Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct Numerical Simulation of a Free Particle-Laden Round Jet with Point-Particles: Turbulence Modulation

Direct numerical simulation method is used to investigate the small scale (d p < η/10) turbulence modulation for a spatially evolving free round jet. Because the turbulence modulation phenomena can not be accurately measured by experimental method, the turbulence modulations are poorly understood. The particle diameter in our simulation is smaller than the Kolmogorov length scale η (d p < η/10), and the point force method can be accurately used for the research of small scale turbulence modulation based strictly on the theory of point force method. The simulation uses an explicit coupling scheme between particles and the fluid, which considers two-way coupling between the particle and the fluid. The DNS results are compared with experimental data with equal Reynolds number (Re = 1700). The particles modulation on the fluid turbulence properties and coherent vortex structures are quantitatively given in our paper, and some new findings on the particles modulation are explicitly explained in this paper, which will further refine our understanding of intricate mechanism of small scale (d p < η/10) turbulence modulation for a spatially evolving free round jet.
Development of a point source integrating cavity absorption meter

The different existing techniques for measuring the absorption coefficient are presented with their advantages and disadvantages. The recurrent problem when measuring absorption appears to be the scattering of light by particles. A solution could be a point source integrating cavity absorption meter. In such an instrument, the sample is enclosed in a spherical cavity made with highly reflective walls. As a result the measurement is not affected by scattering. The development and first experiments made with such an absorption meter at the University of Plymouth are presented in this paper.
Metabolic Profile of Einkorn, Spelt, Emmer Ancient Wheat Species Sourdough Fermented with Strain of Lactiplantibacillus plantarum ATCC 8014

The continuous development of bakery products as well as the increased demands from consumers transform ancient grains into alternatives with high nutritional potential for modern wheat species. The present study, therefore, follows the changes that occur in the sourdough obtained from these vegetable matrices fermented by Lactiplantibacillus plantarum ATCC 8014 during a 24 h. period. The samples were analyzed in terms of cell growth dynamics, carbohydrate content, crude cellulose, minerals, organic acids, volatile compounds, and rheological properties. The results revealed significant microbial growth in all samples, with an average value of 9 log cfu/g but also a high accumulation of organic acids with the increase in the fermentation period. Lactic acid content ranged from 2.89 to 6.65 mg/g, while acetic acid recorded values between 0.51 and 1.1 mg/g. Regarding the content of simple sugars, maltose was converted into glucose, and fructose was used as an electron acceptor or carbon source. Cellulose content decreased as a result of the solubilization of soluble fibers into insoluble fibers under enzymatic action, with percentages of 3.8 to 9.5%. All sourdough samples had a high content of minerals; the highest of which—Ca (246 mg/kg), Zn (36 mg/kg), Mn (46 mg/kg), and Fe (19 mg/kg)—were recorded in the einkorn sourdough.
Negative Samples for Improving Object Detection—A Case Study in AI-Assisted Colonoscopy for Polyp Detection

Deep learning object-detection models are being successfully applied to develop computer-aided diagnosis systems for aiding polyp detection during colonoscopies. Here, we evidence the need to include negative samples for both (i) reducing false positives during the polyp-finding phase, by including images with artifacts that may confuse the detection models (e.g., medical instruments, water jets, feces, blood, excessive proximity of the camera to the colon wall, blurred images, etc.) that are usually not included in model development datasets, and (ii) correctly estimating a more realistic performance of the models. By retraining our previously developed YOLOv3-based detection model with a dataset that includes 15% of additional not-polyp images with a variety of artifacts, we were able to generally improve its F1 performance in our internal test datasets (from an average F1 of 0.869 to 0.893), which now include such type of images, as well as in four public datasets that include not-polyp images (from an average F1 of 0.695 to 0.722).
A Combination of Vision- and Sensor-Based Defect Classifications in Extrusion-Based Additive Manufacturing

Additive manufacturing, also known as 3D printing, has been facing the problem of inconsistent processing defects and product quality as a transformative technology, thus hindering its wide application in industry and other fields. In this context, machine learning (ML) algorithms are increasingly used for automatic classification of process data to achieve computer-aided defect detection. Specifically, in this paper, two data-driven classification prediction models are built by monitoring the sensing signals (temperature and vibration data) and interlayer images during the printing process, using the fused deposition model (FDM) as the base case, and the prediction results of the two machine learning models are fused for prediction. The experimental results show that by fusing the prediction results of the two models, the classification accuracy is significantly higher than the prediction results of a single model. These findings can benefit researchers studying FDM with the goal of producing systems that self-adjust online for quality assurance.
Permutation-Based Transmissions in Finite Blocklength Regime: Efficient and Effective Resource Utilization

In this paper, the concept of permutation-based transmissions is developed at the transport layer of short-packet communications, where the application-layer data is divided into two parts: one is conveyed by the permutation of various lengths in a group of packets, and the other is encapsulated into these various-length packets. The former part, referred to as permutation-conveyed data unit (PCDU), improves the goodput and reduces the latency. From a finite blocklength perspective, the maximal payload rate of permutation-based transmissions is formulated, based on which the goodput and latency are derived and obtained in analytical forms. Moreover, the spectral efficiency and energy efficiency are analysed. Illustrative numerical results on the performance and resource utilisation comparisons not only substantiate the advantages of our permutation-based transmissions over conventional transport-layer encapsulation schemes, but also provide useful tools and specifications for the PCDU design in short-packet communications.
Hybrid Metal-Organic Frameworks/Carbon Fibers Reinforcements for Additively Manufactured Composites

Additively manufactured (AM) composites based on short carbon fibers possess strength and stiffness far less than their continuous fiber counterparts due to the fiber’s small aspect ratio and inadequate interfaces with the epoxy matrix. This investigation presents a route for preparing hybrid reinforcements for AM that comprise short carbon fibers and nickel-based metal-organic frameworks (Ni-MOFs). The porous MOFs furnish the fibers with tremendous surface area. Additionally, the MOFs growth process is non-destructive to the fibers and easily scalable. This investigation also demonstrates the viability of using Ni-based MOFs as a catalyst for growing multi-walled carbon nanotubes (MWCNTs) on carbon fibers. The changes to the fiber were examined via electron microscopy, X-ray scattering techniques, and Fourier-transform infrared spectroscopy (FTIR). The thermal stabilities were probed by thermogravimetric analysis (TGA). Tensile and dynamic mechanical analysis (DMA) tests were utilized to explore the effect of MOFs on the mechanical properties of 3D-printed composites. Composites with MOFs exhibited improvements in stiffness and strength by 30.2% and 19.0%, respectively. The MOFs enhanced the damping parameter by 700%.
Recent Advances in Tick Antigen Discovery and Anti-Tick Vaccine Development

Ticks can seriously affect human and animal health around the globe, causing significant economic losses each year. Chemical acaricides are widely used to control ticks, which negatively impact the environment and result in the emergence of acaricide-resistant tick populations. A vaccine is considered as one of the best alternative approaches to control ticks and tick-borne diseases, as it is less expensive and more effective than chemical controls. Many antigen-based vaccines have been developed as a result of current advances in transcriptomics, genomics, and proteomic techniques. A few of these (e.g., Gavac® and TickGARD®) are commercially available and are commonly used in different countries. Furthermore, a significant number of novel antigens are being investigated with the perspective of developing new anti-tick vaccines. However, more research is required to develop new and more efficient antigen-based vaccines, including on assessing the efficiency of various epitopes against different tick species to confirm their cross-reactivity and their high immunogenicity. In this review, we discuss the recent advancements in the development of antigen-based vaccines (traditional and RNA-based) and provide a brief overview of recent discoveries of novel antigens, along with their sources, characteristics, and the methods used to test their efficiency.
Magnetic dichroism at the giant dipole resonance of Fe and Mn via time-dependent density-functional theory

The polarization-resolved photoabsorption cross section has been calculated in the vicinity of the giant dipole resonances of Fe (45-65 eV) and Mn (45-60 eV) using the relativistic time-dependent local spin-density approximation. The method accounts for the largest features in the unpolarized experimental total cross sections, after Gaussian broadening is applied; however, minor features are not given correctly. Both circular and linear dichroic spectra are presented, however experimental data are not yet available.
Consumers choice of small independent specialty stores in shopping centers during weekday extended trading hours: A qualitative study

Abstract This study explored the behavioral dynamics that is responsible for the success of the small independent specialty retailers in a shopping center during weekday extended trading hours. Drawing on literature from different areas, consumers’ shopping experiences, browsing patterns and factors influencing browsing activities in small independent specialty stores in a shopping center during weekday extended trading hours was investigated. The study was carried out in Brisbane, Australia. Two focus groups with consumers and a personal interview with an expert was performed. This research found consumers were usually goal oriented during weekday late evening trading hours and they would usually engage in browsing in-stores only when they require customer assistance. This research was also able to understand and establish the behavioural dynamics that can determine the performance of the small independent specialty stores during extended trading hours. Overall, this research suggests that the small independent specialty stores are unlikely to experience an increase in sales or attract more customers by extending the trading hours. This study makes an important step in understanding consumers demand for small independent specialty stores in categorized shopping centers during the extended trading hours. The conceptualization and findings of this research contribute to two areas of research: consumer spatial behavior and consumer information search in small independent specialty stores in a shopping center during weekday extended trading hours.
Revisiting Host-Pathogen Interactions in Cystic Fibrosis Lungs in the Era of CFTR Modulators

Cystic fibrosis transmembrane conductance regulator (CFTR) modulators, a new series of therapeutics that correct and potentiate some classes of mutations of the CFTR, have provided a great therapeutic advantage to people with cystic fibrosis (pwCF). The main hindrances of the present CFTR modulators are related to their limitations in reducing chronic lung bacterial infection and inflammation, the main causes of pulmonary tissue damage and progressive respiratory insufficiency, particularly in adults with CF. Here, the most debated issues of the pulmonary bacterial infection and inflammatory processes in pwCF are revisited. Special attention is given to the mechanisms favoring the bacterial infection of pwCF, the progressive adaptation of Pseudomonas aeruginosa and its interplay with Staphylococcus aureus, the cross-talk among bacteria, the bronchial epithelial cells and the phagocytes of the host immune defenses. The most recent findings of the effect of CFTR modulators on bacterial infection and the inflammatory process are also presented to provide critical hints towards the identification of relevant therapeutic targets to overcome the respiratory pathology of pwCF.
Mixture of Two LindleyProbability Models And Application In Reliability

Mixture probability models are developed in general from Uni variate Probability functions (say) g 1 ( x ) and g 2 ( x ) . The mixture of these two is defined by f ( x )  p . g 1 ( x )  (1  p ) g 2 ( x ) where “p” is the mixing ratio. The function that we have in the present paper is the Mixture of two Lindley probability distributions, each of which is having a different parameter. Lindley models are also useful for data showing decaying trends. The properties of Lindley probability distribution that have been shown are Mathematical Expectation, Second Moment, and the Distribution Function. An application of the Mixture Model which has been derived in the present research , has been applied to the Reliability function , in a two component system , when the components are connected in series. The Reliability of the discussed system is compared with reliability values when the Lindley probabilities in the same system , are independent.
MULTI-REFRACTION WITH SAME POLARIZATION STATE IN TWO DIMENSIONAL TRIANGULAR PHOTONIC CRYSTALS

Multi-refraction efiects with one polarization in a two- dimensional triangular photonic crystal (PhC) were systematically studied by theoretical analysis and numerical simulation. The more complicated refraction behaviors can be excited in the higher band regions based on the intricate undulation of one band or the overlap of difierent bands. A novel non-handedness efiect is proposed for the flrst time with group velocity perpendicular to phase velocity. Furthermore, triple refraction phenomena and special collimation efiects of symmetrical positive-negative refraction with the loose incident conditions have been found in difierent band regions of this PhC. These unique features will provide us with more understanding of electromagnetic wave propagation in PhCs and give important guideline for the design of new type optical devices.
Associations of migraines with suicide ideation or attempts: A meta-analysis

Objective Whether migraine is associated with a higher risk of suicide ideation and/or attempts remains controversial. Therefore, we aimed to evaluate these potential associations in migraine patients by performing a meta-analysis of previously published data. Methods We searched for studies published up to 31 June 2022 that compared the risk of suicide ideation/attempt in migraineurs and non-migraineurs in PubMed, EMBASE, and Web of Science databases. Sixteen studies fulfilled the eligibility criteria. We applied Random-effects models to calculate pooled adjusted odds ratios (AORs) and 95% confidence intervals (CIs) in patients with migraine. Results Migraine patients were at a significantly increased risk of suicide ideation (AOR 1.33, 95% CI 1.15–1.54) and suicide attempts (AOR 1.70, 95% CI 1.42–2.03). The increase in risk may be greater in adults (>19 years) than in younger individuals. Conclusion The available evidence indicates a significant association of migraines with suicide ideation and attempts. Future work should confirm and extend these findings, as well as explore whether they are affected by ethnicity or geography.
Predicting work engagement among young adult cancer survivors: A moderated mediation model

Introduction Early research on cancer survivors was focused on exploring cancer treatments. More recently, attention has shifted to cancer survivorship research, focusing on cancer survivors as individual persons, including the multiple facets of survivors' quality of life but is inapplicable in the context of work-related role played in the young adult cancer survivors' lives. However, in recent studies on the outcomes of long-term survivorship, some of the main areas of cancer survivorship research revolves around employment issues of young adult cancer survivors. In the present study, the focus is given on the role of workplace spirituality as a mediator on the association of employee resilience and workplace social support on work engagement in a Malaysian setting, taking into consideration gender and age differences. Methods Using a quantitative research paradigm, data were collected from 270 respondents at Pediatric Institute Kuala Lumpur Hospital. Data were analyzed using descriptive statistics and the Partial Least Square-Structural Equation Model (PLS-SEM) to test the direct, indirect, and mediation effects. Results and discussion The findings revealed that workplace spirituality did mediate the influence of employee resilience and workplace social support on work engagement. The findings also indicated that gender and age moderated the association of employee resilience and work engagement via workplace spirituality.
Multi-Depth Computer-Generated Hologram Based on Stochastic Gradient Descent Algorithm with Weighted Complex Loss Function and Masked Diffraction

In this paper, we propose a method to generate multi-depth phase-only holograms using stochastic gradient descent (SGD) algorithm with weighted complex loss function and masked multi-layer diffraction. The 3D scene can be represented by a combination of layers in different depths. In the wave propagation procedure of multiple layers in different depths, the complex amplitude of layers in different depths will gradually diffuse and produce occlusion at another layer. To solve this occlusion problem, a mask is used in the process of layers diffracting. Whether it is forward wave propagation or backward wave propagation of layers, the mask can reduce the occlusion problem between different layers. Otherwise, weighted complex loss function is implemented in the gradient descent optimization process, which analyzes the real part, the imaginary part, and the amplitude part of the focus region between the reconstructed images of the hologram and the target images. The weight parameter is used to adjust the ratio of the amplitude loss of the focus region in the whole loss function. The weight amplitude loss part in weighted complex loss function can decrease the interference of the focus region from the defocus region. The simulations and experiments have validated the effectiveness of the proposed method.
A Machine Learning Integrated 5.8-GHz Continuous-Wave Radar for Honeybee Monitoring and Behavior Classification

A 5.8-GHz continuous-wave (CW) radar was developed and integrated on a compact printed circuit board (PCB) for near-hive monitoring of honeybees. It supported noninvasive detection of free-flying honeybees at 2 m and micro-Doppler extraction of bee wingbeat signatures at a closer range using both a double-balanced mixer and an in-phase/quadrature (IQ) mixer. An original technique combining full-wave simulations and Doppler-radar monitoring of pendulum motion was used for: radar calibration through spherical targets of different material and size; precise extraction of bee radar cross Section (RCS) at 5.8 GHz; and estimation of detection range enhancement through partial silver coating of targets. Finally, the CW radar was integrated with machine learning (ML) to allow automated classification of incoming, outgoing, and hovering honeybees. Different ML approaches were tested, where the highest accuracy of 93.37% was found in ternary classification via support vector machine acting on line spectral frequencies.
Analyzing oriented textures through phase portraits

An attempt is made to develop a solution for signal-to-symbol transformation in the domain of flowlike or oriented texture. The geometric theory of differential equations is used to derive a symbol set based on the visual appearance of phase portraits. This theory provides a technique for describing textures both qualitatively and quantitatively. An attractive feature of this symbol set is that it is domain independent and makes no assumptions about the kind of texture that may be present. The computational framework for starting with a given oriented texture is provided, and its symbolic representation is derived. This is based on computing the orientation field for the texture and then using a nonlinear least-squares technique over successive windows to determine the changing spatial behavior of the texture. Results of the application of this technique to real texture images are presented. <<ETX>>
Characteristics, Management, and Outcomes of Community-Acquired Pneumonia due to Respiratory Syncytial Virus: A Retrospective Study

Background Respiratory syncytial virus (RSV), a well-known cause of bronchiolitis in children, can cause community-acquired pneumonia (CAP) in adults, but this condition is not well studied. Hence, we described the characteristics and outcomes of patients hospitalized for CAP due to RSV. Methods This was a retrospective study of patients admitted to a tertiary-care hospital between 2016 and 2019 with CAP due to RSV diagnosed by a respiratory multiplex PCR within 48 hours of admission. We compared patients who required ICU admission to those who did not. Results Eighty adult patients were hospitalized with CAP due to RSV (median age 69.0 years, hypertension 65.0%, diabetes 58.8%, chronic respiratory disease 52.5%, and immunosuppression 17.5%); 19 (23.8%) patients required ICU admission. The median pneumonia severity index score was 120.5 (140.0 for ICU and 102.0 for non-ICU patients; p = 0.09). Bacterial coinfection was rare (10.0%). Patients who required ICU admission had more hypotension (systolic blood pressure < 90 mmHg) and a higher prevalence of bilateral infiltrates on chest X-ray (CXR) (89.5% versus 32.7%; p < 0.001). Systemic corticosteroids were used in 57.3% of patients (median initial dose was 40 mg of prednisone equivalent) with ICU patients receiving a higher dose compared to non-ICU patients (p = 0.02). Most (68.4%) ICU patients received mechanical ventilation (median duration of 4 days). The overall hospital mortality was 8.8% (higher for ICU patients: 31.6% versus 1.6%, p < 0.001). Conclusions Most patients with CAP due to RSV were elderly and had significant comorbidities. ICU admission was required in almost one in four patients and was associated with higher mortality.
State estimation in discrete m-D systems

In this study observers and stochastic state estimation for m - D systems are considered. The analysis uses a wave advance process model in transporting the existing 1-D results to the m -D setting. A constrained minimization technique is used to compute the optimal state estimator which preserves quarter plane causality. The optimal state estimator, without the quarter plane causality constraint, is also determined. A comparison then yields insight into the tradeoff between quarter plane causality and estimator performance.