Miracle-dz/UniFAR-FTUs huggingface dataset:
MiRNA Dysregulation in Childhood Hematological Cancer

For decades, cancer biology focused largely on the protein-encoding genes that have clear roles in tumor development or progression: cell-cycle control, apoptotic evasion, genome instability, drug resistance, or signaling pathways that stimulate growth, angiogenesis, or metastasis. MicroRNAs (miRNAs), however, represent one of the more abundant classes of cell modulators in multicellular organisms and largely contribute to regulating gene expression. Many of the ~2500 miRNAs discovered to date in humans regulate vital biological processes, and their aberrant expression results in pathological and malignant outcomes. In this review, we highlight what has been learned about the roles of miRNAs in some of the most common human pediatric leukemias and lymphomas, along with their value as diagnostic/prognostic factors.
On the Spinal Cord Injury During Attempted Cervical Interlaminar Epidural Injection of Steroids

to three days, the catheter tip position fluctuated between T1 and T4, which correlated with the requirement for intravenous analgesics. Changes in patient position and degree of vertebral flexion, high compliance of the epidural space in infants, and high elasticity and stretchability of the Arrow FlexTip catheter may have been predisposing factors for catheter migration [1,2]. With position fluctuations of the catheter tip in the epidural space, physicians performing these procedures should maintain awareness of potential complications such as inadequate analgesia, bradycardia, Horner’s syndrome, and respiratory depression, as well as paralysis in patients receiving anticoagulants.
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising

In online display advertising, guaranteed contracts and real-time bidding (RTB) are two major ways to sell impressions for a publisher. Despite the increasing popularity of RTB, there is still half of online display advertising revenue generated from guaranteed contracts. Therefore, simultaneously selling impressions through both guaranteed contracts and RTB is a straightforward choice for a publisher to maximize its yield. However, deriving the optimal strategy to allocate impressions is not a trivial task, especially when the environment is unstable in real-world applications. In this paper, we formulate the impression allocation problem as an auction problem where each contract can submit virtual bids for individual impressions. With this formulation, we derive the optimal impression allocation strategy by solving the optimal bidding functions for contracts. Since the bids from contracts are decided by the publisher, we propose a multi-agent reinforcement learning (MARL) approach to derive cooperative policies for the publisher to maximize its yield in an unstable environment. The proposed approach also resolves the common challenges in MARL such as input dimension explosion, reward credit assignment, and non-stationary environment. Experimental evaluations on large-scale real datasets demonstrate the effectiveness of our approach.
A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild

Facial recognition has always been a challeng- ing task for computer vision scientists and experts. Despite complexities arising due to variations in camera parameters, illumination and face orientations, significant progress has been made in the field with deep learning algorithms now competing with human-level accuracy. But in contrast to the recent advances in face recognition techniques, Disguised Facial Identification continues to be a tougher challenge in the field of computer vision. The modern day scenario, where security is of prime concern, regular face identification techniques do not perform as required when the faces are disguised, which calls for a different approach to handle situations where intruders have their faces masked. Along the same lines, we propose a deep learning architecture for disguised facial recognition (DFR). The algorithm put forward in this paper detects 20 facial key-points in the first stage, using a 14-layered convolutional neural network (CNN). These facial key-points are later utilized by a support vector machine (SVM) for classifying the disguised faces based on the euclidean distance ratios and angles between different facial key-points. This overall architecture imparts a basic intelligence to our system. Our key-point feature prediction accuracy is 65% while the classification rate is 72.4%. Moreover, the architecture works at 19 FPS, thereby performing in almost real-time. The efficiency of our approach is also compared with the state-of-the-art Disguised Facial Identification methods.
Finite Element Analysis for the Self-Loosening Behavior of the Bolted Joint with a Superelastic Shape Memory Alloy

A macroscopic constitutive model is proposed in this research to reproduce the uniaxial transition ratcheting behaviors of the superelastic shape memory alloy (SMA) undergoing cyclic loading, based on the cosine-type phase transition equation with the initial martensite evolution coefficient that provides the predictive residual martensite accumulation evolution and the nonlinear feature of hysteresis loop. The calculated results are compared with the experimental results to show the validity of the present computational procedure in transition ratcheting. Finite element implementation for the self-loosening behavior of the superelastic SMA bolt is then carried out based on the proposed constitutive model to analyze the curves of stress-strain responses on the bolt bar, clamping force reduction law, dissipation energy change law of the bolted joint for different external loading cases, and preload force of the bolt.
Wideband Hybrid Precoding for Next-Generation Backhaul/Fronthaul Based on mmWave FD-MIMO

Millimeter-wave (mmWave) communication is considered as an indispensable technique for the next-generation backhaul/fronthaul network thanks to its large transmission bandwidth. Especially for heterogeneous network (HetNet), the mmWave full-dimension (FD)-MIMO is exploited to establish the backhaul/fronthaul link between phantom-cell base stations (BSs) and macro-cell BSs, where an efficient precoding is prerequisite. Against this background, this paper proposes a principle component analysis (PCA)-based hybrid precoding for wideband mmWave MIMO backhaul/fronthaul channels. We first propose an optimal hybrid precoder by exploiting principal component analysis (PCA), whereby the optimal high dimensional frequency-selective precoder are projected to the low-dimensional frequency-flat precoder. Moreover, the combiner is designed by leveraging the weighted PCA, where the covariance of received signal is taken into account as weight to the optimal minimum mean square error (MMSE) fully-digital combiner for further improved performance. Simulations have confirmed that the proposed scheme outperforms conventional schemes in spectral efficiency (SE) and bit-error-rate (BER) performance.
Feature Learning for Meta-Paths in Knowledge Graphs

In this thesis, we study the problem of feature learning on heterogeneous knowledge graphs. These features can be used to perform tasks such as link prediction, classification and clustering on graphs. Knowledge graphs provide rich semantics encoded in the edge and node types. Meta-paths consist of these types and abstract paths in the graph. Until now, meta-paths can only be used as categorical features with high redundancy and are therefore unsuitable for machine learning models. We propose meta-path embeddings to solve this problem by learning semantical and compact vector representations of them. Current graph embedding methods only embed nodes and edge types and therefore miss semantics encoded in the combination of them. Our method embeds meta-paths using the skipgram model with an extension to deal with the redundancy and high amount of meta-paths in big knowledge graphs. We critically evaluate our embedding approach by predicting links on Wikidata. The experiments indicate that we learn a sensible embedding of the meta-paths but can improve it further.
Effect of Different Disinfectants on Bacterial Aerosol Diversity in Poultry Houses

To better understand the effect of different disinfectants on the types and quantities of microorganisms in a broiler chicken house, five different types of disinfectants, including ozone, available chlorine, quaternary ammonium salt, glutaraldehyde, and mixed disinfectant, were used. The broiler house microbial communities were analyzed by high-throughput sequencing combined with air sampling. The results showed that the concentrations of airborne aerobic bacteria in the empty broiler houses after application of different disinfectants were significantly reduced compared to a house untreated with disinfectant (P < 0.05 or P < 0.01), and the number of inhalable particles of airborne aerobic bacteria sharply decreased after disinfection. Of the five disinfectants, the mixed disinfectant had the best disinfection efficacy on the total microbial communities (P < 0.05). A total of 508,143 high-quality sequences were obtained by high-throughput sequencing, which identified 1995 operational taxonomic units. In total, 42 phyla and 312 genera were identified. The structures of airborne microbial communities in the broiler houses after the different disinfectants were applied differed. In the house treated with the mixed disinfectant, the microbial communities containing opportunistic pathogens, such as Escherichia-Shigella, Bacillus, and Pseudomonas, had the lowest abundance, with a significant decrease compared to the house untreated with disinfectant. The alpha diversity index showed low diversity of the microbial communities in the house treated with mixed disinfectant. In contrast to the other four disinfectants, only a small amount of bacteria was detected in the air sample in the house treated with the mixed disinfectant; specifically, only four phyla were found (Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes). The mixed disinfectant produced a positive effect on disinfection for four phyla; however, it didn’t thoroughly eliminate them. At genus level, Bacillus, Arenimonas, and Shinella could not be detected in the house treated with the mixed disinfectant, but were detected in houses treated with other disinfectants. The high-throughput sequencing results revealed that the combination of multiple disinfectants exhibited a good disinfection efficacy and that this technique could disinfect the air of broiler houses. These results will help guide the development of a reasonable program for broiler house disinfection.
Exploring the Adoption of Sports Brand Apps: An Application of the Modified Technology Acceptance Model

The purpose of this article was to apply the modified technology acceptance model (TAM) to examine factors influencing consumers' intention and actual behavior in using sports brand apps. Convenience sampling was conducted for Korean consumers (N = 261) of sports brand apps. Data were analyzed by partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0. The results found that the level of enjoyment had a significantly positive effect on the perceived ease of use, while perceived ease of use also positively affected perceived usefulness. Behavioral intention to use sports brand apps was most significantly influenced by perceived enjoyment, followed by perceived usefulness, and then perceived ease of use. Moreover, behavioral intention positively affected actual behavior. In addition, a multi-group analysis carried out found differences between three age groups (20s, 30s, and 40+) regarding the use of sports brand apps. The findings provide a better understanding of consumer behavior when using sports brand apps.
Finite Element Analysis of Long Posterior Transpedicular Instrumentation for Cervicothoracic Fractures Related to Ankylosing Spondylitis

Study Design: Biomechanical finite element model analysis. Objectives: Spinal fractures related to ankylosing spondylitis (AS) are often treated by long posterior stabilization. The objective of this study is to develop a finite element model (FEM) for spinal fractures related to AS and to establish a biomechanical foundation for long posterior stabilization of cervicothoracic fractures related to AS. Methods: An existing FEM (consisting of 2 separately developed models) including the cervical and thoracic spine were adapted to the conditions of AS (all discs fused, C0-C1 and C1-C2 mobile). A fracture at the level C6-C7 was simulated. Besides a normal spine (no AS, no fracture) and the uninstrumented fractured spine 4 different posterior transpedicular instrumentations were tested. Three loads (1.5g, 3.0g, 4.5g) were applied according to a specific load curve. Results: All posterior stabilization methods could normalize the axial stability at the fracture site as measured with gap distance. The maximum stress at the cranial instrumentation end (C3-C4) was slightly greater if every level was instrumented, than in the skipped level model. The skipped level instrumentation achieved similar rotatory stability as the long multilevel instrumentation. Conclusions: Skipping instrumentation levels without giving up instrumentation length reduced stresses in the ossified tissue within the range of the instrumentation and did not decrease the stability in a FEM of a cervicothoracic fracture related to AS. Considering the risks associated with every additional screw placed, the skipped level instrumentation has advantages regarding patient safety.
Shrub encroachment into grasslands: end of an era?

Shifts in the abundance of grasses and woody plants in drylands have occurred several times during the Holocene. However, our understanding of the rates and dynamics of this state-change in recent decades is limited to scattered studies conducted at disparate spatial and temporal scales; the potential misperceptions of shrub cover change could be remedied using cross spatiotemporal scale analyses that link field observations, repeat ground-level photography and remote sensing perspectives. The study was conducted across a semi-arid landscape in southern Arizona. Local data from long-term transects revealed three distinct chronological phases of shrub cover change: expansion (1961–1991, 0.7% y−1), decline (1992–1997, −2.3% y−1) and stabilization (1998–2012, 22–25% with no net cover change). Twenty-eight years (1984–2011) of broad-scale Landsat Thematic Mapper assessments confirm that shrub cover has been relatively stable in recent decades regardless of grazing regimes and landforms with the exception of the proliferation of succulents at lower elevations (verified by repeat photography acquired in 1987 and 2015) where the physical environment is the harshest, reflecting elevated temperature and winter precipitation deficit. Warmer, drier future climates are predicted to reduce woody plant carrying capacity and promote a shift to xerophytic succulents.
The Inhibitory Effect of Ojeoksan on Early and Advanced Atherosclerosis

Atherosclerosis is closely related to vascular dysfunction and hypertension. Ojeoksan (OJS), originally recorded in an ancient Korean medicinal book named “Donguibogam”, is a well-known, blended herbal formula. This study was carried out to investigate the beneficial effects of OJS on atherosclerosis in vitro and in vivo. Western-diet-fed apolipoprotein-E gene-deficient mice (ApoE −/−) were used for this study for 16 weeks, and their vascular dysfunction and inflammation were analyzed. OJS-treated ApoE −/− mice showed lowered blood pressure and glucose levels. The levels of metabolic parameters with hyperlipidemia attenuated following OJS administration. Hematoxylin and eosin (H&E) staining revealed that treatment with OJS reduced atherosclerotic lesions. OJS also suppressed the expression of adhesion molecules and matrix metalloproteinases (MMPs) compared to Western-diet-fed ApoE −/− mice and tumor necrosis factor-alpha (TNF-α)-stimulated human umbilical vein endothelial cells (HUVECs). Expression levels of MicroRNAs (miRNA)-10a, -126 3p were increased in OJS-fed ApoE −/− mice. OJS significantly increased the phosphorylation of endothelial nitric oxide synthase (eNOS) and protein kinase B (Akt), which are involved in nitric oxide (NO) production. OJS also regulated eNOS coupling by increasing the expression of endothelial GTP Cyclohydrolase-1 (GTPCH). Taken together, OJS has a protective effect on vascular inflammation via eNOS coupling-mediated NO production and might be a potential therapeutic agent for both early and advanced atherosclerosis.
Flight of the fruit fly

There comes a time in each of our lives where we grab a thick section of the morning paper, roll it up and set off to do battle with one of nature’s most accomplished aviators— the fly. If, however, instead of swatting we could magnify our view and experience the world in slow motion we would be privy to a world-class ballet full of graceful figure-eight wing strokes, effortless pirouettes, and astonishing acrobatics. After watching such a magnificent display, who among us could destroy this virtuoso? How do flies produce acrobatic maneuvers with such precision? What control mechanisms do they need to maneuver? More abstractly, what problem are they solving as they fly? In this article and the associated video presentation of my invited lecture from the 71st Annual Meeting of the American Physical Society’s Division of Fluid Dynamics, I describe the challenges associated with answering these questions, our attempts to investigate them, and, through various demonstrations depicted in the video, qualitatively illustrate the mechanisms used by these insects to achieve these astonishing behaviors.
RDF Data Storage and Query Processing Schemes

The Resource Description Framework (RDF) represents a main ingredient and data representation format for Linked Data and the Semantic Web. It supports a generic graph-based data model and data representation format for describing things, including their relationships with other things. As the size of RDF datasets is growing fast, RDF data management systems must be able to cope with growing amounts of data. Even though physically handling RDF data using a relational table is possible, querying a giant triple table becomes very expensive because of the multiple nested joins required for answering graph queries. In addition, the heterogeneity of RDF Data poses entirely new challenges to database systems. This article provides a comprehensive study of the state of the art in handling and querying RDF data. In particular, we focus on data storage techniques, indexing strategies, and query execution mechanisms. Moreover, we provide a classification of existing systems and approaches. We also provide an overview of the various benchmarking efforts in this context and discuss some of the open problems in this domain.
Urinary Incontinence Is Associated With Physical Performance Decline in Community-Dwelling Older Women: Results From the International Mobility in Aging Study

Objective: The objective of this study is to evaluate the influence of urinary incontinence (UI) on physical performance. Method: In prospective analyses from the International Mobility in Aging Study (IMIAS), 915 women (65-74 years) from Canada, Colombia, Albania, and Brazil were evaluated in relation to self-reported UI (past week) and physical performance (Short Physical Performance Battery [SPPB]), with reevaluation after 2 years. Linear mixed models examined the influence of UI on SPPB, adjusted by covariates (age, study site, education, income sufficiency, body mass index [BMI] and parity). Results: Women reporting some UI presented lower SPPB mean (β = −0.41, p = .009) and a greater reduction (β = −0.53, p = .001) over 2 years than those reporting no UI. Discussion: Compared with no reported UI, some UI was associated with worse and more pronounced declines in physical performance over 2 years. This study highlights the importance of practices to reduce UI to contribute to healthier aging.
The Potential Role of Genetic Markers in Talent Identification and Athlete Assessment in Elite Sport

In elite sporting codes, the identification and promotion of future athletes into specialised talent pathways is heavily reliant upon objective physical, technical, and tactical characteristics, in addition to subjective coach assessments. Despite the availability of a plethora of assessments, the dependence on subjective forms of identification remain commonplace in most sporting codes. More recently, genetic markers, including several single nucleotide polymorphisms (SNPs), have been correlated with enhanced aerobic capacity, strength, and an overall increase in athletic ability. In this review, we discuss the effects of a number of candidate genes on athletic performance, across single-skilled and multifaceted sporting codes, and propose additional markers for the identification of motor skill acquisition and learning. While displaying some inconsistencies, both the ACE and ACTN3 polymorphisms appear to be more prevalent in strength and endurance sporting teams, and have been found to correlate to physical assessments. More recently, a number of polymorphisms reportedly correlating to athlete performance have gained attention, however inconsistent research design and varying sports make it difficult to ascertain the relevance to the wider sporting population. In elucidating the role of genetic markers in athleticism, existing talent identification protocols may significantly improve—and ultimately enable—targeted resourcing in junior talent pathways.
Factors influencing exotic species richness in Argentina’s national parks

Exotic species introductions are a global phenomenon and protected areas are susceptible to them. Understanding the drivers of exotic species richness is vital for prioritizing natural resource management, particularly in developing countries with limited resources. We analyzed the influence of coarse resolution factors on exotic species richness (plants, mammals, and birds) in Argentina’s National Parks System. We collected data on native species richness, year of park formation, park area, region, elevation range, number of rivers crossing area boundaries, roads entering area, mean annual rainfall, mean annual temperature, mean annual number of visitors, and Human Influence Index within and surrounding each park. We compiled 1,688 exotic records in 36 protected areas: 83% plants and 17% animals (9.5% mammals, 5.5% birds, 1.5% fishes, 0% amphibians, 0% reptiles). The five parks with the most exotic species (all taxa combined) were in north Patagonia. Exotic grasses were the most common exotic plants, and within animals, lagomorphs and feral ungulates were remarkably widespread. Exotic plant richness was mostly influenced by temperature and native plant richness, while exotic mammal and bird richness was driven mostly by anthropogenic variables, with models explaining 36–45% of data deviance. Most variables that positively influenced exotic taxa were indirectly related to an increase in spatial heterogeneity (natural or anthropogenic), suggesting greater niche space variability as facilitators of exotic richness increase. Additional data are needed to further investigate the patterns and mechanisms of exotic species richness in protected areas, which will help to prioritize the greatest needs of monitoring and management.