Miracle-dz/UniFAR-FTUs huggingface dataset:
DashReStreamer: Framework for Creation of Impaired Video Clips under Realistic Network Conditions

The continuous rise of multimedia entertainment has led to an increased demand for delivering outstanding user experience of multimedia content. However, modelling user-perceived Quality of Experience (QoE) is a challenging task, resulting in efforts for better understanding and measurement of user-perceived QoE. To evaluate user QoE, subjective quality assessment, where people watch and grade videos, and objective quality assessment in which videos are graded using one or many objective metrics are conducted. While there is a plethora of video databases available for subjective and objective video quality assessment, these videos are artificially infused with various temporal and spatial impairments. Videos being assessed are artificially distorted with startup delay, bitrate changes, and stalls due to rebuffering events. To conduct a more credible quality assessment, a reproduction of original user experiences while watching different types of streams on different types and quality of networks is needed. To aid current efforts in bridging the gap between the mapping of objective video QoE metrics to user experience, we developed DashReStreamer, an open-source framework for re-creating adaptively streamed video in real networks. The framework takes inputs in the form of video logs captured by the client in a non-regulated setting, along with an.mpd file or a YouTube URL. The ultimate result is a video sequence that encompasses all the data extracted from the video log. DashReStreamer also calculates popular video quality metrics like PSNR, SSIM, MS-SSIM and VMAF. Finally, DashReStreamer allows creating impaired video sequences from the popular streaming platform, YouTube. As a demonstration of framework usage we created a database of 332 realistic video clips, based on video logs collected from real mobile and wireless networks. Every video clip is supplemented with bandwidth trace and video logs used in its creation and also with objective metrics calculation reports. In addition to dataset, we performed subjective evaluation of video content, assessing its effect on overall user QoE. We believe that this dataset and framework will allow the research community to better understand the impacts of video QoE dynamics.
Study of A Streamlining Method Based on Big Data

In the Marine environment, sonar depth sounder has a lot of data redundancy in the detection of high sampling rate. In order to improve computing power and reduce data storage and computation, a simplified data processing algorithm is proposed in this paper. The algorithm controls the sampling points by setting dual variables. A variable λ is used to control the allowable deviation threshold, the extracted points are interpolated against the original sampling points, and the λ value evaluates whether these points can represent the original topographic points. The other variable k is used to control the flag bit of the data position. Through this algorithm, the trend of data can be preserved as much as possible to ensure the authenticity of data. The simulation results show that the algorithm overcomes the shortcomings of the extreme point extraction method, ensures the accuracy of data fitting, and significantly reduces the amount of calculation. This method is easy to operate and convenient for engineering applications.
The Art of Cybercrime Community Research

In the last decade, cybercrime has risen considerably. One key factor is the proliferation of online cybercrime communities, where actors trade products and services, and also learn from each other. Accordingly, understanding the operation and behavior of these communities is of great interest, and they have been explored across multiple disciplines with different, often quite novel, approaches. This survey explores the challenges inherent to the field and the methodological approaches researchers used to understand this space. We note that, in many cases, cybercrime research is more of an art than a science. We highlight the good practices and propose a list of recommendations for future cybercrime community scholars, including taking steps to verify and validate results, establishing privacy and ethical research practices, and mitigating the challenge of ground truth data.
A Multi-source Visual SLAM Localization Algorithm That Reuses IMU Data

For complex environments, there is a problem of cumulative error in VIO algorithms based on vision and IMU. Therefore, this paper proposes a multi-source visual SLAM localization model that reuses IMU data. Firstly, integrating visual and IMU Data based on graph optimization, integrating IMU and GNSS Data based on EKF algorithms, through the above two methods, two primary positioning results are calculated. Then, two primary positioning results are integrated to output the final positioning results, and actual vehicle tests are conducted. The experimental results show that using the EKF algorithm can filter GNSS data with significant errors on the one hand; On the other hand, it can increase the frequency of GNSS data, reduce the error caused by timestamp matching, and thus improve the positioning accuracy of multi-source visual SLAM positioning models that reuses IMU data. Compared to directly using 1Hz original carrier differential fixed solution GNSS data, the RMS of positioning error which using filtered GNSS positioning data with the same frequency as vision is reduced by 90.04%.
Effects of Urbanization in China on the East Asian Summer Monsoon as Revealed by Two Global Climate Models

The East Asian summer monsoon (EASM), vulnerable to anthropogenic activities, exerts profound impacts on precipitation in East Asia. In recent decades, China has been experiencing rapid urbanization. It has not yet reached a consensus on its influences on EASM. Here, we introduce satellite‐derived urban impervious areas of China during 1985–2017 into two global climate models with contrasting biases of climatological EASM simulation. Both models consistently show that urbanization weakens EASM by increasing surface friction drag. The increased surface roughness reduces climatological southerly winds in the concentrated urbanization area. As a result, moisture convergence occurs south of the concentrated urbanization area with ascending motion, while moisture divergence with descending motion appears to the north, resulting in the precipitation anomalies of “southern flood and northern drought. ” The dominant role of urban dynamic forcing in regulating EASM is confirmed by reducing urban roughness to the level of croplands in sensitivity experiments. As urban dynamic forcing is largely mitigated, the urbanization impact mainly driven by urban thermal forcing conversely strengthens EASM due to enhanced land‐sea thermal contrast via urbanization‐induced warming. Spatial patterns and magnitudes of the urbanization‐induced EASM weakening vary between the two models due to disparities in their simulations of urban thermodynamic forcing and atmospheric adjustments. These results underscore the robust weakening effect of urbanization on EASM by urban friction drag and document uncertainties in the related spatial pattern and magnitude resulting from model discrepancies.
The adsorption of naproxen on adsorbents obtained from pepper stalk extract by green synthesis

Abstract This study presented the adsorption of naproxen on adsorbents filled with Cu, Fe, and Cu/Fe nanoparticles (NPs) obtained by the green synthesis method from pepper stem waste. The resulting adsorbents were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy-energy dispersive X-ray spectroscopy, and thermal gravimetric-differential thermal analysis. The amount of naproxen not adsorbed in the solution was determined from the cyclic voltammetry method, which is one of the electrochemical methods. The equation of the calibration curve used in the conversion of current to concentration and the R 2 value were y = 2.6165 x − 288.22 y=2.6165x-288.22 and 0.999, respectively. While the adsorption with the BS-extract was 3.3%, it was 46.142% for Cu-NP, 92 mg/g, and 57.622% for Fe-NP. With 116.0 mg/g Cu/Fe-NP, 82.406% and 165.0 mg/g capacity were reached. In the isotherm calculations, since the R 2 values for each adsorbent were in the range of 0.998–0.997, it was determined that the Freundlich and Halsey isotherms were compatible. Accordingly, under these conditions, Naproxen adsorption was multilayered and the adsorbent surface had a heterogeneous structure. Graphs drawn from the kinetic data showed that the adsorption obeyed the second-order kinetics. The R 2 value of the kinetic curves was 1 for all adsorbents. Thermodynamic data were determined by Van’t Hoff curves with R 2 values in the range of 0.998–0.996. The enthalpy value for Cu/Fe-NP was calculated to be 31.854 kJ/mol, the entropy value was 0.1993 kJ/mol-K, and the free energy was −27.5374 kJ/mol. These values were 34.605 kJ/mol, 0.272 kJ/mol-K, and −46.451 kJ/mol for Fe-NP, respectively; and 19.79 kJ/mol, 0.247 kJ/mol-K, and −54.3226 kJ/mol for Cu-NP. While all NPs (except Cu-NP) had a high recovery percentage in three cycles, this decreased to 80% at pH 10. For Cu-NP, the recovery percentage decreased at pH 8.5 and 7, but surprisingly it increased at pH 10. As a result, it can be inferred that NPs play a good role in adsorbent development, and Fe and Cu NP-doped BS adsorbents have a better effect on naproxen adsorption and have been evaluated as adsorbents suitable for use several times. Graphical abstract
The pyroptosis-related signature predicts prognosis and influences the tumor immune microenvironment in dedifferentiated liposarcoma

Abstract Background Dedifferentiated liposarcoma (DDL), a member of malignant mesenchymal tumors, has a high local recurrence rate and poor prognosis. Pyroptosis, a newly discovered programmed cell death, is tightly connected with the progression and outcome of tumor. Objective The aim of this study was to explore the role of pyroptosis in DDL. Methods We obtained the RNA sequencing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases to identify different pyroptosis-related genes (PRGs) expression pattern. An unsupervised method for clustering based on PRGs was performed. Based on the result of cluster analysis, we researched clinical outcomes and immune microenvironment between clusters. The differentially expressed genes (DEGs) between the two clusters were used to develop a prognosis model by the LASSO Cox regression method, followed by the performance of functional enrichment analysis and single-sample gene set enrichment analysis. All of the above results were validated in the Gene Expression Omnibus (GEO) dataset. Results Forty-one differentially expressed PRGs were found between tumor and normal tissues. A consensus clustering analysis based on PRGs was conducted and classified DDL patients into two clusters. Cluster 2 showed a better outcome, higher immune scores, higher immune cells abundances, and higher expression levels in numerous immune checkpoints. DEGs between clusters were identified. A total of 5 gene signatures was built based on the DEGs and divided all DDL patients of the TCGA cohort into low-risk and high-risk groups. The low-risk group indicates greater inflammatory cell infiltration and better outcome. For external validation, the survival difference and immune landscape between the two risk groups of the GEO cohort were also significant. Receiver operating characteristic curves implied that the risk model could exert its function as an outstanding predictor in predicting DDL patients’ prognoses. Conclusion Our findings revealed the clinical implication and key role in tumor immunity of PRGs in DDL. The risk model is a promising predictive tool that could provide a fundamental basis for future studies and individualized immunotherapy.
Designing host-associated microbiomes using the consumer/resource model

A key step towards rational microbiome engineering is the in silico sampling of realistic microbial communities that correspond to desired host phenotypes, and vice versa. This remains challenging due to a lack of generative models that simultaneously model compositions of host-associated microbiomes and host phenotypes. To that end, we present a machine learning model based on the consumer/resource (C/R) framework. In the model, variation in microbial ecosystem composition arises due to differences in the availability of effective resources (latent variables) while species’ resource preferences remain conserved. Variation in the same latent variables is used to model phenotypic variation across hosts. In silico microbiomes generated by our model accurately reproduce universal and dataset-specific statistics of bacterial communities. The model allows us to address two salient questions in microbiome design: (1) which host phenotypes maximally constrain the composition of the host-associated microbiome? and (2) what are plausible microbiome compositions corresponding to user-specified host phenotypes? Thus, our model aids the design and analysis of microbial communities associated with host phenotypes of interest.
The concept of the gain curve

Gain curves were introduced to explain how hermaphrodites could displace a dioecious population, and to account for sexual allocation in hermaphrodites. Terms for gamete production employed for the first purpose were transformed for the second into male and female gain curves that ostensibly defined fitness outcomes. These gain curves pose a conceptual challenge if they are specified separately because fitness at the population level cannot occur through one sex function independently of success through the other. If gain curves truly represent fitness outcomes, anomalies can arise, such as inequality of total male and female fitness in a population. Gain curves were originally used in a mathematical framework that treated the ostensible gain functions as inputs of male and female actors to a mating arena rather than as mating outcomes from that arena. I present a model of sex allocation that incorporates power functions to describe both gamete production and fitness gain in a manner that explicitly separates these two roles. In this formulation, the gamete production functions have the identical effect on optimal sex allocation originally attributed to gain curves while the true fitness gain curves lose nearly all effect on the optimum. Thus, despite the label, gain curves were implicitly describing inputs rather than outcomes. Because gain curves have been a staple of evolutionary ecology for decades, the implication is that much of our understanding of sexual allocation in hermaphrodites needs to be revisited. I outline some directions such an effort might take.
Engineering of methionine-auxotroph Escherichia coli via parallel evolution of two enzymes from Corynebacterium glutamicum’s direct-sulfurylation pathway enables its recovery in minimal medium

Methionine biosynthesis relies on the sequential catalysis of multiple enzymes. Escherichia coli, the main bacteria used in research and industry for protein production and engineering, utilizes the three-step trans-sulfurylation pathway catalyzed by L-homoserine O-succinyl transferase, cystathionine gamma synthase and cystathionine beta lyase to convert L-homoserine to L-homocysteine. However, most bacteria employ the two-step direct-sulfurylation pathway involving L-homoserine O-acetyltransferases and O-acetyl homoserine sulfhydrylase. We previously showed that a methionine-auxotroph E. coli strain (MG1655) with deletion of metA, encoding for L-homoserine O-succinyl transferase, and metB, encoding for cystathionine gamma synthase, could be complemented by introducing the genes metX, encoding for L-homoserine O-acetyltransferases and metY, encoding for O-acetyl homoserine sulfhydrylase, from various sources, thus altering the Escherichia coli methionine biosynthesis metabolic pathway to direct-sulfurylation. However, introducing metX and metY from Corynebacterium glutamicum failed to complement methionine auxotrophy. Herein, we generated a randomized genetic library based on the metX and metY of Corynebacterium glutamicum and transformed it into a methionine-auxotrophic E. coli strain lacking the metA and metB genes. Through multiple enrichment cycles, we successfully isolated active clones capable of growing in M9 minimal media without external methionine supplementation. The dominant metX mutations in the evolved methionine-autotrophs Escherichia coli were L315P and H46R. Interestingly, we found that a metY gene encoding only the N-terminus 106 out of 438 amino acids of the wild-type MetY enzyme is functional and supports the growth of the methionine auxotroph. Recloning the new genes into the original plasmid and transforming them to methionine auxotroph Escherichia coli validated their functionality. These results show that directed enzyme-evolution enables the fast engineering of new active variants within the Escherichia coli methionine direct-sulfurylation pathway, leading to efficient complementation.
Early survival in Atlantic salmon is associated with parental genotype at loci linked to timing of maturation late in life

Genomic regions with large phenotypic effects often contain genes that may have critical roles as early as development, with potentially broad physiological and morphological effects across later life stages. However, the life-stage-specific fitness consequences are rarely explored. In Atlantic salmon (Salmo salar), variation in two large effect genomic regions, six6 and vgll3, is linked to both age at maturity (a life-history trait with strong fitness effects) and several physiological and behavioural traits in early life. Here, by analysing offspring DNA samples from an experiment where fertilized eggs from known families of wild Atlantic salmon were planted into natural streams with manipulated nutrient levels, we tested if genetic variation in these loci is associated with survival in early life. We found that higher early life survival was linked to the genotype associated with late maturation in the vgll3 locus, but with early maturation in the six6 locus. These effects were significant only in high-nutrient streams, while we observed no effect in low-nutrient streams. We also showed that the differences in early survival were not explained by additive effects of genes in the offspring generation, but by maternal genotypes in the six6 locus, and by both parents’ genotypes in the vgll3 locus. These results suggest that indirect genetic effects are significant determinants of early life survival associated with these loci. Our study demonstrates an intriguing case of how large effect loci in the wild might exhibit complex fitness associations across life stages, and indicates that predicting evolutionary dynamics in the wild is likely difficult.
“Ca. Nitrosocosmicus” members are the dominant archaea associated with pepper (Capsicum annuum L.) and ginseng (Panax ginseng C.A. Mey.) plants’ rhizospheres

Background Although archaea are widespread in terrestrial environments, little is known about the selection forces that shape their composition, functions, survival, and proliferation strategies in the rhizosphere. The ammonia-oxidizing archaea (AOA), which are abundant in soil environments, catalyze the first step of nitrification and have the potential to influence plant growth and development significantly. Results Based on archaeal 16S rRNA and amoA gene (encoding the ammonia monooxygenase subunit A) amplicon sequencing analysis, distinct archaeal communities dominated by AOA were found to be associated with the root systems of pepper (Capsicum annuum L.) and ginseng (Panax ginseng C.A. Mey.) plants compared to bulk soil not penetrated by roots. AOA related to “Candidatus Nitrosocosmicus”, which, unlike most other AOA, harbor genes encoding manganese catalase (MnKat), dominated rhizosphere soils, and thus contributed to the development of distinct archaeal communities in rhizospheres. Accordingly, for both plant species, the copy number ratios of AOA MnKat genes to amoA genes were significantly higher in rhizosphere soils than in bulk soils. In contrast to MnKat-negative strains from other AOA clades, the catalase activity of a representative isolate of “Ca. Nitrosocosmicus” was demonstrated. Members of this clade were enriched in H2O2-amended bulk soils, and constitutive expression of their MnKat gene was observed in both bulk and rhizosphere soils. Conclusions Due to their abundance, “Ca. Nitrosocosmicus” members can be considered key players mediating the nitrification process in rhizospheres. The selection of this MnKat-containing AOA in rhizospheres of several agriculturally important plants hints at a previously overlooked AOA-plant interaction. For additional mechanistic analyses of the interaction, this key clade of AOA with cultured representatives can be employed.
A pathologically expanded, clonal lineage of IL-21 producing CD4+ T cells drives Inflammatory neuropathy

Inflammatory neuropathies, which include CIDP (chronic inflammatory demyelinating polyneuropathy) and GBS (Guillain Barre Syndrome), result from autoimmune destruction of the peripheral nervous system (PNS) and are characterized by progressive weakness and sensory loss. CD4+ T cells play a key role in the autoimmune destruction of the PNS. Yet, key properties of pathogenic CD4+ T cells remain incompletely understood. Here, we use paired scRNAseq and scTCRseq of peripheral nerves from an inflammatory neuropathy mouse model to identify IL-21 expressing CD4+ T cells that are clonally expanded and multifunctional. These IL-21-expressing CD4+ T cells are comprised of two transcriptionally distinct expanded populations, which express genes associated with Tfh and Tph subsets. Remarkably, TCR clonotypes are shared between these two IL-21-expressing populations, suggesting a common lineage differentiation pathway. Finally, we demonstrate that IL-21 signaling is required for neuropathy development and pathogenic T cell infiltration into peripheral nerves. IL-21 signaling upregulates CXCR6, a chemokine receptor that promotes CD4+ T cell localization in peripheral nerves. Together, these findings point to IL-21 signaling, Tfh/Tph differentiation, and CXCR6-mediated cellular localization as potential therapeutic targets in inflammatory neuropathies.