Miracle-dz/UniFAR-FTUs huggingface dataset:
Fresh Produce as a Potential Vector and Reservoir for Human Bacterial Pathogens: Revealing the Ambiguity of Interaction and Transmission

The consumer demand for fresh produce (vegetables and fruits) has considerably increased since the 1980s for more nutritious foods and healthier life practices, particularly in developed countries. Currently, several foodborne outbreaks have been linked to fresh produce. The global rise in fresh produce associated with human infections may be due to the use of wastewater or any contaminated water for the cultivation of fruits and vegetables, the firm attachment of the foodborne pathogens on the plant surface, and the internalization of these agents deep inside the tissue of the plant, poor disinfection practices and human consumption of raw fresh produce. Several investigations have been established related to the human microbial pathogens (HMPs) interaction, their internalization, and survival on/within plant tissue. Previous studies have displayed that HMPs are comprised of several cellular constituents to attach and adapt to the plant’s intracellular niches. In addition, there are several plant-associated factors, such as surface morphology, nutrient content, and plant–HMP interactions, that determine the internalization and subsequent transmission to humans. Based on documented findings, the internalized HMPs are not susceptible to sanitation or decontaminants applied on the surface of the fresh produce. Therefore, the contamination of fresh produce by HMPs could pose significant food safety hazards. This review provides a comprehensive overview of the interaction between fresh produce and HMPs and reveals the ambiguity of interaction and transmission of the agents to humans.
Oblique plane microscopy for 3D, multi-color, eight-day time-lapse imaging of genetically heterogeneous breast cancer spheroids in 384-well plates with quantitative 3D analysis

Oblique plane microscopy (OPM) is a light-sheet microscopy technique that illuminates a tilted plane of a specimen and collects the fluorescence with the same high NA objective. Here, we apply OPM with stage-scanned image volume acquisition to perform high-content, 3D time-lapse imaging of up to 180 breast cancer spheroids over eight days every eight hours. Each spheroid comprises a combination of one to three different cell populations, each co-expressing a unique oncogene-fluorescent protein pair. We trained the image segmentation tool Cellpose to segment nuclei in the resulting data in order to measure integrated fluorescence intensity, nuclear size, and nuclear count for each of the different oncogenes to quantify competition between mutations.
Rozmyty regulator stanu układu dwumasowego

Application of control methods based on state vector leads to precise tracking of reference signal. However, the parametric or measurement disturbance definitely make it difficult to maintain the correct operation of the system. Therefore, in this paper, implementation of an additional fuzzy element is proposed. It can recalculate, using information about the speed error, the coefficients in the feedback paths. Then, shape of the state variables and the dynamics of the system are forced properly. In the design process, the metaheuristic algorithm - S ymbiotic O rganisms S earch (SOS) - was used. The electrical drive contains elastic shaft. The results of the simulations confirm the correctness of the analyzed method. Moreover, the experimental tests were performed (with the dSPACE 1103 card, the system contains two DC motor with 0.5kW). ( Fuzzy state controller applied for two-mass system )
Bootstrap confidence intervals for simulation outputs

Confidence intervals obtained by bootstrap methods and normal approximation are compared, based on output data from terminating and steady-state simulations. Bootstrap intervals are equal or better than normal approximation intervals in actual probability coverages. Furthermore, bootstrap methods capture the skewness in the distribution of outputs and, therefore, are more desirable than normal approximation.
Single machine parallel-batching scheduling problem with fuzzy due-date and fuzzy precedence relation

A problem of single machine parallel-batching problem with fuzzy due-date and fuzzy precedence relation is investigated. Each job has a positive processing time. Set-up times are assumed to be identical for all batches. All batch sizes cannot exceed a common upper bound. The length of a batch is equal to the largest processing time among all jobs in the batch. Fuzzy due-date denotes the degree of satisfaction with respect to completion times of jobs. Fuzzy precedence constraint expresses the satisfaction level about precedence between two jobs. The objective is to minimise maximum completion time, maximise the minimum value of desirability of the fuzzy due-date and the minimum value of desirability of the fuzzy precedence. First, we propose a fuzzy due-date and ordinary precedence model, which maximises the minimum satisfaction degree of fuzzy due-date. An efficient iterative algorithm based on Procedure HL is designed. On that basis, another efficient algorithm to seek non-dominated solution is presented for the main problem in this paper. The non-dominated solution is defined to be consists of batch size, batch number and allocation of jobs to batches. The whole solution procedure needs at most computational time. Finally, we illustrate the procedure with a numerical example.
Arma neuron networks for modeling nonlinear dynamical systems

A new neuronal structure, the ARMA neuron, is proposed here. These new neurons are designed for modeling nonlinear dynamics often encountered in chemical engineering processes. They are an extension of standard neurons which are used for static process modeling. These new neurons contain internal input/output dynamic structure and can model dynamic non-linearities in a flexible manner. A nonlinear output transformation is used here as opposed to a linear version used earlier (Krishnapura and Jutan, 1993). New algorithms for training networks comprised of the new ARMA neurons are developed using the backpropagation approach. The ARMA neurons are used to model both simulated and experimental nonlinear dynamic processes, including an industrial fluidized bed reactor. On propose ici une nouvelle structure neuronale, le neurone ARMA. Ces nouveaux neurones sont concus pour la modelisation des dynamiques non lineaires souvent rencontrees dans les procedes de genie chimique. Ils constituent une extension des neurones standards utilises dans la modelisation des procedes statiques. Ces nouveaux neurones contiennent une structure dynamique interne entree/sortie et peuvent modeliser des non-linearites dynamiques de maniere flexible. On utilise une transformation de sortie non lineaire ici par opposition a une version lineaire utilisee anterieurement (Krishnapura et Jutan, 1993). De nouveaux algorithmes pour entrainer des reseaux comportant les nouveaux neurones ARMA sont mis au point par la technique de retropropagation. Les neurones ARMA servent a modeliser les procedes dynamiques non lineaires simules ou experimentaux, incluant un reacteur a lit fluidise industriel.
Arthropod communities along an elevation gradient in Denali National Park and Preserve, Alaska: Rapidly shrinking tundra hosts a unique assemblage of specialists

ABSTRACT Arthropods at high latitudes and elevations are likely to be vulnerable to effects from climate change such as increased temperatures and shifting vegetation boundaries. Though range shifts northwards and upslope have been reported for many arthropod taxa in temperate latitudes, baseline data needed to track such changes are scarce at northern latitudes. We investigated the influence of climate and vegetation cover on the abundance, diversity, and species composition of pollinators and epigeic arthropods along an elevation gradient in Denali National Park and Preserve, Alaska. We compared arthropods across three habitat types: low-elevation forest, mid-elevation shrubs, and high-elevation tundra along five replicate transects over three years. We collected 35,473 arthropods representing 510 species. Arthropod communities differed distinctly across the three habitat types, with tundra having the highest number of strong indicators and unique species. Elevation, air temperature, and vegetation structure were strong drivers for the ordination of sites. As treeline and shrubline shift upslope with climate change, we predict that distributions of some arthropods will shift to track these habitat boundaries and that tundra-associated arthropods will be most vulnerable as their habitat shrinks. Long-term monitoring of arthropods along elevation gradients at northern latitudes is needed to detect such declines.
Considerations on performance evaluation of cavity-backed slot antenna using the FDTD technique

The finite-difference time-domain (FDTD) method is considered a versatile and efficient tool for the solution of Maxwell's equations in complex structures for any time dependence. We show an antenna feed model suitable for performance evaluation of a cavity-backed slot antenna using the FDTD technique. The gap voltage and the coaxial feed models are examined, and their input characteristics and absolute gains are compared. Analytical results show that the input characteristics are estimated with fewer time steps for the coaxial model than for the conventional gap voltage model. Furthermore, we show how to calculate absolute gains and radiation patterns using the coaxial model and a sinusoidal voltage source at the desired frequency. The computed results of the absolute gain converge after the fifteenth period of the voltage source for the coaxial model and are in good agreement with the experimental results. On the other hand, the absolute gain is observed to fluctuate when the gap voltage model is used. The performance evaluation and comparison reveals that the coaxial model is an appropriate feed model for use in the analysis of the performance of the cavity-backed slot antenna using the FDTD technique. The good agreement of the FDTD results with the experimental measurements demonstrates the effectiveness of the model and the method proposed.
The Connection between Immunocompetence and Reproduction in Wildlife

Reproduction rate is important for the survival of animal populations. During gravidity, a trade-off occurs between the individual well-being of gravid females and investment in offspring. Due to the high synthesis and energy requirements for the growing fetus, other physiological activities are downregulated in pregnant females. This causes changes in the composition of the reproductive microbiome and a decreased immune response to presented antigens and pathogens. As a result, the immunocompetence of gravid wild animals declines. In general, therefore, increased infection rates during pregnancy can be observed in all wildlife species studied. In the course of evolution, however, this has apparently evolved as a suitable strategy to ensure the survival of the population as a whole.
Prospects for targeting ACKR1 in cancer and other diseases

The chemokine network is comprised of a family of signal proteins that encode messages for cells displaying chemokine G-protein coupled receptors (GPCRs). The diversity of effects on cellular functions, particularly directed migration of different cell types to sites of inflammation, is enabled by different combinations of chemokines activating signal transduction cascades on cells displaying a combination of receptors. These signals can contribute to autoimmune disease or be hijacked in cancer to stimulate cancer progression and metastatic migration. Thus far, three chemokine receptor-targeting drugs have been approved for clinical use: Maraviroc for HIV, Plerixafor for hematopoietic stem cell mobilization, and Mogalizumab for cutaneous T-cell lymphoma. Numerous compounds have been developed to inhibit specific chemokine GPCRs, but the complexity of the chemokine network has precluded more widespread clinical implementation, particularly as anti-neoplastic and anti-metastatic agents. Drugs that block a single signaling axis may be rendered ineffective or cause adverse reactions because each chemokine and receptor often have multiple context-specific functions. The chemokine network is tightly regulated at multiple levels, including by atypical chemokine receptors (ACKRs) that control chemokine gradients independently of G-proteins. ACKRs have numerous functions linked to chemokine immobilization, movement through and within cells, and recruitment of alternate effectors like β-arrestins. Atypical chemokine receptor 1 (ACKR1), previously known as the Duffy antigen receptor for chemokines (DARC), is a key regulator that binds chemokines involved in inflammatory responses and cancer proliferation, angiogenesis, and metastasis. Understanding more about ACKR1 in different diseases and populations may contribute to the development of therapeutic strategies targeting the chemokine network.
Plasma sheet ion energization during dipolarization events

The energization of plasma sheet particles during storm-time dipolarization of the magnetospheric field lines is examined by means of three-dimensional particle codes. In the direction perpendicular to the magnetic field, owing to appreciable temporal variations of the field within a cyclotron turn, particles can experience large magnetic moment changes. A detailed analysis of this effect reveals an “effective pick-up velocity” at substorm onset, which depends upon the magnitude of the magnetic transition and delineates particle motions at nearly constant or highly variable magnetic moment. In the parallel direction, the large but short-lived electric field yields an intense acceleration of the particles traveling in the equatorial region. It is demonstrated that significant decelerations can also be achieved off-equator if the particles drift against the surging electric field. Such decelerations occur in regions where the curvature of the E × B paths substantially exceeds that of the magnetic field lines (namely, at relatively large L- shells). Systematic calculations of model plasma sheet distribution functions clearly exemplify the earthward injection of energetic particles during dipolarization events. Owing to phasing between particle motion and the transient electric field, the computed spectrograms display the formation of characteristic bouncing ion patterns with fine structures on fast time scales. To some extent, the simulations support the convection surge mechanism of particle acceleration put forward by Mauk [1986]. However, distinct collapse characteristics as well as the inclusion of nonadiabatic effects result in significantly higher energization rates, particularly at high mass-to-charge ratios.
Quasi-interpolation in Spline Spaces: Local Stability and Approximation Properties

In this work we analyze the approximation error in Sobolev norms for quasi-interpolation operators in spline spaces. We establish in a general way the hypotheses on a quasi-interpolant to achieve the optimal order of approximation. Finally, we propose simple but general constructions of such operators that satisfy the established hypotheses and illustrate their performance through some numerical tests.
Deformation of soap films pushed through tubes at high velocity

The behaviour of soap films pushed through tubes at large velocities, up to several metres per second, is investigated in this paper. The film shape deviates from its equilibrium configuration perpendicular to the walls and gets curved downstream. A simple model relates the radius of curvature of the film to the friction in the lubrication films touching the wall, and the scaling of Bretherton (J. Fluid Mech., vol. 10, 1961, pp. 166–188) holds up to surprisingly high velocities, at which the capillary and Weber numbers are no longer small parameters. The tube geometry is varied and accounted for through the notion of hydraulic diameter. A limit of stability of the films, beyond which they burst or evolve unsteadily, is predicted, and it quantitatively captures the observations. The new questions raised by our results on the dissipation in soap films are discussed, especially the role of Plateau borders and inertial effects.
The Role of RYR2 in Atrial Fibrillation

Background. Atrial fibrillation (AF) is a common arrhythmia in elderly patients and is associated with increased risk of mortality. The pathogenesis of AF is complex and based on multiple genetic and environmental factors. Genome-wide association studies identified several loci in AF patients, indicating the complex genetic architecture of this disease. In rare cases, familial forms of AF have been described. Today, pathogenic variants in at least 11 different genes are associated with monogenic AF. Case presentation. The 37-year-old male patient presented to our emergency department with AF. At the age of 35, he had already been diagnosed with paroxysmal AF. Additionally, his 34-year-old brother had also been diagnosed with AF as well as nonobstructive hypertrophic cardiomyopathy. Moreover, the patient's father was diagnosed with AF in his twenties. Transthoracic echocardiography and cardiac MRI revealed a reduced systolic left ventricular ejection without any signs of hypertrophic cardiomyopathy. Genetic testing identified the heterozygous missense variants c.3371C > T, p.(Pro1124Leu) in RYR2 (NM_001035.3) and c.2524C > A, p.(Pro842Thr) in HCN4 (NM_005477.3) in the patient's and his brother's DNA. Discussion. This case of familial AF helps to strengthen the role of RYR2 as a disease gene in the context of AF. Although the variant in RYR2 needs to be classified formally as variant of unknown significance, we regard it as probably disease-causing due to the previously published data. As RYR2 has already been identified as a possible target for prevention and therapy of AF, the knowledge of variants in RYR2 might become even more crucial for individual molecular therapies in the future.
Electron transport in quantum dot solids: Monte Carlo simulations of the effects of shell filling, Coulomb repulsions, and site disorder

A Monte Carlo model is developed for the hopping conductance in arrays of quantum dots QDs. Hopping is simulated using a continuous time random walk algorithm, incorporating all possible transitions, and using a nonresonant electron-hopping rate based on broadening of the energy levels through quantum fluctuations. Arrays of identical QDs give rise to electronic conductance that depends strongly upon level filling. In the case of low charging energy, metal insulator transitions are observed at electron occupation levels, n, that correspond to the complete filling of an S, P ,o rD shell. When the charging energy becomes comparable to the level broadening, additional minima in conductance appear at integer values of n, as a result of electron-electron repulsion. Disorder in QD diameters leads to disorder in the energy levels, resulting in washing out of the structure in the dependence of conductance on n and a net reduction in conductance. Simulation results are shown to be consistent with experimental measurements of conductance in arrays of zinc oxide and cadmium selenide QDs that have different degrees of size disorder, and the degree of size disorder is quantified. Simulations of the temperature dependence of conductance show that both Coulombic charging and size disorder can lead to activated behavior and that size disorder leads to conductance that is sublinear on an Arrhenius plot.
Integrated Structural Dynamic Response Analysis considering the UNDEX Shock Wave and Gas Bubble Pulse

Two typical impact loadings, shock wave and gas bubble pulse, due to UNDEX(UNDerwater EXplosion), should be considered together for the closest response analysis of structure subjected to UNDEX to a reality. Since these two impact loadings have different response time bands, however, their response characteristics of structure are different from each other. It is impossible to consider these effectively under the current computational environment and the mathematical model has not yet been developed. Whereas Hicks model approximates the fluid-structure interaction due to gas bubble pulse as virtual mass effect, treating the flow by the response of gas bubble after shock wave as incompressible ideal fluid contrary to the compressible flow due to shock wave, Geers-Hunter model could make the closest response analysis of structure under UNDEX to a real one as a mathematical model considering the fluid-structure interaction due to shock wave and gas bubble pulse together using acoustic wave theory and DAA(Doubly Asymptotic Approximation). In this study, the application and effectiveness of integrated dynamic response analysis of submerged structure was examined with the analysis of the shock wave and gas bubble pulse together.
Hamiltonian Formalism and the Canonical Commutation Relations in Quantum Field Theory

Cyclic representations of the canonical commutation relations and their connection with the Hamiltonian formalism are studied. The vacuum expectation functional E(f)=(Ψ0,ei[open phi](f)Ψ0) turns out to be a very convenient tool for the discussion. The uniqueness of a translationally invariant state (vacuum) is proved under the assumption of the cluster decomposition property for E(f). The existence and near uniqueness of the Hamiltonian in cyclic representations of the canonical commutation relations are established. The conditions for the relativistic invariance of the theory are stated in terms of vacuum expectation values at a fixed time. It is shown that E(f) is the Fourier transform of a quasi‐invariant nonnegative measure on the space of all linear functionals of the test functions.
Sample efficient frontier in multivariate conditionally heteroscedastic elliptical models

In this paper, the asymptotic distributions of sample parameters of the efficient frontier and sample characteristics of optimal portfolios are derived. This is done assuming the asset returns to follow a k-dimensional VARMA–GARCH process. Moreover, estimators of the mean vector and the covariance matrix of the asset returns are suggested, which are asymptotic independent normally distributed within the considered class of stochastic processes.
Parasitic nematode secreted phospholipase A2 suppresses cellular and humoral immunity by targeting hemocytes in Drosophila melanogaster

A key aspect of parasitic nematode infection is the nematodes’ ability to evade and/or suppress host immunity. This immunomodulatory ability is likely driven by the release of hundreds of excretory/secretory proteins (ESPs) during infection. While ESPs have been shown to display immunosuppressive effects on various hosts, our understanding of the molecular interactions between individual proteins released and host immunity requires further study. We have recently identified a secreted phospholipase A2 (sPLA2) released from the entomopathogenic nematode (EPN) Steinernema carpocapsae we have named Sc-sPLA2. We report that Sc-sPLA2 increased mortality of Drosophila melanogaster infected with Streptococcus pneumoniae and promoted increased bacterial growth. Furthermore, our data showed that Sc-sPLA2 was able to downregulate both Toll and Imd pathway-associated antimicrobial peptides (AMPs) including drosomycin and defensin, in addition to suppressing phagocytosis in the hemolymph. Sc-sPLA2 was also found to be toxic to D. melanogaster with the severity being both dose- and time-dependent. Collectively, our data highlighted that Sc-sPLA2 possessed both toxic and immunosuppressive capabilities.