Miracle-dz/UniFAR-FTUs huggingface dataset:
Significance of N6-Methyladenosine RNA Methylation Regulators in Immune Infiltrates of Ovarian Cancer

N6-methyladenosine (m6A) RNA methylation regulators play an important role in the occurrence and development of tumors. Here, we aimed to identify the potential roles of m6A RNA methylation regulators in immune infiltrates of ovarian cancer. We obtained two distinct m6A patterns (m6Acluster.A and m6Acluster.B) based on the expression levels of all 21 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) database using a consensus clustering algorithm. Differential analysis of m6Acluster.A and m6Acluster.B identified 196 m6A-related genes. We further validated the m6A regulation mechanism based on the 196 m6A-related genes using another consensus clustering algorithm. Considering individual differences, principal component analysis algorithms were used to calculate an m6A score for each sample in order to quantify the m6A patterns. A low m6A score was associated with immune activation and enhanced response to immune checkpoint inhibitors, whereas a high m6A score was associated with tumor progression. Finally, we successfully verified the correlation between m6A regulators and immune microenvironment in OC using our microarray analysis data. In summary, m6A regulators play non-negligible roles in immune infiltrates of ovarian cancer. Our investigation of m6A patterns may help to guide future immunotherapy strategies for advanced ovarian cancer.
Population Genetics of the Black Citrus Aphid Aphis aurantii (Hemiptera, Aphididae) in China

The black citrus aphid, Aphis aurantii Boyer de Fonscolombe, 1841, is one of the most destructive pests in commercial tea plantations and gardens in China. In this study, we investigated the population genetic structure of A. aurantii based on the concatenated sequences of two mitochondrial genes, cytochrome c oxidase I (cox1) and cytochrome b (cytb). A total of 166 haplotypes were identified from 177 individuals collected at 11 locations in China. The whole Chinese A. aurantii population showed a low nucleotide diversity (0.00968) and a high population diversity (haplotype diversity; 0.9991). The haplotypes of the 11 local populations were widely distributed in the neighbor-joining phylogenetic tree and haplotype network diagram, whereas no apparent lineages were detected. Gene flow analysis showed gene exchanges among local populations. The pairwise Fst values revealed a certain amount of genetic difference among local populations. Analysis of molecular variance (AMOVA) reflected genetic differences both within and among populations. The isolation by distance (IBD) analysis revealed a high positive correlation between the geographic distance and genetic distance of the different populations. Neutral test and mismatch distribution suggested that A. aurantii may have experienced recent population expansion events.
Effect of the Hypoxia Inducible Factor on Sorafenib Resistance of Hepatocellular Carcinoma

Sorafenib a multi-target tyrosine kinase inhibitor, is the first-line drug for treating advanced hepatocellular carcinoma (HCC). Mechanistically, it suppresses tumor angiogenesis, cell proliferation and promotes apoptosis. Although sorafenib effectively prolongs median survival rates of patients with advanced HCC, its efficacy is limited by drug resistance in some patients. In HCC, this resistance is attributed to multiple complex mechanisms. Previous clinical data has shown that HIFs expression is a predictor of poor prognosis, with further evidence demonstrating that a combination of sorafenib and HIFs-targeted therapy or HIFs inhibitors can overcome HCC sorafenib resistance. Here, we describe the molecular mechanism underlying sorafenib resistance in HCC patients, and highlight the impact of hypoxia microenvironment on sorafenib resistance.
Nanoparticle-Assisted Diagnosis and Treatment for Abdominal Aortic Aneurysm

An abdominal aortic aneurysm (AAA) is a localized dilatation of the aorta related to the regional weakening of the wall structure, resulting in substantial morbidity and mortality with the aortic ruptures as complications. Ruptured AAA is a dramatic catastrophe, and aortic emergencies constitute one of the leading causes of acute death in older adults. AAA management has been centered on surgical repair of larger aneurysms to mitigate the risks of rupture, and curative early diagnosis and effective pharmacological treatments for this condition are still lacking. Nanoscience provided a possibility of more targeted imaging and drug delivery system. Multifunctional nanoparticles (NPs) may be modified with ligands or biomembranes to target agents' delivery to the lesion site, thus reducing systemic toxicity. Furthermore, NPs can improve drug solubility, circulation time, bioavailability, and efficacy after systemic administration. The varied judiciously engineered nano-biomaterials can exist stably in the blood vessels for a long time without being taken up by cells. Here, in this review, we focused on the NP application in the imaging and treatment of AAA. We hope to make an overview of NP-assisted diagnoses and therapy in AAA and discussed the potential of NP-assisted treatment.
The Differential Growth Inhibition of Phytophthora spp. Caused by the Rare Sugar Tagatose Is Associated With Species-Specific Metabolic and Transcriptional Changes

Tagatose is a rare sugar with no negative impacts on human health and selective inhibitory effects on plant-associated microorganisms. Tagatose inhibited mycelial growth and negatively affected mitochondrial processes in Phytophthora infestans, but not in Phytophthora cinnamomi. The aim of this study was to elucidate metabolic changes and transcriptional reprogramming activated by P. infestans and P. cinnamomi in response to tagatose, in order to clarify the differential inhibitory mechanisms of tagatose and the species-specific reactions to this rare sugar. Phytophthora infestans and P. cinnamomi activated distinct metabolic and transcriptional changes in response to the rare sugar. Tagatose negatively affected mycelial growth, sugar content and amino acid content in P. infestans with a severe transcriptional reprogramming that included the downregulation of genes involved in transport, sugar metabolism, signal transduction, and growth-related process. Conversely, tagatose incubation upregulated genes related to transport, energy metabolism, sugar metabolism and oxidative stress in P. cinnamomi with no negative effects on mycelial growth, sugar content and amino acid content. Differential inhibitory effects of tagatose on Phytophthora spp. were associated with an attempted reaction of P. infestans, which was not sufficient to attenuate the negative impacts of the rare sugar and with an efficient response of P. cinnamomi with the reprogramming of multiple metabolic processes, such as genes related to glucose transport, pentose metabolism, tricarboxylic acid cycle, reactive oxygen species detoxification, mitochondrial and alternative respiration processes. Knowledge on the differential response of Phytophthora spp. to tagatose represent a step forward in the understanding functional roles of rare sugars.
Examining Scale Dependent Environmental Effects on American Lobster (Homarus americanus) Spatial Distribution in a Changing Gulf of Maine

The Gulf of Maine (GOM) is a highly complex environment and previous studies have suggested the need to account for spatial nonstationarity in species distribution models (SDMs) for the American lobster (Homarus americanus). To explore impacts of spatial nonstationarity on species distribution, we compared models with the following three assumptions : (1) large-scale and stationary relationships between species distributions and environmental variables; (2) meso-scale models where estimated relationships differ between eastern and western GOM, and (3) finer-scale models where estimated relationships vary across eastern, central, and western regions of the GOM. The spatial scales used in these models were largely determined by the GOM coastal currents. Lobster data were sourced from the Maine-New Hampshire Inshore Bottom Trawl Survey from years 2000–2019. We considered spatial and environmental variables including latitude and longitude, bottom temperature, bottom salinity, distance from shore, and sediment grain size in the study. We forecasted distributions for the period 2028–2055 using each of these models under the Representative Concentration Pathway (RCP) 8.5 “business as usual” climate warming scenario. We found that the model with the third assumption (i.e., finest scale) performed best. This suggests that accounting for spatial nonstationarity in the GOM leads to improved distribution estimates. Large-scale models revealed a tendency to estimate global relationships that better represented a specific location within the study area, rather than estimating relationships appropriate across all spatial areas. Forecasted distributions revealed that the largest scale models tended to comparatively overestimate most season × sex × size group lobster abundances in western GOM, underestimate in the western portion of central GOM, and overestimate in the eastern portion of central GOM, with slightly less consistent and patchy trends amongst groups in eastern GOM. The differences between model estimates were greatest between the largest and finest scale models, suggesting that fine-scale models may be useful for capturing effects of unique dependencies that may operate at localized scales. We demonstrate how estimates of season-, sex-, and size- specific American lobster spatial distribution would vary based on the spatial scale assumption of nonstationarity in the GOM. This information may help develop appropriate local adaptation measures in a region that is susceptible to climate change.
CRISPR/Cas9-Mediated Whole Genomic Wide Knockout Screening Identifies Specific Genes Associated With PM2.5-Induced Mineral Absorption in Liver Toxicity

PM2.5, also known as fine particles, refers to particulate matter with a dynamic diameter of ≦2.5 μm in air pollutants, that carries metals (Zn, Co, Cd) which can pass through the alveolar epithelium and enter the circulatory system and tissues. PM2.5 can cause serious health problems, such as non-alcoholic fatty liver and hepatocellular carcinoma, although the underlying mechanisms of its toxic effect are poorly understood. Here, we exposed L02 cells to PM2.5 and performed a pooled genome−wide clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) to assess loss of function and identify new potential PM2.5targets. Enrichr and KEGG pathway analyses were performed to identify candidate genes associated with PM2.5 toxicity. Results revealed that four key genes, namely ATPase Na+/K+ transporting subunit alpha 2 (ATP1A2), metallothionein 1M (MT1M), solute carrier family 6 members 19 (SLC6A19) and transient receptor potential cation channel subfamily V member 6 (TRPV6) were associated with PM2.5 toxicity, mainly in regulating the mineral absorption pathway. Downregulating these genes increased cell viability and attenuated apoptosis in cells exposed to PM2.5. Conversely, overexpressing TRPV6 exacerbated cell apoptosis caused by PM2.5, while a reactive oxygen species (ROS) inhibitor N-acetyl-l-cysteine (NAC) alleviated PM2.5-induced apoptosis. In conclusion, ATP1A2, MT1M, SLC6A19 and TRPV6 may be contributing to absorption of metals in PM2.5 thereby inducing apoptosis mediated by ROS. Therefore, they hold potential as therapeutic targets for PM2.5-related diseases.
A Novel circRNA–miRNA–mRNA Hub Regulatory Network in Lung Adenocarcinoma

The growing evidence suggests that circular RNAs (circRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of circRNAs in lung adenocarcinoma (LUAD) remains unclear. This study clarified the potentially regulatory network and functional mechanism of circRNAs in LUAD. The expression data of circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from the Gene Expression Omnibus (GEO) database. Relying on GSE101586, GSE101684, and GSE112214, we identified differentially expressed circRNAs (DEcircRNAs). Depending on GSE135918 and GSE32863, we screened out differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs), respectively. Then, a novel competing endogenous RNA (ceRNA) regulatory network related to LUAD was constructed. We also revealed biological processes and signal pathways regulated by these DEcircRNAs. Based on gene expression data and survival information of LUAD patients in The Cancer Genome Atlas (TCGA) and GEO, we implemented survival analysis to select DEmRNAs related to prognosis and build a novel circRNA–miRNA–mRNA hub regulatory network. Meanwhile, quantitative real-time PCR (qRT-PCR) was utilized to validate DEcircRNAs in the ceRNA hub regulatory network. As a result, a total of 8 DEcircRNAs, 19 DEmiRNAs, and 85 DEmRNAs were identified. The novel ceRNA regulatory network included 5 circRNAs, 8 miRNAs, and 22 mRNAs. The final ceRNA hub regulatory network contained two circRNAs, two miRNAs, and two mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the five DEcircRNAs may affect LUAD onset and progression through Wnt signaling pathway and Hippo signaling pathway. All in all, this study revealed the regulatory network and functional mechanism of circRNA-related ceRNAs in LUAD.
Socioeconomic Correlates of Anti-Science Attitudes in the US

Successful responses to societal challenges require sustained behavioral change. However, as responses to the COVID-19 pandemic in the US showed, political partisanship and mistrust of science can reduce public willingness to adopt recommended behaviors such as wearing a mask or receiving a vaccination. To better understand this phenomenon, we explored attitudes toward science using social media posts (tweets) that were linked to counties in the US through their locations. The data allowed us to study how attitudes towards science relate to the socioeconomic characteristics of communities in places from which people tweet. Our analysis revealed three types of communities with distinct behaviors: those in large metro centers, smaller urban places, and rural areas. While partisanship and race are strongly associated with the share of anti-science users across all communities, income was negatively and positively associated with anti-science attitudes in suburban and rural areas, respectively. We observed that emotions in tweets, specifically negative high arousal emotions, are expressed among suburban and rural communities by many anti-science users, but not in communities in large urban places. These trends were not apparent when pooled across all counties. In addition, we found that anti-science attitudes expressed five years earlier were significantly associated with lower COVID-19 vaccination rates. Our analysis demonstrates the feasibility of using spatially resolved social media data to monitor public attitudes on issues of social importance.
A Mobile Robotic 3-D Measurement Method Based on Point Clouds Alignment for Large-Scale Complex Surfaces

Large-scale complex surfaces are the core components of large aircraft, ships, and wind turbine generators. High-accuracy manufacturing of the components is very crucial for its performance. Automated and high-accuracy large-scale 3-D measurement is an effective means for the manufacturing accuracy control of these components. This article proposes an automated mobile robotic profile measurement method for large-scale complex surfaces, and it also proposes a high-accuracy point clouds alignment algorithm to improve the measurement accuracy. A fringe projection scanner, integrated on the end of a mobile robot, is utilized to scan the surface and obtain the local scanning point clouds. The local scanning point clouds’ coarse alignment is implemented using the robot’s joint data and the laser sensor’s positioning data. After that, a fine alignment algorithm combining the fruit fly optimization algorithm (FOA) with the improved iterative closest point (IICP) algorithm is proposed for point clouds’ fine alignment. Practical measurement was performed on a sectional wind turbine blade, and a broad region of $4.6 \text { m} \times 2.6$ m was measured. An accuracy evaluation method based on point-to-plane distance was adopted to evaluate the measurement error. The result that the mean distance error is less than 0.4 mm shows the proposed mobile robotic measurement system and the aligning method are of high accuracy.
Linear Promises: Towards Safer Concurrent Programming (Artifact)

In this paper, we introduce a new type system based on linear typing, and show how it can be incorporated in a concurrent programming language to track ownership of promises. By tracking write operations on each promise, the language is able to guarantee exactly one write operation is ever performed on any given promise. This language thus precludes a number of common bugs found in promise-based programs, such as failing to write to a promise and writing to the same promise multiple times. We also present an implementation of the language, complete with an efficient type checking algorithm and high-level programming constructs. This language serves as a safer platform for writing high-level concurrent code.
Thermography of Photovoltaic Panels and Defect Detection Under Outdoor Environmental Conditions

This paper investigates the possibility of detecting defects in photovoltaic (PV) cell and panels under harsh outdoor environmental conditions with the help of synchronized thermography (ST). Infrared (IR) images are obtained under changing solar radiation levels, moderate wind speeds and ambient temperatures below zero degree Celsius with the help of a portable IR-camera. We demonstrate that IR-images obtained under harsh environmental conditions provide the same information as IR-images recorded under common environmental conditions. We elaborate the differences in parameters such as measurement time and region-of-interest (ROI) which need to be adjusted when carrying out measurements under harsh conditions. Our technique allows maintenance staff to carry out measurements, both, during summertime and wintertime, on the site of a PV power plant to identify PV panels with potential defects.
Volumetric properties of aqueous sodium chloride solutions from 0/sup 0/ to 500/sup 0/C at pressures up to 2000 bars based on a regression of available data in the literature

The volumetric properties of aqueous sodium chloride solutions from 0/sup 0/ to 500/sup 0/C at pressures up to 2000 bars for concentrations ranging from infinite dilution to as high as 8.0 molal were obtained by a computer regression of the available experimental data from the literature. The regression was done using (1) the simplest forms of equations capable of describing the experimental data, (2) unsmoothed data where possible, and (3) a least-squares regression technique in which the individual data points were weighted with respect to their relative uncertainty. By following this procedure, a set of internally consistent data was generated. The results are presented in 27 tables of density data at various concentrations, temperatures, and pressures. Two tables of empirical constants capable of generating the tables of density values as well as interpolating the tabulated values are also given.
Exploiting Vitis Framework for Accelerating Sobel Algorithm

Edge detection is one of the most common operations needed in the image processing domain. In this work, alternative implementations of the Sobel algorithm are tested on a ZCU102 Xilinx embedded platform, demonstrating how different optimization techniques can be conveniently configured in Xilinx Vitis environment. We exploit (a) Xilinx Runtime library (XRT) that allows the reprogramming of the reconfigurable logic at real time and (b) the various high-level attributes offered by the OpenCL API for efficient resource allocation in the state-of-the-art Xilinx Ultrascale Multi-Processor System-on-Chips (MPSoC). Specifically, different implementations of the Sobel algorithm (varying the data transfer models and data packing modes) are demonstrated and analyzed. Our experimental results shows that starting from a CPU implementation with 656 ms latency, the frame processing time is reduced to a range between 17 ms and 22 ms depending on the allocated resources, leading to a solution that is up to 38 times faster.
Hyperspectral Images Unmixing Based on Abundance Constrained Multi-Layer KNMF

Due to the low spatial resolution of the sensors, the hyperspectral images contain mixed pixels. The purpose of hyperspectral unmixing is to decompose the mixed pixels into a series of endmembers and abundance fractions. In order to improve the performance of the nonlinear unmixing algorithm for hyperspectral images, a nonlinear unmixing method, i.e., abundance constrained multi-layer kernel non-negative matrix factorization (AC-MLKNMF), is presented. Firstly, MLKNMF is presented to iteratively decompose the mixed pixels into a multi-layer structure, and then AC-MLKNMF is presented based on MLKNMF by adding the sparseness constraint and total variation regularization to the abundance to characterize the sparseness and the piecewise smooth structure of the abundance maps according to the spatial distribution characteristics of the actual ground-objects. Experimental results on synthetic and real datasets show that the proposed AC-MLKNMF can improve the hyperspectral unmixing accuracy compared with single-layer KNMF, and it is also superior to multi-layer non-negative matrix factorization, KNMF without pure pixels, kernel sparse NMF, MLKNMF.
Privacy-Preserving Matrix Factorization for Cross-Domain Recommendation

Cross-domain recommender systems are known to provide solutions to the cold start and data sparsity problems in recommender systems. This can be achieved by leveraging sufficient ratings and users’ profiles in one domain to enhance accurate recommendations in another domain. However, domains with sufficient ratings are not willing to share their users’ ratings with other recommender systems or domains due to users’ privacy and legal concern. Hence this shows a need for a privacy-preserving mechanism that encourages secure knowledge transfer between different domains. This study proposes a privacy-preserving cross-domain recommender system based on matrix factorization. Specifically, the study formally described the privacy requirements of a cross-domain recommender system, which are different from a single domain recommender system. It designs a new framework for a privacy-preserving cross-domain recommender system and then utilized the somewhat homomorphic encryption (SWHE) scheme to ensure users’ privacy. The SWHE scheme was used to encrypt users’ ratings in different domains, shared latent factor approach was implemented between the domains and extracted knowledge was securely transferred from the source domain to the target domain. We prove that users’ privacy is secured throughout the stages involved in the proposed protocol. Experiments on both synthetic and real datasets demonstrate the efficiency of our protocol.
Localized Surface Strain Measurement for Load Detection Using Diamond like Carbon Coating on a Linear Guide

Linear Guides are highly loaded standard machine parts. Being able to measure the load on them is interesting for predictive maintenance and process optimization. One possibility of doing this is measuring the resulting strain at different parts. In this study localized strain measurement with a large amount of sensors on the outer surface of the linear guide was enabled by a Diamond like Carbon (DLC) layer, whereas the actual sensor areas were established by a novel versatile contacting device. Measured strain distribution on the front and side faces is presented and compared with Finite-Element-Method (FEM) based predictions. Suitability of sensor locations for load measurement is discussed, and a method for retrieving the load from the sensor data based on a load distribution model is nresented.