Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness Evaluation of Optical Illusion Deceleration Markings for a V-Shaped Undersea Tunnel Based on the Set Pair Analysis Method and the Technique for Order Preference by Similarity to Ideal Solution Theory

To improve traffic safety in undersea tunnels, the speed control effect of optical illusion deceleration markings (OIDMs) in V-shaped undersea tunnels and their applicability to drivers were explored. In this study, UC-Win/Road software was used to build a simulation scenario, and the V-shaped Jiaozhou Bay undersea tunnel in Qingdao, China, was selected as the simulated road section. Four kinds of OIDMs were selected as the research objects. According to the physiological and psychological response characteristics of drivers to the visual recognition process of OIDMs and vehicle driving parameters, three primary and six secondary evaluation indices were identified. The analytic hierarchy process-entropy weight method was applied to assign weights to each evaluation index in combination, and a comprehensive evaluation model based on the set pair analysis method and the technique for order preference by similarity to ideal solution was constructed to comprehensively evaluate the effectiveness of the OIDMs based on the ternary coefficient and the comprehensive evaluation index. To verify the accuracy of the model, the data of the three secondary evaluation indicators with larger weight coefficients were statistically analyzed, and the results showed that the results of the statistical analysis of the data were consistent with the results of the model test. In the entrance section of the tunnel, the combination of white inverted fishbone deceleration markings and red warning pavement has the highest comprehensive evaluation index of γA1 = 0.9611. In the downhill section of the tunnel, the white variable-spacing inverted fishbone deceleration markings have the highest comprehensive evaluation index, γB1 = 0.9644.
A Review on Contact and Collision Methods for Multi-Body Hydrodynamic Problems in Complex Flows

Modeling and direct numerical simulation of particle-laden ﬂows have a tremendous variety of applications in science and engineering across a vast spectrum of scales from pollution dispersion in the atmosphere, to ﬂuidization in the combustion process, to aerosol deposition in spray medication, along with many others. Due to their strongly nonlinear and multiscale nature, the above complex phenomena still raise a very steep challenge to the most computational methods. In this review, we provide comprehensive coverage of multibody hydrodynamic (MBH) problems focusing on particulate suspensions in complex ﬂuidic systems that have been simulated using hybrid Eulerian-Lagrangian particulate ﬂow models. Among these hybrid models, the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) provides mathematically simple and computationally-eﬃcient algorithms for solid-ﬂuid hydrodynamic interactions in MBH simulations. This paper elaborates on the mathematical framework, applicability, and limitations of various ‘simple to complex’ representations of close-contact interparticle interactions and collision methods, including short-range interparticle and particle-wall steric interactions, spring and lubrication forces, normal and oblique collisions, and mesoscale molecular models for deformable particle collisions based on hard-sphere and soft-sphere models in MBH models to simulate settling or ﬂow of nonuniform particles of diﬀerent geometric shapes and sizes in diverse ﬂuidic systems.
Application of High-Performance Liquid Chromatography with Fluorescence Detection for Non-Polar Heterocyclic Aromatic Amines and Acridine Derivatives Determination in Pork Loin Roasted in a Roasting Bag

Heat treatment of meat can lead to the formation of carcinogenic organic compounds. The influence of dried fruits on the formation of non-polar heterocyclic aromatic amines (carbolines) and nitrogen derivatives of polycyclic aromatic hydrocarbons (azaarenes) in roasted pork loin was elucidated. Two hundred grams of fruit per 1 kg of meat were used as stuffing. Carbolines, derivatives of pyridoimidazole and pyridoindole, and azaarenes (benzoacridines and dibenzoacridines) were determined by means of high-performance liquid chromatography with fluorescence detection. The total concentration of six δ-, γ- and α-carbolines in roasted pork loin was 1.3 ng/g. This content decreased by 64%, 58%, and 54% in pork loin stuffed with prunes, apricots, and cranberries, respectively. Concentrations of β-carbolines (harmane and norharmane) increased under the influence of added fruits. The norharmane content increased the most, from 2.2 ng/g in the control sample to 12.3 ng/g in meat prepared with cranberries. The harmane content increased from 1.0 ng/g to 3.6 ng/g in meat with prunes. The total concentration of azaarenes (two benzoacridines and dibenzo[a,c]acridine), which was close to 0.1 ng/g, decreased in dishes with prunes and apricots by 54% and 12%, respectively. Azaarenes were not found in samples of meat stuffed with cranberries.
Approximations for multidimensional discrete scan statistics

In this thesis, we derive accurate approximations and error bounds for the probability distribution of the multidimensional discrete scan statistics. We start by improving some existing results concerning the estimation of the distribution of extremes of 1-dependent stationary sequences of random variables, both in terms of range of applicability and sharpness of the error bound. These estimates play the key role in the approximation process of the multidimensional discrete scan statistics distribution. The presented methodology has two main advantages over the existing ones found in the literature: first, beside the approximation formula, an error bound is also established and second, the approximation does not depend on the common distribution of the observations. For the underlying random field under which the scan process is evaluated, we consider two models: the classical model, of independent and identically distributed observations and a dependent framework, where the observations are generated by a block-factor. In the i.i. d. case, in order to illustrate the accuracy of our results, we consider the particular settings of one, two and three dimensions. A simulation study is conducted where we compare our estimate with other approximations and inequalities derived in the literature. The numerical values are efficiently obtained via an importance sampling algorithm discussed in detail in the text. Finally, we consider a block-factor model for the underlying random field, which consists of dependent data and we show how to extend the approximation methodology to this case. Several examples in one and two dimensions are investigated. The numerical applications accompanying these examples show the accuracy of our approximation. All the methods presented in this thesis leaded to a Graphical User Interface (GUI) software, implemented in Matlab®.
Magnetic Fields in Star-Forming Filaments in Different Environments

Cold, dense filaments, some appearing as infrared dark clouds, are the nurseries of stars. Tremendous progress in terms of temperature, density distribution and gas kinematics has been made in understanding the nature of these filaments. However, very little is known about the role played by magnetic fields in the evolution of these filaments. Here, I summarize the recent observational efforts and ongoing projects (POLSTAR survey) in this direction.
Does Human Papillomavirus Infection Influence the Frequency and Severity of Nutritional Disorders in Head and Neck Cancer?

Background: About 87% of head and neck cancer (HNC) patients (mostly oropharyngeal cancer—OPC) are infected with human papillomavirus (HPV). Recent studies have demonstrated a significant correlation between HPV infection and nutritional disorders in HNC patients. Therefore, we formed a hypothesis that nutritional disorders or their severity in HNC patients may be associated with the occurrence of HPV infection due to known molecular differences in involved tissue. This literature review aimed to evaluate the influence of HPV infection on the occurrence and severity of nutritional disorders in HNC patients. Materials and Methods: The PubMed database was used to search papers with the keywords “HPV”, “HNC”, and “nutritional disorders” in different variants and combinations. Conclusions: The data available in the discussed papers indicate, among other things, that HPV−positive patients may be at higher risk of malnutrition, critical weight loss, and necessity for gastrostomy after radiotherapy or chemoradiotherapy (C-RT). It should be highlighted that despite some studies demonstrating positive results, currently available data regarding the influence of HPV infection on the occurrence and severity of nutritional disorders in HNC remain limited and inconclusive, and thus further research on this issue is warranted.
Supervised detection of Alternaria solani on ultra-high-resolution modified RGB UAV images

Potato cultivation is regularly affected by Alternaria solani, a destructive foliar pathogen causing early blight, a premature defoliation of potato plants resulting in yield losses. Currently, Alternaria is treated through preventive application of chemical crop protection productions, following warnings based on weather predictions and visual observations. Automatic detection could make the mapping of early blight more accurate, reducing production losses and application of crop protection products. Current research explores the potential of deep learning of high resolution imagery within precision agriculture, mainly using supervised learning. However, available datasets are often limited in size and variation, which reduces the robustness of the developed models. Here, we present a convolutional network to detect Alternaria and evaluate the influence of sampling size, sampling balance and sampling accuracy on the model performance. These analyses are based on ultra-high-resolution datasets of modified RGB cameras obtained with unmanned aerial vehicles (UAV) and collected over experimental in-field Alternaria trials. By using this varied dataset instead of a single-time dataset, higher accuracies are achieved. The method is relatively robust for imbalances of the training dataset. Further, we show that labeling quality plays a role, but that an error of up of to 20% of labeling is acceptable for good results. In conclusion, extra variability leads to more robust disease detection, desirable for in-field application.
Impact of Online Teaching Capacity Building Programmes on Online Teaching: A Case of University of Kabianga Kenya

The Covid-19 pandemic disrupted educational programmes globally, Kenya being not an exception. Most universities in Kenya closed down before slowly shifting to online teaching shrouded with challenges, partly due to inadequate staff expertise in online teaching. There was therefore a need for capacity building on online teaching to build resilience and support the achievement of Sustainable Development Goal 4 amidst the pandemic. The University of Kabianga initiated programmes to train the teaching staff on online education. The staff were also encouraged to enrol for online teaching Massive Open Online Courses (MOOCs) offered locally and internationally. This study sought to assess the lecturers’ perceptions of the impact of these online teaching capacity building programmes in terms of relevance, effectiveness, efficiency, and sustainability. The study is underpinned by the Impact Evaluation Model and Mezirow's transformative learning theory. Descriptive-participatory research design through an online survey was used for data collection and the results revealed that although the programmes were considered relevant, most lecturers were averse to the interventions and recommends further structured training.
Experimental test of an entropic measurement uncertainty relation for arbitrary qubit observables

The uncertainty principle is an important tenet and active field of research in quantum physics. Information-theoretic uncertainty relations, formulated using entropies, provide one approach to quantifying the extent to which two non-commuting observables can be jointly measured. Recent theoretical analysis predicts that general quantum measurements are necessary to saturate some such uncertainty relations and thereby overcome certain limitations of projective measurements. Here, we experimentally test a tight information-theoretic measurement uncertainty relation with neutron spin- 1 / 2 qubits. The noise associated to the measurement of an observable is defined via conditional Shannon entropies and a tradeoff relation between the noises for two arbitrary spin observables is demonstrated. The optimal bound of this tradeoff is experimentally obtained for various non-commuting spin observables. For some of these observables this lower bound can be reached with projective measurements, but we observe that, in other cases, the tradeoff is only saturated by general quantum measurements (i.e. positive-operator valued measures) as predicted theoretically. These results showcase experimentally the advantage obtainable by general quantum measurements over projective measurements when probing certain uncertainty relations.
Molecular Mechanisms Underlying the Effects of Bimin Kang Mixture on Allergic Rhinitis: Network Pharmacology and RNA Sequencing Analysis

Background Allergic rhinitis (AR) is a highly prevalent chronic inflammatory disease of the respiratory tract. Previous studies have demonstrated that Bimin Kang Mixture (BMK) is effective in alleviating AR symptoms and reducing the secretion of inflammatory factors and mucin; however, the precise mechanisms underlying these effects remain unclear. Methods We built target networks for each medication component using a network pharmacology technique and used RNA-seq transcriptome analysis to screen differentially expressed genes (DEGs) for AR patients and control groups. The overlapping targets in the two groups were assessed using PPI networks, GO, and KEGG enrichment analyses. The binding ability of essential components to dock with hub target genes was investigated using molecular docking. Finally, we demonstrate how BMK can treat AR by regulating the NF-κB signaling pathway through animal experiments. Results Effective targets from network pharmacology were combined with DEGs from RNA-seq, with 20 intersections as key target genes. The construction of the PPI network finally identified 5 hub target genes, and all hub target genes were in the NF-κB signaling pathway. Molecular docking suggests that citric acid, deoxyandrographolide, quercetin, luteolin, and kaempferol are structurally stable and can spontaneously attach to IL-1β, CXCL2, CXCL8, CCL20, and PTGS2 receptors. Animal experiments have shown that BMK inhibits NF-κB transcription factor activation, reduces the expression of proinflammatory cytokines and chemokines IL-1β, CXCL2, IL-8, and COX-2, and exerts anti-inflammatory and anti-allergic effects. Conclusion BMK by regulating the NF-κB signaling pathway improves inflammatory cell infiltration, regulates mucosal immune balance, and reduces airway hypersensitivity. These findings provide theoretical support for the clinical efficacy of BMK for AR treatment.
Quinoa Snack Production at an Industrial Level: Effect of Extrusion and Baking on Digestibility, Bioactive, Rheological, and Physical Properties

This research aimed to produce gluten-free snacks on a pilot scale from quinoa flour. These snacks experienced an extrusion process, followed by baking. The effects of these technological processes on carbohydrate and protein digestibility, extractable phenolic compounds (EPP), hydrolyzable phenolic compounds (HPP), antioxidant capacity, and physical properties were evaluated in raw quinoa flour and extruded snacks. Extrusion increased digestible starch (RDS) from 7.33 g/100 g bs to 77.33 g /100 g bs. Resistant starch (RS) showed a variation of 2 g/100 g bs. It is noteworthy that protein digestibility increased up to 94.58 g/100 bs after extrusion and baking. These processes increased HPP content, while EPP and carotenoid content decreased. The samples showed significant differences (p < 0.05) in the antioxidant properties determined through the DPPH and ABTS methods. Values of 19.72 ± 0.81 µmol T/g were observed in snacks and 13.16 ± 0.2 µmol T/g in raw flour, but a reduction of up to 16.10 ± 0.68 µmol T/g was observed during baking. The baking process reduced the work of crispness (Wcr) from 0.79 to 0.23 N.mm, while the saturation (C*) was higher in baked ones, showing higher color intensity. The baking process did not influence the viscosity profile. The results in this study respond to the growing interest of the food industry to satisfy consumer demand for new, healthy, and expanded gluten-free snacks with bioactive compounds.
Intensive care therapy during the pandemic in 2020 and beyond: Mnemonics can help

In a busy working environment, with a shortage of healthcare workers and increased workloads since the beginning of the COVID-19 pandemic, the implementation of an easy-to-remember mnemonic can significantly help anesthesiologists and clinicians in conducting intensive therapy. One of the first mnemonics in critical care therapy was implemented by Jean-Louis Vincent in 2005. FAST HUG concept reminds clinicians of crucial moments in therapy - nutritional support(F-feeding), analgesia and sedation (A - analgesia, S - sedation), thrombosis prophylaxis (T - thrombolytic prophylaxis), head elevation in bed (H - head of the elevated bed), antiulcer therapy (U - stress ulcer prevention) and glycemic control (G - glucose control). This acronym has been modified and tested in several studies over the years for the treatment of different patient types. This concept is widely utilized in intensive care units, it is characterized with easy implementation, and proved to be useful in ventilator-associated pneumonia prevention. Therapy of critically ill patients with COVID-19 is based on elements of general intensive care therapy with some specific therapeutic guidelines. With the intention to ease and improve therapy of patients with COVID-19 in intensive care units, a new and comprehensive acronym is proposed: One Fast Hug Bids COVID.
Recent Progress of Electrode Architecture for MXene/MoS2 Supercapacitor: Preparation Methods and Characterizations

Since their discovery, MXenes have conferred various intriguing features because of their distinctive structures. Focus has been placed on using MXenes in electrochemical energy storage including a supercapacitor showing significant and promising development. However, like other 2D materials, MXene layers unavoidably experience stacking agglomeration because of its great van der Waals forces, which causes a significant loss of electrochemically active sites. With the help of MoS2, a better MXene-based electrodecan is planned to fabricate supercapacitors with the remarkable electrochemical performance. The synthesis of MXene/MoS2 and the ground effects of supercapacitors are currently being analysed by many researchers internationally. The performance of commercial supercapacitors might be improved via electrode architecture. This analysis will support the design of MXene and MoS2 hybrid electrodes for highly effective supercapacitors. Improved electrode capacitance, voltage window and energy density are discussed in this literature study. With a focus on the most recent electrochemical performance of both MXene and MoS2-based electrodes and devices, this review summarises recent developments in materials synthesis and its characterisation. It also helps to identify the difficulties and fresh possibilities MXenes MoS2 and its hybrid heterostructure in this developing field of energy storage. Future choices for constructing supercapacitors will benefit from this review. This review examines the newest developments in MXene/MoS2 supercapacitors, primarily focusing on compiling literature from 2017 through 2022. This review also presents an overview of the design (structures), recent developments, and challenges of the emerging electrode materials, with thoughts on how well such materials function electrochemically in supercapacitors.
Relationship between Baseline [18F]FDG PET/CT Semiquantitative Parameters and BRCA Mutational Status and Their Prognostic Role in Patients with Invasive Ductal Breast Carcinoma

Aim: To assess the relationship between [18F]FDG PET/CT, breast cancer gene (BRCA) status, and their prognostic role in patients with ductal breast cancer (DBC). Methods: Forty-one women were included. PET/CT semiquantitative parameters such as standardized uptake value (SUV) body weight max (SUVmax), SUV body weight mean (SUVmean), SUV lean body mass (SUVlbm), SUV body surface area (SUVbsa), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ratio SUVmax/blood-pool (S-BP), and ratio SUVmax/liver (S-L) were also extracted. The relationship between these parameters, BRCA, and other clinicopathological features were evaluated. Kaplan–Meier, univariate, and multivariate analyses were performed to find independent prognosticators for progression free (PFS) and overall survival (OS). Results: Significant positive correlations between BRCA status and SUVmax (p-value 0.025), SUVlbm (p-value 0.016), and SUVbsa (p-value 0.018) were reported. Mean PFS was 53.90 months with relapse/progression of disease occurring in nine (22.0%) patients; mean OS was 57.48 months with death occurring in two (4.9%) patients. Survival curves revealed TLG, MTV, and BRCA status as prognosticator for PFS; BRCA was also a prognosticator for OS. Univariate and multivariate analyses did not confirm such insights. Conclusion: We reported a correlation between some PET/CT parameters and BRCA status; some insights on their prognostic role have been underlined.
Ultrashort magnetic impulses driven by coherent control with vector beams

We introduce a new technique for the generation of magnetic impulses. This technique is based on coherent control of electrical currents using cylindrical laser beams with azimuthal polarization. When used to ionize a medium, in this case atomic hydrogen is considered, an azimuthal current impulse is driven. The spatial distribution of this current bears close resemblance to that of a solenoid, and produces a magnetic field impulse. The excitation and relaxation dynamics of this current temporally confine the resulting magnetic field to a Tesla-scale, terahertz bandwidth impulse. Importantly, the magnetic fields are spatially isolated from electric fields. This all-optical approach will enable ultrafast time-domain spectroscopy of magnetic phenomena.
Quantum field theory of X-cube fracton topological order and robust degeneracy from geometry

We propose a quantum field theory description of the X-cube model of fracton topological order. The field theory is not (and cannot be) a topological quantum field theory (TQFT), since unlike the X-cube model, TQFTs are invariant (i.e. symmetric) under continuous spacetime transformations. However, the theory is instead invariant under a certain subgroup of the conformal group. We describe how braiding statistics and ground state degeneracy are reproduced by the field theory, and how the the X-cube Hamiltonian and field theory can be minimally coupled to matter fields. We also show that even on a manifold with trivial topology, spatial curvature can induce a ground state degeneracy that is stable to arbitrary local perturbations! Our formalism may allow for the description of other fracton field theories, where the only necessary input is an equation of motion for a charge density.