Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-expression and interaction network analysis reveals dysregulated neutrophil and T-cell activation as the core mechanism associated with septic shock

Septic shock as a subset of sepsis, has a much higher mortality, while the mechanism is still elusive. This study was aimed at identifying core mechanisms associated with septic shock and its high mortality by investigating transcriptome data. We screened 72 septic-shock-associated genes (SSAGs) with differential expression between septic shock and sepsis in the discovery dataset. Further gene set enrichment analysis identified upregulated neutrophil activation and impaired T-cell activation in septic shock. Co-expression analysis revealed nine co-expressed gene modules. In addition, we determined twenty-one prognostic SSAGs using cox regression analysis in an independent dataset. Moreover, protein–protein interaction (PPI) network revealed two clusters. Among these neutrophil activation was enriched in the most positively-related modules and the cluster2 PPI network, while T-cell activation was enriched in both the most negatively-related module and one of the most positively-related modules as well as the cluster1 PPI network. ELANE, LCN2 and IFI44 were identified as hub genes with CytoHubba methods and semantic similarity analysis. Notably, ELANE was the only prognostic gene and was further validated in an external dataset. Blood neutrophil count was demonstrated to increase in septic shock and be a risky factor of prognosis based on clinical data. In conclusions, septic shock is associated with upregulated neutrophil activation and dysregulated T-cell activation. Three hub genes might have potentials as sensitive markers for the further translational research and ELANE could be a robust prognostic biomarker and effective therapeutic target.
Linewidth narrowed vertical-cavity surface-emitting lasers for millimeter-wave generation by optical heterodyning

Narrow beat-note linewidths as low as 190 kHz have been obtained by optically heterodyning two vertical-cavity surface-emitting lasers (VCSELs) whose linewidths are minimized by optical feedback. Narrow line operation has been achieved stably at frequencies up to a detector limited value of 25 GHz for both free space and fiber-loop arrangements.
A class of approximate Riemann solvers and their relation to relaxation schemes

We show that a simple relaxation scheme of the type proposed by Jin and Xin (Comm. Pure Appl. Math. 48(1995) pp. 235-276) can be reinterpreted as defining a particular approximate Riemann solver for the original system of m conservation laws. Based on this observation, a more general class of approximate Riemann solvers is proposed which allows as many as 2m waves in the resulting solution. These solvers are related to more general relaxation systems and connections with several other standard solvers are explored. The added flexibility of 2m waves may be advantageous in deriving new methods. Some potential applications are explored for problems with discontinuous flux functions or source terms. where u ∈ lR m and the flux function f(u) may be nonlinear. We assume the system is hyperbolic, so the Jacobian f ' (u) is diagonalizable with real eigenvalues. Many finite-volume methods for this conservation law are based on solving Riemann problems at cell interfaces between the neighboring cell averages. The Riemann problem consists of the equation (1.1) together with piecewise constant data with a single discontinuity between two values Ul and Ur. Often some approximate Riemann solver is used, which consists of Mw waves W p ∈ lR m propagating at some speeds s p ∈ lR for p = 1, 2, . ,Mw. The vectors W p represent the jump in u across each wave and must sum up to the total jump,
Pooled Log Periodogram Regression

Estimation of the memory parameter in time series with long range dependence is considered. A pooled log periodogram regression estimator is proposed that utilizes a set of mL periodogram ordinates with L→∞ rather than m ordinates as in the conventional log periodogram estimator. Consistency and asymptotic normality of the pooled regression estimator are established. The pooled estimator is shown to have smaller asymptotic variance, but larger asymptotic bias, than the conventional log periodogram estimator. Finite sample performance is assessed in simulations and the methods are illustrated in an empirical application with inflation and stock returns.
Three-Dimensional numerical modelling of the Marmore waterfalls

This paper describes the application of a three-dimensional Computational Fluid Dynamic (CFD) model to simulate the Marmore waterfall (Italy), which is part of the complex hydraulic system Nera Velino rivers, Piediluco lake. The domain reconstruction has been performed through a non-conventional photogrammetry topographic surveying. The simulations have been performed employing a CFD model that solves the Navier-Stokes equations with the Large Eddy Simulations turbulence closure scheme and the Volume of Fluid multiphase method to handle the free-surface flow. A good agreement is achieved between the CFD model and the real waterfall flow.
Modification of magnetic properties and structure of Kr+ ion-irradiated CrPt3 films for planar bit patterned media

30 keV Kr+ ions were irradiated onto L12 ordered CrPt3 (20 nm) alloy films fabricated by a magnetron sputtering deposition followed by an appropriate heat treatment, and the modification of the structure and magnetic properties of the CrPt3 films was investigated in detail. The fabricated L12 CrPt3 (20 nm) onto a fused quartz substrate exhibited a quite large perpendicular anisotropy of 5×106 ergs/cc, due to the large lattice distortion of 1%. The large perpendicular anisotropy decreased with increasing the ion dose, and became almost zero at the ion dose of 2×1014 ions/cm2 due to the loss of the magnetic order of CrPt3. The suppression of the magnetic order of CrPt3 by the Kr+ ion irradiation is attributed to the transformation of the structure from the L12 phase to a disordered fcc phase, which was confirmed by x-ray diffraction analysis. Unlike the magnetization and perpendicular anisotropy, the anisotropy field of CrPt3 does not decrease significantly with the increase in the Kr+ ion dose, and exhibit.
Both Acute and Consecutive Days of Formoterol Stimulation Influence Myogenic, Mitochondrial, and myomiR Gene Expression in Human Skeletal Muscle Cells

Skeletal muscle physiology is regulated by microRNA that are localized within skeletal muscle (myomiRs). This study investigated how the expression of myomiRs and genes regulating skeletal muscle mass and myogenesis are influenced in response to acute and consecutive days of exercise-related signaling using the exercise mimetic, formoterol, in vitro. Human skeletal muscle cells were proliferated and differentiated for 6 days. Experimental conditions included: (a) control, (b) acute formoterol stimulation (AFS), and (c) consecutive days of formoterol stimulation (CFS). For AFS, myotubes were treated with 30 nM of formoterol for three hours on day 6 of differentiation, and this was immediately followed by RNA extraction. For CFS, myotubes were treated with 30 nM of formoterol for three hours on two or three consecutive days, with RNA extracted immediately following the final three-hour formoterol treatment. We observed increased myomiR expression for both AFS and CFS. AFS appeared to promote myogenesis, but this effect was lost with CFS. Additionally, we observed increased expression of genes involved in metabolism, mitochondrial biogenesis, and muscle protein degradation in response to AFS. myomiR and gene expression appear to be sensitive to acute and long-term exercise-related stimuli, and this likely contributes to the regulation of skeletal muscle mass.
Laser-induced optical anisotropy in self-supporting amorphous GeSe2 films

A comprehensive study of laser induced optical anisotropy in amorphous GeSe2 films is presented. This anisotropic structure of the amorphous network can be reoriented reversibly by changing the incident-beam polarisation. A model is constructed that accounts for experimental findings, in particular for the logarithmic time development of the laser-induced anisotropy.
Letter Strokewidth, Spacing, and Legibility

The development of computerized typography has revolutionized our ability to create type designs, in facilitating both the rapid design of new fonts and the alteration of their characteristics almost infinitely[10, 13]. Although type designs vary for a variety of reasons, their primary purpose is to serve as the elements of text-coded communication. Legibility is a general term that refers to the effectiveness of typography in communicating the text code. It can be defined and measured in several ways, including direct judgment, reading speed[11, 3, 9], and visual acuity [16].
Condition Assessment of Power Circuit Breakers Based on Machine Learning Algorithms

This article presents two approaches to power circuit breakers condition assessment. The first one covers a wide variety of machine learning classification algorithms where the input for the classification is a manually selected feature set. The second one utilizes deep learning classification based on the convolutional neural network. Both approaches revolve around the idea behind spectral kurtosis, one of which exploits its visual representation in the form of kurtogram. The first approach uses a spectral kurtosis curve as the base for feature extraction while the second approach uses a spectral kurtosis kurtogram as a single input into the convolutional neural network. The validation is performed on a large set of vibration signatures and compared to competing state-of-the-art algorithms. The results indicate promising features of the proposed approach.
Mixture model of NMR - its application to diagnosis and treatment of brain cancer

Nuclear Magnetic Resonance (NMR) is widely used technique i n cancer diagnosis and treatment planning. It is employed to search for the high con centration regions of particular metabolites, which are directly related to the concentrati on of cancer cells. NMR signal maybe be characterized by a set of peaks which are representation o f every distinct metabolite. Area under peak must be calculated in order to obtain proper infor mation about metabolite amount. Commercially available software allows for the analysis of one-peak-in-time only. The proposed technique, based on Gaussian Mixture Model (GMM), allows fo r m deling all-peaks-in-time, and corrects after the neighboring peaks giving more accura te estimates of metabolite concentration. The resulting software processes NMR signal from t he very beginning up to the final result, which is given in a form of so called metabolite map.
Tuning between Nuclear Organization and Functionality in Health and Disease

The organization of eukaryotic genome in the nucleus, a double-membraned organelle separated from the cytoplasm, is highly complex and dynamic. The functional architecture of the nucleus is confined by the layers of internal and cytoplasmic elements, including chromatin organization, nuclear envelope associated proteome and transport, nuclear–cytoskeletal contacts, and the mechano-regulatory signaling cascades. The size and morphology of the nucleus could impose a significant impact on nuclear mechanics, chromatin organization, gene expression, cell functionality and disease development. The maintenance of nuclear organization during genetic or physical perturbation is crucial for the viability and lifespan of the cell. Abnormal nuclear envelope morphologies, such as invagination and blebbing, have functional implications in several human disorders, including cancer, accelerated aging, thyroid disorders, and different types of neuro-muscular diseases. Despite the evident interplay between nuclear structure and nuclear function, our knowledge about the underlying molecular mechanisms for regulation of nuclear morphology and cell functionality during health and illness is rather poor. This review highlights the essential nuclear, cellular, and extracellular components that govern the organization of nuclei and functional consequences associated with nuclear morphometric aberrations. Finally, we discuss the recent developments with diagnostic and therapeutic implications targeting nuclear morphology in health and disease.
Novel Smart Assistance System for Arteriosclerosis Evaluation

Arteriosclerosis is a cardiovascular disease that can cause calcification, sclerosis, stenosis, or obstruction of blood vessels and may further cause abnormal peripheral blood perfusion or other complications. In clinical settings, several approaches, such as computed tomography angiography and magnetic resonance angiography, can be used to evaluate arteriosclerosis status. However, these approaches are relatively expensive and require an experienced operator and often the injection of a contrast agent. In this article, a novel smart assistance system based on near-infrared spectroscopy was proposed that can noninvasively assess blood perfusion and thus indicate arteriosclerosis status. In this system, a wireless peripheral blood perfusion monitoring device simultaneously monitors changes in hemoglobin parameters and the cuff pressure applied by a sphygmomanometer. Several indexes extracted from changes in hemoglobin parameters and cuff pressure were defined and can be used to estimate blood perfusion status. A neural network model for arteriosclerosis evaluation was constructed using the proposed system. The relationship between the blood perfusion indexes and arteriosclerosis status was investigated, and the neural network model for arteriosclerosis evaluation was validated. Experimental results indicated that the differences in many blood perfusion indexes for different groups were significant and that the neural network model could effectively evaluate arteriosclerosis status (accuracy = 80.26%). By using a sphygmomanometer, the model can be employed for simple arteriosclerosis screening and blood pressure measurements. The model offers real-time noninvasive measurement, and the system is relatively inexpensive and easy to operate.
Blind deconvolution of long exposure lens-based chromotomographic spectrometer data

Projection-based chromotomographic spectrometers are sensors that collect both spatial and spectral information with fairly simple optical as well as electronic hardware. Efforts to utilize them for remote sensing applications have met with obstacles primarily due to the fact that the impulse response of the imaging system as a function of wavelength must be know in order to reconstruct the spatial/spectral content of the scene under study. This paper reports a blind deconvolution algorithm specifically designed to reconstruct the spectrum of the scene under study as well as an estimate of the wavelength dependent atmospheric transfer function of the system. The method is tested using simulated data with realistic turbulence and noise factors in order to demonstrate its effectiveness.
EADD-YOLO: An efficient and accurate disease detector for apple leaf using improved lightweight YOLOv5

Introduction Current detection methods for apple leaf diseases still suffer some challenges, such as the high number of parameters, low detection speed and poor detection performance for small dense spots, which limit the practical applications in agriculture. Therefore, an efficient and accurate model for apple leaf disease detection based on YOLOv5 is proposed and named EADD-YOLO. Methods In the EADD-YOLO, the lightweight shufflenet inverted residual module is utilized to reconstruct the backbone network, and an efficient feature learning module designed through depthwise convolution is proposed and introduced to the neck network. The aim is to reduce the number of parameters and floating point of operations (FLOPs) during feature extraction and feature fusion, thus increasing the operational efficiency of the network with less impact on detection performance. In addition, the coordinate attention module is embedded into the critical locations of the network to select the critical spot information and suppress useless information, which is to enhance the detection accuracy of diseases with various sizes from different scenes. Furthermore, the SIoU loss replaces CIoU loss as the bounding box regression loss function to improve the accuracy of prediction box localization. Results The experimental results indicate that the proposed method can achieve the detection performance of 95.5% on the mean average precision and a speed of 625 frames per second (FPS) on the apple leaf disease dataset (ALDD). Compared to the latest research method on the ALDD, the detection accuracy and speed of the proposed method were improved by 12.3% and 596 FPS, respectively. In addition, the parameter quantity and FLOPs of the proposed method were much less than other relevant popular algorithms. Discussion In summary, the proposed method not only has a satisfactory detection effect, but also has fewer parameters and high calculation efficiency compared with the existing approaches. Therefore, the proposed method provides a high-performance solution for the early diagnosis of apple leaf disease and can be applied in agricultural robots. The code repository is open-sourced at https://github.com/AWANWY/EADD-YOLO.
The Measurement of Aerosol Optical Properties Using Continuous Wave Cavity Ring-Down Techniques

Abstract Large uncertainties in the effects that aerosols have on climate require improved in situ measurements of extinction coefficient and single-scattering albedo. This paper describes the use of continuous wave cavity ring-down (CW-CRD) technology to address this problem. The innovations in this instrument are the use of CW-CRD to measure aerosol extinction coefficient, the simultaneous measurement of scattering coefficient, and its small size, suitable for a wide range of aircraft applications. The prototype instrument measures extinction and scattering coefficient at 690 nm and extinction coefficient at 1550 nm. The instrument itself is small (60 cm × 48 cm × 15 cm) and relatively insensitive to vibrations. The prototype instrument has been tested in the lab and used in the field. While improvements in performance are needed, the prototype has been shown to make accurate and sensitive measurements of extinction and scattering coefficients. Combining these two parameters, one can obtain the single-s.
Numerical model of current-voltage characteristics and efficiency of GaAs nanowire solar cells

Numerical simulation of current-voltage (J-V) characteristics of III-V nanowire core-shell p-n junction diodes under illuminated conditions is presented with an emphasis on optimizing the nanowire design for photoconversion efficiency. Surface recombination and depletion effects are found to play a dominant role in the J-V characteristics. The impact of surface charge density, surface recombination velocity, doping concentration, and nanowire geometry are investigated. Investigation of contacting methodology indicated that solar cell efficiency is degraded with electrical contacts on the sidewalls of the nanowire due to Fermi level pinning at the metal/semiconductor interface. On the other hand, contacts on the top of nanowires with sidewall passivation provide solar cell performance close to the detailed balance efficiency limit of ∼30%. Elimination of the thin film between nanowires produces a smaller dark current and improved cell performance.
Ultrasonic scattering by blood: theories, experimental results and biomedical applications

In this paper, theoretical and experimental efforts that have been undertaken to better understand the phenomenon of ultrasonic scattering in blood will be reviewed. This subject is of interest in biology and medicine because the echoes generated by blood are used to extract blood velocity by ultrasonic Doppler flow and imaging devices. In the course of these investigations it became clear that ultrasonic scattering from blood is dependent upon such hematological and hemodynamic properties of blood as hematocrit, plasma protein concentration, flow rate and flow cycle duration. Several aspects of these experimental results have been successfully modeled by recent theoretical developments. An unexpected consequence of these efforts is that ultrasound appears to be a viable tool for blood flow visualization and hemodynamic measurements. Two unique hemodynamic phenomena that have never been reported in the hemodynamic literature have been observed: the black hole, a low echogenic zone in the center stream of .
Antibiotic Resistance of Streptococcus pneumoniae in the Nasopharynx of Healthy Children Less than Five Years Old after the Generalization of Pneumococcal Vaccination in Marrakesh, Morocco

Streptococcus pneumoniae (S. pneumoniae) remains one of the most important pathogens causing childhood infections. The spread of antibiotic-resistant bacteria is a leading cause of treatment failure in children. The purpose of this investigation is to report the antibiotic and multidrug resistance (MDR) of S. pneumoniae strains isolated from healthy children throughout the years 2020–2022. Antimicrobial susceptibility testing of S. pneumoniae strains in selected antimicrobials was performed using disk diffusion and E-test methods on bloodMueller–Hinton agar. The antimicrobials tested included oxacillin, amoxicillin, ceftriaxone, norfloxacin, gentamicin, vancomycin, erythromycin, clindamycin, pristinamycin, tetracycline, chloramphenicol, and trimethoprim-sulfamethoxazole. A total of 201 S. pneumoniae strains were isolated from the nasopharynx of healthy children in Marrakesh, Morocco. The highest rate of resistance of S. pneumoniae was found in penicillin (57.2%), followed by tetracycline (20.9%), and erythromycin (17.9%). The rates of resistance to clindamycin, trimethoprim-sulfamethoxazole, and chloramphenicol were 14.9%, 4%, and 1.5%, respectively. All isolates were susceptible to norfloxacin, gentamicin, vancomycin, and pristinamycin. Approximately 17% of all S. pneumoniae strains were resistant to at least three different antibiotic families. This study showed a low rate of antibiotics resistance among nasopharyngeal S. pneumoniae strains, and it is thus essential to monitor S. pneumoniae susceptibility in healthy children.
Reconstruction of a high contrast and large object by using the hybrid algorithm combining a Levenberg-Marquardt algorithm and a genetic algorithm

An iterative inverse scattering technique (IIST) is proposed for reconstructing the permittivity of a two dimensional object with large size and high contrast. The IIST uses the FEM for calculating the electric fields and uses the hybrid algorithm for minimizing the cost function where the hybrid algorithm (HGLMA) is composed of a Levenberg-Marquardt algorithm (LMA) that is a kind of gradient algorithm and genetic algorithm (GA). Numerical results show that the IISTs based on the HGLMA and the GA can all reconstruct the permittivity of the high-contrast and large object, in contrast the IIST based on the LMA can't reconstruct the desired permittivity due to trapping in local minima of the cost function. Numerical results also show that the quality of the permittivity reconstructed by the HGLMA is better than that of the permittivity by GA and the convergence of HGLMA is faster than that of GA. When the noise is present, the characteristics of the cost function show that multiple incident waves are needed for the stable inversion.