Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling limit of the random walk in random environment in the subdiffusive case

We consider a random walk on a Galton-Watson tree in random environment, in the subdiffusive case. We prove the convergence of the renormalised height function of the walk towards the continuous-time height process of a spectrally positive strictly stable L\'evy process, jointly with the convergence of the renormalised range of the walk towards the real tree coded by the latter continuous-time height process.
B cells in primitive vertebrate act as pivotal antigen presenting cells in priming adaptive immunity (P5035)

The long-held paradigm that B cells are unable to phagocyte large particles has been broken by a new discovery that teleost B cells have potent phagocytic and microbicidal abilities. This finding provides preliminary clues that B cells in primitive vertebrates might act as pivotal antigen presenting cells (APCs) in priming adaptive immunity. In this study, we provide evidence for this suggestion in zebrafish model. By in vitro antigen presentation and in vivo adoptive transfer assays, we found that zebrafish B cells have potent capacity to present both soluble and particulate antigens to prime naive CD4+ T cells. The CD86 and CD83 co-stimulatory molecules were identified to be essential for this process. Besides, IL-4 was found to be able to dramatically promote the B cell-mediated CD4+ T cell priming by up-regulating the expression of CD86, CD83 and MHC II molecules on B cells. Our results suggest that B cells in primitive vertebrates were important professional APCs for the initiation of adaptive immunity, whose functional characterization resembles the dendritic cells (DCs). The CD86 and CD83 were two ancient co-stimulatory molecules originating from teleost fish, whose regulatory functions were conserved from fish to mammals throughout vertebrate evolution. These results benefit to the better understanding of the evolutionary history of B subsets such as the origin of B1 cells, as well as the origin of immune-regulatory signaling networks in adaptive immunity.
How does the COVID-19 pandemic influence tourist rating behaviour? An empirical exploration based on expectation theory

ABSTRACT The COVID-19 pandemic has caused serious consequences to the world economy and the tourism and hospitality industries, which depend on human movement, have been greatly affected. Unlike previous studies that have mainly investigated different focus attributes in online reviews after the COVID-19 pandemic, this study focuses on how such a health crisis affects individual tourists’ rating behaviour. To address the research question, this study collected data from Qunar.com and adopted an interrupted time-series strategy in which the treated observations are set as tourists’ rating behaviour after the pandemic and control observations are set as tourists’ rating behaviour before the pandemic. Our results indicate that the COVID-19 pandemic positively affects tourist ratings for hotels, and such a positive effect is strengthened when tourists focus on health-related issues or travel for business. However, such an influence is weakened if hotels have a high star level. This study offers implications for both academics and practitioners.
Slow waves of boiling under hot water depressurization

Experimental studies of hot water depressurization show that the pressure in a vessel, just after it is opened, drops much lower than the pressure of saturation but the liquid does not boil uniformly throughout the vessel. Essentially, liquid boiling begins only on the arrival of a ‘slow wave’ of rarefaction which moves at a low speed of approximately 10 m s−1 from the open end deep into the vessel. To explain this phenomenon we suggest a model that takes into account the difference in phase velocities. Although this difference in bubble flows is only about 1 m s−1 it proves to be sufficient to cause bubble breakup. Using this model we obtained the ‘slow wave of boiling’ in a numerical experiment that was in good agreement with the physical experiment.
National Surveillance of Tetracycline, Erythromycin, and Clindamycin Resistance in Invasive Streptococcus pyogenes: A Retrospective Study of the Situation in Spain, 2007–2020

Background: This work reports on antimicrobial resistance data for invasive Streptococcus pyogenes in Spain, collected by the ‘Surveillance Program for Invasive Group A Streptococcus’, in 2007–2020. Methods: emm typing was determined by sequencing. Susceptibility to penicillin, tetracycline, erythromycin, and clindamycin was determined via the E-test. tetM, tetO, msrD, mefA, ermB, ermTR, and ermT were sought by PCR. Macrolide-resistant phenotypes (M, cMLSB, and iMLSB) were detected using the erythromycin–clindamycin double-disk test. Resistant clones were identified via their emm type, multilocus sequence type (ST), resistance genotype, and macrolide resistance phenotype. Results: Penicillin susceptibility was universal. Tetracycline resistance was recorded for 237/1983 isolates (12.0%) (152 carried only tetM, 48 carried only tetO, and 33 carried both). Erythromycin resistance was detected in 172/1983 isolates (8.7%); ermB was present in 83, mefA in 58, msrD in 51, ermTR in 46, and ermT in 36. Clindamycin resistance (methylase-mediated) was present in 78/1983 isolates (3.9%). Eight main resistant clones were identified: two that were tetracycline-resistant only (emm22/ST46/tetM and emm77/ST63/tetO), three that were erythromycin-resistant only (emm4/ST39/mefA-msrD/M, emm12/ST36/mefA-msrD/M, and emm28/ST52/ermB/cMLSB), and three that were tetracycline–erythromycin co-resistant (emm11/ST403/tetM-ermB/cMLSB, emm77/ST63/tetO-ermTR/iMLSB, and emm77/ST63/tetM-tetO-ermTR/iMLSB). Conclusions: Tetracycline, erythromycin, and clindamycin resistance rates declined between 2007 and 2020. Temporal variations in the proportion of resistant clones determined the change in resistance rates.
The CfA Einstein Observatory extended deep X-ray survey

All IPC exposures in the Einstein Extended Deep X-ray Survey program have been reanalyzed. The current survey covers about 2.3 sq deg with a typical limiting sensitivity of about 5 x 10 to the -14th ergs/sq cm/s in the energy range from 0.8-3.5 keV. A total of 25 IPC sources are detected above a threshold of 4.5 sigma. A total of 18 are detected independently in the HRI, leading to the identification of six with stars and 11 with extragalactic objects. The remaining sources are classified as extragalactic. The population of identified extragalactic objects is dominated by QSOs, with one or two possible clusters. The basic conclusions of the original survey remain unchanged. 49 refs.
Lithium and rapid rotation in chromospherically active single giants

Spectroscopic observations have been obtained of a group of moderately rapidly rotating (v sin i=6-46 km s −1 ) chromospherically active, single giants. Such rotational velocities indicate that the rotostat hypothesis of Gray (1989) must be modified. Lithium abundances have been determined for all but one of these stars and for a number of chromospherically active binaries. Many of the single giants have unexpectedly large lithium abundances. The rapid rotation of these single stars, which results in increased chromospheric activity via the dynamo, appears to be related to their high lithium abundances
Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data

Abstract The available beach classification algorithms and sediment budget models are mainly based on in situ parameters, usually unavailable for several coastal areas. A morphological analysis using remotely sensed data is a valid alternative. This study focuses on the application of data mining techniques, particularly decision trees (DTs) and artificial neural networks (ANNs) to an IKONOS-2 image in order to identify beach features/patterns in a stretch of the northwest coast of Portugal. Based on knowledge of the coastal features, five classes were defined. In the identification of beach features/patterns, the ANN algorithm presented an overall accuracy of 98.6% and a kappa coefficient of 0.97. The best DTs algorithm (with pruning) presents an overall accuracy of 98.2% and a kappa coefficient of 0.97. The results obtained through the ANN and DTs were in agreement. However, the ANN presented a classification more sensitive to rip currents. The use of ANNs and DTs for beach classification from remotely sensed data resulted in an increased classification accuracy when compared with traditional classification methods. The association of remotely sensed high-spatial resolution data and data mining algorithms is an effective methodology with which to identify beach features/patterns.
Investigations into Differential Glyphosate Sensitivity between Two Horseweed (Conyza Canadensis) Growth Types

Abstract Horseweed [Conyza canadensis (L.) Cronquist] grows in one of two distinct growth phenotypes, “rosette” and “upright” growth types, and they have recently been observed co-occurring in Michigan fields. Previous research found that upright plants from two glyphosate-resistant populations were 3- and 4-fold less sensitive to glyphosate than their rosette siblings. Further experiments were conducted to investigate whether differential glyphosate sensitivity of the growth types was due to glyphosate retention, absorption, or translocation. The total amount of glyphosate retained on the C. canadensis leaf surface was similar for both growth types; however, on a per-weight and per-area bases, the upright growth type retained 21% and 18% less glyphosate, respectively. Glyphosate absorption was up to 85% at 168 h after treatment (HAT), and was not different between the rosette and upright growth types or between the susceptible (S) and resistant (R) biotypes. Additionally, there was no difference in translocation between the two growth types within each biotype at any time point. Interestingly, at 168 HAT, [14C]glyphosate translocation was higher in the S rosette compared with the two growth types from the R biotype; however, the S upright type was similar to both R growth types. Thus, glyphosate resistance in the R biotype may be due to an alternative mechanism rather than impaired translocation, which has been cited as the primary mechanism of glyphosate resistance in C. canadensis. These results suggest that reduced glyphosate retention on a per-weight and per-area bases of the upright growth type may contribute to increased glyphosate tolerance due to a diluted concentration of glyphosate in the plant. However, another factor is likely related to the mechanism of resistance within the R biotype, which is contributing to a 3-fold difference in glyphosate sensitivity between the two growth types, such as alterations in EPSPS gene expression or changes in undescribed metabolism genes.
Space Target Classification With Corrupted HRRP Sequences Based on Temporal–Spatial Feature Aggregation Network

High-resolution range profile (HRRP) sequences have great potential for space target classification because they can provide both scattering information and micromotion information. However, many factors cause an obtained HRRP sequence for a space target to be corrupted in real cases due to noise interference, limited radar resources, and the requirement of multitarget observations. Many space target classification methods cease to be effective when HRRP sequences are corrupted, so classifying space targets with corrupted HRRP sequences is still a challenging problem. To solve this problem, a novel space target classification method based on a temporal–spatial feature aggregation network (TSFA-Net) is proposed by using the corrupted HRRP sequences directly. First, a sequence-to-token module (S2T-module) is designed to extract low-level and fine-grained features from the raw inputs. Second, to effectively model the long-range dependencies among corrupted HRRP sequences and capture global representations without losing target local features, we propose a parallel and dual-branch block, i.e., a temporal–spatial feature aggregation block (TSFA-block), by combining a Transformer network and a convolutional neural network (CNN). Then, via progressively hierarchically stacking TSFA-blocks, a hierarchical temporal–spatial feature aggregation subnetwork (H-TSFA-subnetwork) is constructed to obtain the final temporal–spatial features. Finally, a token-to-label module (T2L-module) is adopted to obtain the classification results. Extensive experiments demonstrate that the proposed method achieves state-of-the-art classification accuracy for space target classification with HRRP sequences, especially under the conditions of a low signal-to-noise ratio and a high missing rate.
Similarity solutions for magnetic bubble expansion

A model for an expanding magnetic bubble or plasmoid is introduced, corresponding to a large aspect ratio torus, having one-dimensional (cylindrical) symmetry but with three dimensional expansion, with the length of the cylinder expanding in time in the same manner as the radius. This model has a general class of similarity equations in ideal magnetohydrodynamics (MHD) for spherical expansion. There are two parameters c, d characterizing the similarity solutions, depending on boundary conditions and conservation relations. These solutions exhibit either tangential discontinuities or shocks at the boundary, depending on the values of the constants c and d. Some of the solutions have magnetic fluxes within the bubble increasing with time, but with smaller or zero magnetic fields outside the bubble, requiring a shock and a dynamo in the shock region. The results of simulations of one class of solutions with a Lagrangian MHD code show good agreement. Some of the properties of fully toroidal solutions of the s.
A new measure of nominal‐ordinal association

A new measure for evaluating the strength of the association between a nominal variable and an ordered categorical response variable is introduced. The introduction of a new measure is justified by analysing the characteristics of a measure of the nominal-ordinal association proposed by Agresti (1981), especially with respect to the problem of the 'choice' of a predictive variable. The sample-based version of the index is studied, and its asymptotic standard error and asymptotic distribution are derived. Simulations are considered to evaluate the adequacy of the asymptotic approximation determined, following Goodman & Kruskal (1963).
Turbulent Jet Energy Dissipation at Vertical Drops

The energy loss of the vertical drop with subcritical flow in the upstream channel has been studied experimentally with a physical model of 0.20 m drop height. Experimental data were collected in a range where few data exist. Based on a similarity between a turbulent surface jet and the flow over the drop, a model is developed using the theories of the shear layer and fully developed surface jet to estimate the energy loss. The results were compared with previous and current experimental data and were found to agree well with the proposed model.
Economic and value chain analysis to support an investigation and risk mitigation efforts on Marek’s disease in layers in the southern part of Thailand

Background and Aim: Marek’s disease (MD) is a common lymphoproliferative disease affecting chickens and causing economic losses in commercial poultry. The MD outbreak was noticed in the southern part of Thailand in 2019. The suspected cases were found with an abnormal number of cases of layers dying with clinical signs, for example, weakness and emaciation, with evidence of MD gross lesions. This study aimed to raise awareness of the MD outbreak through value chain analysis (VCA), identifying associated possible risk factors, and estimating the associated economic impact. Materials and Methods: Value chain analysis, including seasonal calendar, value chain diagram, and layer movement mapping of the layer industry, was conducted. High-risk stakeholders were identified on the basis of risk practices and interactions between stakeholders. A case–control study was conducted to determine risk factors associated with the MD outbreak on layer farms, and partial budget analysis was used to estimate economic losses associated with MD. Results: The value chain diagram showed the linkages between stakeholders, including estimation of the percentage of products moved from one stakeholder group to another and the negotiated price. Fourteen out of 35 layer farms were case farms. Farm size and source of birds were significantly associated with the MD outbreak. The MD outbreak caused total economic losses of 295,823 USD. Farms that slaughtered infected birds with additional revenues incurred losses of 140,930 USD, whereas farms that culled infected birds without additional revenue returned incurred losses of 1995 USD. Conclusion: The VCA provided a better understanding of the layer and egg businesses in South Thailand and guided the development of questionnaires for outbreak investigation. The potential risk factor findings suggested the need for further exploration of the source of the MD outbreak.
The three-dimensional power spectrum measured from the APM Galaxy Survey – I. Use of the angular correlation function

We describe a method of recovering the three-dimensional power spectrum of galaxy clustering from measurements of the angular correlation function w(θ). We apply the technique to w(θ) measured from the APM Galaxy Survey in the magnitude range 17≤b J ≤20, using models for the redshift distribution of APM galaxies that reproduce the distributions measured in faint redshift surveys. The APM power spectrum is a power law at high wavenumbers, with slope P(k)∞k −1.25 , as expected from the power-law slope of the angular correlation fuction. The power spectrum rises above the power law at wavenumbers 0.08 h Mpc −1 ≤k≤0.2 h Mpc −1 . Systematic and random errors dominate the estimates of the power spectrum at wavenumbers smaller than 0.05 h Mpc −1
A TENS Based System for 2-Dimensional Balance Biofeedback Under Muscle Fatigue Condition

Many balance assist or training systems have been developed to improve postural control, however these have limitations such as being bulky or unable to provide 2-dimensional feedback. Furthermore, efficiency of the commonly used vibro-tactile feedback modality can be reduced due to muscle fatigue. Therefore, we suggest a transcutaneous electrical nerve stimulation (TENS) based electro-tactile biofeedback system to provide efficient balance biofeedback even under muscle fatigue condition. A feedback scheme based on Stevens’ power law is devised to provide 2-dimensional feedback using only four electrodes attached to the user’s leg. A pilot test involving the tracking of directions indicated by stimuli was done to select the algorithm appropriate for use in the directional perception test and the balance study. The perception, in 8 directions, of electro-tactile cues delivered using the developed scheme is compared with that of vibro-tactile cues under both normal and fatigued conditions. In addition, we have done standing balance experiments to verify the effectiveness of the developed balance biofeedback scheme. 20 healthy participants took part in these experiments that were conducted under two conditions. The perception results show that under the fatigued condition, the electro-tactile modality is more perceptible than the vibro-tactile modality. Results of the balance biofeedback experiment with no feedback, continuous stimulation with and without dead-zone and directional feedback conditions show that directional electro-tactile feedback helped the most in improving the users’ balance under normal and fatigued conditions. These promising results pave the way for future studies on the applications of this scheme for balance rehabilitation.
Stabilization of Acne Vulgaris-Associated Microbial Dysbiosis with 2% Supramolecular Salicylic Acid

Facial microbiota dysbiosis is an important factor in causing acne vulgaris. The present study aimed to analyze the effect of 2% Supramolecular Salicylic Acid (SSA) on acne-associated facial bacteria. In the current study, 30 acne vulgaris patients (treated with 2% SSA for eight weeks) and ten volunteers with no facial acne were selected. Samples from acne patients (before and after treatment) and volunteers (not treated) were analyzed via high throughput sequencing, Deblur algorithm, and R microbiome package. After treatment with 2% SSA, the total lesion count and global acne grading system (GAGS) score reduced significantly (p < 0.001). Metagenomic sequencing analysis revealed that the pre-treated acne group had low α and deviated β diversity compared to the control and post-treated acne groups. Due to the treatment with 2% SSA, α diversity index was increased and β diversity was stabilized significantly (p < 0.001). The relative abundance of bacterial genera in the pre-treated acne group was uneven and had a high proportion of Staphylococcus, Ralstonia, and Streptococcus. The proportion of these three genera was significantly decreased in the post-treated group, and overall bacteria genera distribution tends toward the healthy individual. It is concluded that 2% SSA normalizes the microbial communities associated with the skin.
Determinants of Corporate Tax Non-Compliance: Evidence from the Special Voluntary Disclosure Programme (SVDP)

This paper aims to provide empirical evidence on the determinants of corporate tax non-compliance in Malaysia based on secondary data collected during the Special Voluntary Disclosure Programme (SVDP) in 2018 and 2019. A total of 4,192 cases have been extracted from the integrated Case Management System (CMS) and Sistem Taksir Sendiri Syarikat (STSC) systems of the Inland Revenue Board Malaysia (IRBM) and analysed. The tax gap has been used as a proxy for tax non-compliance. The independent variables were corporate characteristics and strategies undertaken by companies for tax non-compliance. The research findings reveal that there is a significant positive relationship between firm size, nationality, real estate, understatement of sales, overstatement of purchases, and other strategies and corporate tax non-compliance. Construction and unallowable expenses have a significant negative relationship with corporate tax non-compliance. This study is the first study that investigates factors that could influence the corporate tax non-compliance based on SVDP data. This dataset is unique as it was extracted during the SVDP programme. The findings support on previous findings and provide further essential information to policymakers and tax authorities in designing tax audit guidelines, planning for tax amnesty initiative in future, providing training for their manpower, and formulating effective enforcement strategies.
Insensitivity of Steady-state Distributions of Generalized Semi-Markov Processes. Part II

A generalized semi-Markov process with speeds describes the fluctuation, in time, of the state of a certain general system involving, at any given time, one or more living components, whose residual lifetimes are being reduced at state-dependent speeds. Conditions are given for the stationary state distribution, when it exists, to depend only on the means of some of the lifetime distributions, not their exact shapes. This generalizes results of K6nig and Jansen, particularly to the infinite-state case.