modified control signal to superconducting magnetic energy storage for compensating the microgrid frequency deviation (∆f). To prove the effectiveness of the proposed coordinated control strategy, an islanded microgrid was tested for the MATLAB/Simulink simulation. The physical constraints of the turbines such as generation rate constraints and speed governor dead band are considered in this study. The results confirmed the effectiveness and robustness of the proposed coordination performance against all scenarios of different load profiles, wind power fluctuation, and system uncertainties in microgrid integrated with high penetration of wind farms. Moreover, the results have been compared with both: the optimal load frequency control with/without the effect of conventional superconducting magnetic energy storage.
Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection

Objective: To develop a method for detection of bradycardia and ventricular tachycardia using the photoplethysmogram (PPG). Approach: The detector is based on a dual-branch convolutional neural network (CNN), whose input is the scalograms of the continuous wavelet transform computed in 5-s segments. Training and validation of the CNN is accomplished using simulated PPG signals generated from RR interval series extracted from public ECG databases. Manually annotated real PPG signals from the PhysioNet/CinC 2015 Challenge Database are used for performance evaluation. The performance is compared to that of a pulse-based reference detector. Results: The sensitivity/specificity were found to be 98.1%/97.9 and 76.6%/96.8% for the CNN-based detector, respectively, whereas the corresponding results for the pulse-based detector were 94.7%/99.8 and 67.1%/93.8%, respectively. Significance: The proposed detector may be useful for continuous, long-term monitoring of bradycardia and tachycardia using wearable devices, e.g., wrist-worn devices, especially in situations where sensitivity is favored over specificity. The study demonstrates that simulated PPG signals are suitable for training and validation of a CNN.
Kidney Stone Prediction Using Neural Network Classifier

kidney stone disorder is a frequent hassle in the World today. The majority of kidney stones is tiny and bypass on their own. Overwork, which suppresses human antibodies, excessive sodium intake, and worse exterior surroundings stipulations such as bloodless and dampness too are effortless reasons of kidney illnesses nowadays. Using bodily inspection or operators to acquire findings for large datasets is tough. In CT scans there is a lot of noise, which will increase the mistakes. Deep gaining knowledge of strategies like neural networks has proven to be enormously really helpful in this field. As a result, this challenge employs the Convolutional Neural Network (CNN). The facets are extracted the usage of GLCM and then classified the usage of CNN. This find out about makes use of the Fuzzy C-Mean clustering approach to section computed tomography pictures in order to pick out the kidney stones early on.
Occupational Health Sufferings of Child Waste Workers in South Asia: A Scoping Review

Background: Child labor remains a health hazard, affecting the mental, physical, and emotional well-being of children. Children engage in waste management through various channels while constantly working to create a healthier and cleaner environment and exposing themselves to numerous health risks. Thus, this scoping review aims to explore the occupational injuries, health hazards, and sufferings of child waste workers in South Asia. Methods: Following the PRISMA guidelines, a scoping review of available relevant scientific literature was completed to comprehensively analyze the extent of child waste workers’ health suffering. Online databases PubMed, SCOPUS, and Google Scholar were searched for predefined criteria. Collected references were screened with Rayyan web tools and Endnote. Based on study inclusion criteria, a thematic synthesis was performed on the findings of 12 articles. Results: This study’s findings provided deep insights into the most prevalent occupational health sufferings among child waste workers, as depicted in the available literature. Prevalence of injuries like cuts and wounds was found predominant. These injuries are caused by the collection, transportation, dumping, and recycling of waste. Respiratory, musculoskeletal, and skin diseases are more prevalent among child waste worker children than in control groups of the same socioeconomic backgrounds. A higher chance of genetic or neuro-degenerative disorder and DNA mutation indicates a long-term effect on the children working in the waste management sector. Psychological sufferings were the least explored, although very common among child laborers. MPD (Minor Psychiatric Disorder) was very high among waste workers. Regarding healthcare-seeking behavior, traditional methods are preferable rather than formal health facilities. More research is required in this area due to a lack of evidence on the health problems of child waste workers. Conclusions: Occupational hazards were myriad among child waste workers. Though many children are involved in waste management, they are typically excluded from mainstream child protection and support systems, making them more exposed to occupational harassment and injury. Policymakers should design specific programs for these vulnerable groups considering the issues below, i.e., provide protective equipment such as facemasks, gloves, footwear, and rag sorting tools to safeguard them from physical damage and illness, ensure access to health care, to school, and provide basic nutrients to them. Furthermore, the authorities should think of alternative income generating programs for these groups of children.
Detection and isolation of false data injection attack for smart grids via unknown input observers

The emergence of cyber-physical attacks brings a key challenge to the existing system integrity protection schemes (SIPSs) of smart grids. As one of typical cyber-physical attacks, false data injection attacks (FDIAs) can bypass the existing Kalman filter-based -detector detection techniques in SIPSs. To improve the detection performance against the FDIAs in SIPSs, this study proposes an unknown input observer (UIO)-based detection and isolation method. Taking the stealthy characteristics of FDIAs into account, this study presents a set of UIOs to detect the FDIA based on the internally physical dynamics. Furthermore, a UIO-based detection and isolation algorithm against the FDIAs is proposed based on the feature of residuals generated by UIOs. To detect the cyber attacks quickly and avoid missing detection, an adaptive threshold is designed to replace the precomputed threshold by taking the model linearised error and disturbance into account. Finally, comprehensive simulation results on the proposed algorithm are carried out, and the effectiveness of improving the detection performance in SIPSs is verified.
Construction of Robot Computer Image Segmentation Model Based on Partial Differential Equation

The application of partial differential equation in robot computer image smoothing and image segmentation based on curve evolution is studied to achieve the breakthrough and innovation of classical methods. First of all, the image is interpolated and enlarged, usually with double primary interpolation and double secondary interpolation. The robot computer image obtained by interpolation has a better effect on the smooth part of the image, but the edge becomes blurred. Then, the model is used to enhance the amplified image and remove the noise introduced during interpolation. In the process of PDE image segmentation, using the level set method, natural continuation cannot guarantee that the embedded function is always a signed distance function in the evolution process. The results show that compared with the classical fourth-order model, this model can well retain the details of the image, smooth bevels, and edges of the image. The proposed new model is better than the second-order model and the classical fourth-order model both in PSNR value and MAE value and in visual effect. Secondly, the model based on piecewise smooth Mumford-Shah not only expresses the original image better but also solves the problem of gradual image segmentation with gray value. Therefore, the robot computer image segmentation model based on partial differential equation can segment the image better.
Constitutive Relations of Anisotropic Polycrystals: Self-Consistent Estimates

In this paper, the elastic constitutive relation of polycrystals contains the effect of the mesostucture coefficients. We consider a general case and derive the average elastic constitutive relation pertaining to polycrystals of cubic crystals with any symmetry of crystalline orientation in their statistical distribution. Following Budiansky and Wu, we used self-consistent estimates of eigenstrain to obtain the effective elastic constitutive relation of polycrystals in an explicit form. For the Voigt assumption and the Reuss assumption, the effective elastic constitutive relation of polycrystals on cubic crystals contains the the mesostructure coefficients up to linear terms. In general, the linear term expression works well for materials such as aluminum, the single crystal of which has weak anisotropy. However the same expression (which allows the anisotropic part of the effective elastic constitutive relation to depend only linearly on the mesostructure coefficients) does not suffice for materials such as copper, in which the single crystal is strongly anisotropic. Per the Taylor theorem, we expand the expression based on the self-consistent estimates with respect to the mesostructure coefficients up to quadratic terms for anisotropic polycrystals of cubic crystals. While our numerical data are very close to those of Morris, our expression is much simpler.
Combination of Building Information Modeling and Infrared Point Cloud for Nondestructive Evaluation

Infrared thermography is a nondestructive evaluation technique that has emerged as a practical approach for energy audit, damage detection, and structural monitoring applications. Advancements in unmanned aerial vehicle technologies have increased the capabilities of infrared thermography and expedited the inspection process. Recently, applications of infrared imaging and Structure-from-Motion have been developed and demonstrated that it is possible to reconstruct point clouds from scalar fields containing emissivity and temperature values retrieved from the infrared images. This paper develops and quantifies the accuracy of a novel cloud-to-model tool that converts the emissivity scalar fields extracted from the point cloud into an analysis layer that can be imported into a building information modeling environment. The model developed allows for an intuitive interpretation of the collected data through the association between a single building component and a piece of the point cloud that describes its properties in the infrared range. In this paper, the accuracy of the proposed infrared-based approach is compared with the one of a point cloud generated using high-resolution digital images.
Identification of Exported Plasmodium falciparum Proteins That Bind to the Erythrocyte Cytoskeleton

Plasmodium proteins are exported to the erythrocyte cytoplasm to create an environment that supports parasite replication. Although hundreds of proteins are predicted to be exported through Plasmodium export element (PEXEL)-dependent and -independent mechanisms, the functions of exported proteins are largely uncharacterized. In this study, we used a biochemical screening approach to identify putative exported P. falciparum proteins that bound to inside-out vesicles prepared from erythrocytes. Out of 69 P. falciparum PEXEL-motif proteins tested, 18 bound to inside-out vesicles (IOVs) in two or more independent assays. Using co-affinity purifications followed by mass spectrometry, pairwise co-purification experiments, and the split-luciferase assay, we identified 31 putative protein–protein interactions between erythrocyte cytoskeletal proteins and predicted exported P. falciparum proteins. We further showed that PF3D7_1401600 binds to the spectrin-binding domain of erythrocyte ankyrin via its MESA erythrocyte cytoskeleton binding (MEC) motif and to the N-terminal domains of ankyrin and 4.1R through a fragment that required an intact Plasmodium helical interspersed sub-telomeric (PHIST) domain. Introduction of PF3D7_1401600 into erythrocyte ghosts increased retention in the microsphiltration assay, consistent with previous data that reported a reduction of rigidity in red blood cells infected with PF3D7_1401600-deficient parasites.
Modified dual buck–boost AC/DC converter with self‐balanced DC output voltages

With wide applications of DC loads and renewable energy generation sources, the DC micro-grid becomes more and more attractive, especially regarding active AC/DC converters. Recently, a high-efficiency buck-boost AC/DC converter with three terminal outputs has been presented for DC micro-grid. However, the main drawback of this converter is that the output voltages become unbalanced in the case of unequal DC loads, which causes a challenge in practical applications. In this study, a modified buck-boost AC/DC converter with self-balanced DC output voltages is proposed. Equivalent circuits are used to analyse the operating principle of the proposed converter. As an important part of the proposed converter, the coupled inductor is designed, while the design procedure is described in detail. The dead-beat control method is adopted to shape the waveform of the coupled inductor current. A 220 V/50 Hz/1.5 kW prototype is developed, and detailed experiments are carried out to corroborate the validity of the proposed converter.
HSPA8 Single-Nucleotide Polymorphism Is Associated with Serum HSC70 Concentration and Carotid Artery Atherosclerosis in Nonalcoholic Fatty Liver Disease

There is an association between nonalcoholic fatty liver disease (NAFLD) and atherosclerosis, but the genetic risk of atherosclerosis in NAFLD remains unclear. Here, a single-nucleotide polymorphism (SNP) of the heat shock 70 kDa protein 8 (HSPA8) gene was analyzed in 123 NAFLD patients who had been diagnosed using a liver biopsy, and the NAFLD phenotype including the maximum intima–media thickness (Max-IMT) of the carotid artery was investigated. Patients with the minor allele (A/G or G/G) of rs2236659 showed a lower serum heat shock cognate 71 kDa protein concentration than those with the major A/A allele. Compared with the patients with the major allele, those with the minor allele showed a higher prevalence of hypertension and higher Max-IMT in men. No significant associations between the HSPA8 genotype and hepatic pathological findings were identified. In decision-tree analysis, age, sex, liver fibrosis, and HSPA8 genotype were individually associated with severe carotid artery atherosclerosis (Max-IMT ≥ 1.5 mm). Noncirrhotic men aged ≥ 65 years were most significantly affected by the minor allele of HSPA8. To predict the risk of atherosclerosis and cardiovascular disease, HSPA8 SNP genotyping might be useful, particularly for older male NAFLD patients.
Immediate Effects of Extracorporeal Shock Wave Therapy in Fascial Fibroblasts: An In Vitro Study

Extracorporeal shock waves (ESWs) are used in the treatment of soft tissue injuries, but their role in the treatment of myofascial pain has not yet been demonstrated. The aim of this study was to investigate changes in cell biology of fibroblasts derived from deep/muscular fascia following treatment with ESWs. Primary fascial fibroblasts were collected from small samples of human fascia lata of the thigh of three volunteer patients (two men, one woman) during orthopedic surgery, and put in culture. These cells were exposed to 100 impulses of 0.05 mJ/mm2 with a frequency of 2.5 Hz, using 3D-printed support. This study demonstrated for the first time that ESWs can lead to in vitro production of hyaluronan-rich vesicles immediately after the treatment. At 1, 4, and 24 h after treatment, Alcian blue and Toluidine blue staining; immunocytochemistry to detect hyaluronic acid binding protein (HABP), collagen I, and collagen III; and transmission electron microscopy demonstrated that these vesicles are rich in hyaluronan and collagen I and III. The diameter of these vesicles was assessed, highlighting a small size at 1 h after ESW treatment, whereas at 4 and 24 h, they had an increase in the size. Particularly evident was the release of hyaluronan-rich vesicles, collagen-I, and collagen-III starting at 1 h, with an increase at 4 h and maintenance by 24 h. These in vitro data indicate that fascial cells respond to ESW treatment by regulating and remodeling the formation of extracellular matrix.