Miracle-dz/UniFAR-FTUs huggingface dataset:
Lysophosphatidic Acid Receptor 6 (LPAR6) Is a Potential Biomarker Associated with Lung Adenocarcinoma

LPAR6 is the most recently determined G-protein-coupled receptor of the lysophosphatidic acid receptor, and very few of studies have demonstrated the performance of LPAR6 in cancers. Moreover, the relationship of LPAR6 to the potential of prognosis and tumor infiltration immune cells in different types of cancer are still unclarified. In this study, the mRNA expression of LPAR6 and its clinical characteristics were evaluated on various databases. The association between LPAR6 and immune infiltrates of various types of cancer were investigated via TIMER. Immunohistochemistry (IHC) for LPAR6 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissue microarray with patients’ information was detected. We constructed a systematic prognostic landscape in a variety of types of cancer base on the expression level of mRNA. We enclosed that higher LPAR6 mRNA expression level was associated with better overall survival in some types of malignancy. Moreover, LPAR6 significantly affects the prognostic potential of various cancers in The Cancer Genome Atlas Program (TCGA), especially in lung cancer. Tissue microarrays of lung cancer patient cohorts demonstrated that a higher protein level of LPAR6 was correlated to better overall survival of LUAD rather than LUSC cohorts. Further research indicated that the underlying mechanism of this phenome might be the mRNA expression level of LPAR6 was positively associated to infiltrating statuses of devious immunocytes in LUAD rather than in LUSC, that is, LPAR6 expression potentially contributes to the activation and recruiting of T cells (CD8+ T, naive T, effector T cell) and NK cells and inactivates Tregs, decreases T cell exhaustion and regulates T-helper (Th) cells in LUAD. Our discovery implies that LPAR6 is associated with prognostic potential and immune-infiltrating levels in LUAD. These discoveries imply that LPAR6 could be a promising novel biomarker for indicating the prognosis potential of LUAD patients.
GRACE-FO Antenna Phase Center Modeling and Precise Orbit Determination with Single Receiver Ambiguity Resolution

Precise knowledge of the phase center location of the global navigation satellite system (GNSS) antenna is a prerequisite for precise orbit determination (POD) of the low Earth orbit (LEO) satellite. The phase center offset (PCO) and phase center variation (PCV) values for the LEO antenna obtained from ground calibration cannot reflect the error sources encountered in the actual spacecraft environment. PCV corrections are estimated by ionosphere free (IF) carrier phase post-fit residuals of reduced dynamic orbit determination. Ambiguity resolution (AR) plays a crucial role in achieving the best orbit accuracy. The single receiver AR concept is realized using wide-lane (WL) and narrow-lane (NL) bias products. Single difference (SD) observations between satellites are applied to remove the receiver dependent phase bias. SD AR and traditional double difference (DD) AR methods are applied to fix the ambiguities. The recovered SD and DD IF ambiguities are taken as pseudo-observations to constrain the undifferenced IF ambiguity parameters in the POD process. The LEO orbits based on float ambiguity (FA), SD, AR, and DD AR are investigated. One year’s data collected by the Gravity Recovery And Climate Experiment Follow-On (GRACE-FO) mission and GPS precise products provided by the Center for Orbit Determination in Europe (CODE) were analyzed. Precise orbit generated by the Jet Propulsion Laboratory (JPL), independent satellite laser ranging (SLR), and K-band ranging (KBR) measurements were utilized to assess the orbit accuracy. More than 98% of SD WL and 95% of SD NL ambiguities are fixed, which confirms the good quality of the bias products and correctness of the SD AR method. With PCV corrections, the average phase residuals of DD and SD AR solutions are 0.13 and 0.41 mm, which indicates improved consistency between applied models and observations. Compared with JPL’s orbit, the SD AR orbits achieve the accuracy of 6.0, 6.2, and 5.1 mm in along-track, cross-track, and radial directions. The SD AR solutions show an average improvement of 18.3% related to the FA orbits while 6.3% is gained by the DD AR approach. The root mean squares (RMSs) of SLR residuals for FA, DD AR, and SD AR solutions are 11.5, 10.2, and 9.6 mm, which validate the positive effect of AR on POD. Standard deviation (STD) of KBR residuals for SD AR orbits is 1.8 mm while 0.9 mm is achieved by the DD AR method. The explanation is that the phase bias products used for SD AR are not free of errors and the errors may degrade the KBR validation. In-flight PCV calibration and ambiguity resolution improve the LEO orbit accuracy effectively.
Synthesis of Novel 1,2,4-Triazolyl Coumarin Derivatives as Potential Anticancer Agents

A series of novel coumarin derivatives carrying 1,2,4-triazole or 1,2,4-triazolo[3,4-b][1,3,4]thiadiazole moieties were prepared and evaluated in vitro as anticancer in the human colon cancer (HCT116) cell line. The derivatives 4c and 8c exhibited marked anticancer activity with IC50 values 4.363 and 2.656 µM, respectively. The molecular docking studies suggested possible interaction with tyrosine kinases (CDK2).
The Regulation of Plant Vegetative Phase Transition and Rejuvenation: miRNAs, a Key Regulator

In contrast to animals, adult organs in plants are not formed during embryogenesis but generated from meristematic cells as plants advance through development. Plant development involves a succession of different phenotypic stages and the transition between these stages is termed phase transition. Phase transitions need to be tightly regulated and coordinated to ensure they occur under optimal seasonal, environmental conditions. Polycarpic perennials transition through vegetative stages and the mature, reproductive stage many times during their lifecycles and, in both perennial and annual species, environmental factors and culturing methods can reverse the otherwise unidirectional vector of plant development. Epigenetic factors regulating gene expression in response to internal cues and external (environmental) stimuli influencing the plant’s phenotype and development have been shown to control phase transitions. How developmental and environmental cues interact to epigenetically alter gene expression and influence these transitions is not well understood, and understanding this interaction is important considering the current climate change scenarios, since epigenetic maladaptation could have catastrophic consequences for perennial plants in natural and agricultural ecosystems. Here, we review studies focusing on the epigenetic regulators of the vegetative phase change and highlight how these mechanisms might act in exogenously induced plant rejuvenation and regrowth following stress.
α-Glucan Phosphorylase-Catalyzed Enzymatic Reactions Using Analog Substrates to Synthesize Non-Natural Oligo- and Polysaccharides

As natural oligo- and polysaccharides are important biomass resources and exhibit vital biological functions, non-natural oligo- and polysaccharides with a well-defined structure can be expected to act as new functional materials with specific natures and properties. α-Glucan phosphorylase (GP) is one of the enzymes that have been used as catalysts for practical synthesis of oligo- and polysaccharides. By means of weak specificity for the recognition of substrates by GP, non-natural oligo- and polysaccharides has precisely been synthesized. GP-catalyzed enzymatic glycosylations using several analog substrates as glycosyl donors have been carried out to produce oligosaccharides having different monosaccharide residues at the non-reducing end. Glycogen, a highly branched natural polysaccharide, has been used as the polymeric glycosyl acceptor and primer for the GP-catalyzed glycosylation and polymerization to obtain glycogen-based non-natural polysaccharide materials. Under the conditions of removal of inorganic phosphate, thermostable GP-catalyzed enzymatic polymerization of analog monomers occurred to give amylose analog polysaccharides.
Has India’s Employment Guarantee Program Achieved Intended Targets?

This paper explores the performance of the world’s largest employment guarantee program, the Mahatma Gandhi National Rural Employment Guarantee Scheme in India, both nationally and through a sub-national-level comparison based on key performance indicators viz. (i) financial indicators, (ii) physical performance indicators, and (iii) inclusiveness indicators. The paper is based on administrative data taken from the Ministry of Rural Development from 2006 to 2019. Despite sharp increases in fund allocation, total expenditures, and utilization rates, there was deceleration in majority of physical performance indicators after 2016, including total person-days employment and person-days of employment per household, with wide variation in sub-national level implementation capabilities. The finding also rejects the falsity of saturation of MGNREGA work in the rural areas, which is reflected in a strong positive correlation between fund allocation and employment generation. Its broader objective of social safety net for vulnerable people in rural areas shows an achievement, although with some gaps in implementation. JEL classification: H53, J43, P25
Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

Sandy range land refers to a major component of grassland area types in the semi-arid area of northern China. Monitoring of vegetation and land surface temperature (LST) using remote sensing technology can help determine the degree of desertification in a regional and/or sub regional scale, as in the Horqin Sandy Land selected in this study. Correlation analysis was performed to examine the relationship between the fractional vegetation coverage (FVC) and the LST within one growing season (from May to August 2017), at different spatial scales. The results showed that the FVC increased from 0.12 in May to 0.29 in August, and the LST increased first and then declined. The highest LST was 41.68 °C in July, while the lowest was 28.62 °C in August. At the grid scale, the LST increased first and then declined with the increase of the FVC on 25 May, 10 June, and 29 August; the FVC ranged from 0.29–0.38, 0.27–0.32, and 0.29–0.38 with the preference of the ‘turning point’, respectively. A negative correlation was identified between the FVC and the LST and without any ‘turning point’ in the fitting curve on 28 July. The correlation between FVC and LST complied with the grid scale at the sample area scale. The coupling analysis of landscape pattern expressed by FVC and LST showed that, the landscape evenness, Euclidean nearest neighbor distance, and landscape splitting degree all showed strong coupling correlation in any study period (P). The landscape aggregation of FVC and LST showed a good coupling at the relatively high and low air temperature conditions of P1 and P3. Landscape contagion showed a good coupling between FVC and LST at relatively moderate air temperature condition of P1 and P4. Air temperature conditions and characteristics of vegetation coverage should be considered for a more targeted analysis when analyzing the relationship between FVC and LST and attention should be paid to the timing and type of study area in practical application.
Research on Distance Teaching System of English Course Based on Wireless Network Technology

The development in technology is taking place with an accelerating pace across the globe. The increasing expansion and advancement in the field of information technology and the modern teaching system provide a technical support for the development of a distance teaching system to learn English courses. Multimedia teaching system of English course based on B/S framework (system 1) and English teaching system based on MVC architecture (system 2) were the two most prominent and widely used approaches for the distance teaching system of English learning courses. These systems comprehensively consider the current English teaching needs, develop the existing architectures, discuss the system architecture and functions, and establish the corresponding development environment. However, the mentioned systems have the problem of high proportion of memory resource consumption and high failure rate of the communicating nodes. In order to reduce the proportion of memory resource consumption and node failure rate of distance teaching system and effectively improve the teaching effect, this study designed a distance teaching system of English course based on wireless network technology. In order to analyze the functionality and stability of the wireless network technology in distance teaching of English course, the server-side and client-side modules of the system are designed. The server side is mainly used to maintain and control the overall functions of the system, while the client side is used to access/request the contents from the server. On this basis, the system software module is designed. The memory consumption results are accounted for under 30%, which is significantly lower than the earlier-mentioned systems, and the node failure rate of the system proposed in this paper does not increase significantly and remains below 4% all the time which indeed is a very low amount of failure rate. The experimental results show that the memory resource consumption ratio and node failure rate of the proposed system are very low, and the application feedback effect is significantly better than the other systems.
A Role for the Bone Marrow Microenvironment in Drug Resistance of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis and remarkable resistance to chemotherapeutic agents. Understanding resistance mechanisms against currently available drugs helps to recognize the therapeutic obstacles. Various mechanisms of resistance to chemotherapy or targeted inhibitors have been described for AML cells, including a role for the bone marrow niche in both the initiation and persistence of the disease, and in drug resistance of the leukemic stem cell (LSC) population. The BM niche supports LSC survival through direct and indirect interactions among the stromal cells, hematopoietic stem/progenitor cells, and leukemic cells. Additionally, the BM niche mediates changes in metabolic and signal pathway activation due to the acquisition of new mutations or selection and expansion of a minor clone. This review briefly discusses the role of the BM microenvironment and metabolic pathways in resistance to therapy, as discovered through AML clinical studies or cell line and animal models.
Magnetic Particle Imaging: An Emerging Modality with Prospects in Diagnosis, Targeting and Therapy of Cancer

Simple Summary Magnetic Particle Imaging (MPI) is an emerging imaging technique that provides quantitative direct imaging of superparamagnetic iron oxide nanoparticles. In the last decade, MPI has shown great prospects as one of the magnetic methods other than Magnetic Resonance Imaging with applications covering cancer diagnosis, targeting enhancement, actuating cancer therapy, and post-therapy monitoring. Working on different physical principles from Magnetic Resonance Imaging, MPI benefits from ideal image contrast with zero background tissue signal, enabling hotspot-type images similar to Nuclear Medicine scans but using magnetic agents rather than radiotracers. In this review, we discussed the relevance of MPI to cancer diagnostics and image-guided therapy as well as recent progress to clinical translation. Abstract Background: Magnetic Particle Imaging (MPI) is an emerging imaging modality for quantitative direct imaging of superparamagnetic iron oxide nanoparticles (SPION or SPIO). With different physics from MRI, MPI benefits from ideal image contrast with zero background tissue signal. This enables clear visualization of cancer with image characteristics similar to PET or SPECT, but using radiation-free magnetic nanoparticles instead, with infinite-duration reporter persistence in vivo. MPI for cancer imaging: demonstrated months of quantitative imaging of the cancer-related immune response with in situ SPION-labelling of immune cells (e.g., neutrophils, CAR T-cells). Because MPI suffers absolutely no susceptibility artifacts in the lung, immuno-MPI could soon provide completely noninvasive early-stage diagnosis and treatment monitoring of lung cancers. MPI for magnetic steering: MPI gradients are ~150 × stronger than MRI, enabling remote magnetic steering of magneto-aerosol, nanoparticles, and catheter tips, enhancing therapeutic delivery by magnetic means. MPI for precision therapy: gradients enable focusing of magnetic hyperthermia and magnetic-actuated drug release with up to 2 mm precision. The extent of drug release from the magnetic nanocarrier can be quantitatively monitored by MPI of SPION’s MPS spectral changes within the nanocarrier. Conclusion: MPI is a promising new magnetic modality spanning cancer imaging to guided-therapy.
Smart cities and urban inequality

ABSTRACT Smart city technologies are criticized because they might exacerbate income inequalities. Four factors are suggested to explain this phenomenon: the uneven diffusion of information and communication technologies (ICTs); that these ICTs cannot be afforded by low-income citizens; that smart cities could further human capital divides; and the involvement of private actors in the implementation of projects. These critiques are not based on empirical verification. We test whether smart urban characteristics are associated with increases in urban income inequalities, using data on urban smartness and urban income inequality for 106 European cities. Results show that smart cities are associated with lower levels of urban income inequality.
Youth Identity in the Digital Age

AbstractThe digital culture has a profound influence on the formation of personal identity among the youth of Gens Y and Z. The networked society has strongly affected the process of forming an “inner identity,” a critical task in the adolescent period. The design of digital social media and apps can enslave youth in the “hive” and take away the solitude and resources needed for them to cultivate their “inner identity. ” Therefore, there is a need for institutions such as school, family, and church to reinvent better ways to accommodate youth and engage them with digital media with responsibility and discernment.
Pressure sensitivity of multiscale carbon-admixtures–enhanced cement-based composites

The pressure-sensitive cement-based composites added with multiscale carbon materials, that is, carbon blacks, carbon fibers, and carbon nanotubes are investigated. In the article, the sensing property of cement-based composites with seven different proportions of carbon blacks, carbon fibers, and carbon nanotubes under cyclic loading is discussed and then the optimized formula among these seven proportions is chosen to investigate the influences of temperature and saturation degree on its sensing properties. In addition, the maximum perceivable frequency of multiscale carbon-admixtures–enhanced cement-based composite is obtained from the experimental results. The results indicate that the fractional change in resistance of the cement-based sensing composites increases at first and then decreases with the increase of temperature, but decreases with the increase of humidity. Additionally, the fractional change in resistance has a decrease with the increase of loading frequency, and the cement-based sensing composites prepared can perceive the biggest loading frequency of 0.5 Hz.
ARRHYTHMIA CLASSIFICATION USING DEEP RESIDUAL NEURAL NETWORKS

Arrhythmia classification with electrocardiogram (ECG) is of great importance for the identification of arrhythmia diseases. However, since the variance of ECG signal in wave appears frequently, it is still a very challenging task to obtain a very good classification result. In this paper, an arrhythmia classification with ECG based on deep residual networks is proposed, of which two improved residual blocks are used to combine soft and hard subsampling. With such blocks, the network can well hold spatial information and improve the classification performance with a simple model structure. Experiments on the MIT-BIH arrhythmia database show that the proposed method obtained an average classification accuracy of 99.59% and an average classification specificity 99.63%, which are 0.26% and 0.57% higher than that of the most state-of-art method based on deep learning.
Temperature-Dependent Charge Transport in Polymer-Sorted Semiconducting Carbon Nanotube Networks with Different Diameter Distributions

The availability of purely semiconducting single-walled carbon nanotube (s-SWCNT) dispersions has prompted their widespread application in solution-processed thin-film transistors with excellent device performance but has also raised the question of how their precise composition influences charge transport properties in random networks. Here, we compare hole and electron transport in three different polymer-sorted s-SWCNT networks from nearly monochiral (6,5) nanotubes (diameter 0.76 nm) to mixed networks of s-SWCNTs with medium (0.8–1.3 nm) and large (1.2–1.6 nm) diameters. Temperature-dependent field-effect mobilities are extracted from gated four-point probe measurements that exclude any contributions by contact resistance and indicate thermally activated transport. The mobility data can be fitted to the fluctuation-induced tunneling model, although with significant differences between the network compositions. The network with the broadest diameter and thus bandgap range results in the strongest tempe.
Risks of Infection with SARS-CoV-2 Due to Contaminated Surfaces: A Scoping Review

The COVID-19 outbreak is a global health concern. Understanding the transmission modes of the SARS-CoV-2 virus is key to limit the spread of the pandemic. A lack of knowledge about the possibility of SARS-CoV-2 transmission and infection through contaminated surfaces is noticeable and recent studies have stated conflicting findings. This scoping review aims to understand the risks of contaminations via fomites better. Relevant publications were selected through Google Scholar, Web of Science, PubMed, Embase, Medline, and Cochrane Library, with related keywords. PRISMA-ScR guidelines were followed. Out of the 565 articles found, exclusion criteria were applied, duplicates removed, and a total of 25 articles were finally included in the study. The included documents were assessed by the contamination risk: “low” (37.5%), “high” (16.7%), “plausible” (8.3%), “unlikely” (8.3%) risk, and “insufficient evidence” (29.2%). Research in hospital settings was found as the main setting in the reviewed papers, which precisely indicated the risk of contaminated surfaces. This scoping review underscores the risk of SARS-CoV-2 infection via contaminated surfaces assessed as low in the majority of the reviewed articles. Further evaluation of the risk of the virus transmission by fomites and providing adequate information on its infectivity via contaminated surfaces in real-life conditions is essential.
Methane hydrate self-preservation features in oil suspensions

Features of methane hydrate self-preservation in the dispersions prepared from water in oil emulsions from two deposits in East Siberia were studied. Under experimental conditions, substantial self-preservation of the hydrate is observed in the dispersion based on oil 1, while the effect is weakened in the dispersions based on oil 2. It is demonstrated that the observed difference is connected with the presence of Span 80 surfactant in water in oil 2 emulsion.