Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabonomic Analysis of Metabolites Produced by Escherichia coli in Patients With and Without Sepsis

Aim To analyze the metabolites of the most common sepsis-related pathogen and their correlation with clinical indicators. Methods Information of bacterial-infection patients in Huzhou Central hospital was retrospectively investigated and analyzed. The most common pathogen inducing sepsis was selected. Then, the metabolic profiles of pathogens from blood were detected by liquid chromatography/mass spectrometry. Cluster and classification analysis, KEGG pathway enrichment analysis, multidimensional OPLS-DA, Z scores, correlation analysis were used to analyze the metabolites. Results Escherichia coli (E. coli) was the pathogen that caused the most infection (about 21%) and sepsis. Amino acids, peptides, terpene glycosides, carbohydrates were the main metabolites of E.coli and they were mainly digestive and endocrine-related compounds. Most of them were related to amino acids metabolism, cofactors and vitamins metabolism, biosynthesis of secondary metabolites, et al. Moreover, metabolites were involved in purine metabolism, neuroactive ligand-receptor interaction, ABC transporters, etc. Then, over 70 differential metabolites such as tyramine, tryptophan, 3- hydroxymalondialdehyde were screened in E.coli from nonseptic and septic patients. They were mainly involved in phenylalanine metabolism, tryptophan metabolism, protein digestion and absorption. Distribution of metabolites of E. coli from nonseptic and septic patients was obviously different. What is more, differential metabolites had evidently correlation with SOFA score, APPACHE II score, C-reactive protein, erythrocyte, platelet, aspartate aminotransferase, coagulation function, lactic acid (p < 0.01). Conclusion The different metabolic profile of E. coli from nonseptic and septic patients indicated that differential metabolites might be associated with sepsis.
Interfacial stability with mass and heat transfer

A simplified formulation is presented to deal with interfacial stability problems with mass and heat transfer. For Rayleigh–Taylor stability problems of a liquid‐vapor system, it is found that the effect of mass and heat transfer tends to enhance the stability of the system when the vapor is hotter than the liquid, although the classical stability criterion is still valid. For Kelvin–Helmholtz stability problems, however, the classical stability criterion is found to be substantially modified due to the effect of mass and heat transfer.
Shape of the geomagnetic field solar wind boundary

The shape of the boundary of the geomagnetic field in a solar wind has been calculated by a self-consistent method in which, in first order, approximate magnetic fields are used to calculate a boundary surface. The electric currents in this boundary produce magnetic fields, which can be calculated once the first surface is known. These are added to the dipole field to give more accurate fields, which are then used to compute a new surface. This iterative procedure converges rapidly, and the final surface may be tested by finding how close the total fields outside the boundary are to the required value of zero. The result of this stringent test is that the magnetic fields in the plasma outside the fourth surface and within twice the distance to the boundary on the solar side are everywhere less than 1 per cent of the geomagnetic dipole field in the absence of a solar wind. This surface has been used to calculate the perturbation of the geomagnetic field by the solar wind; the results of these calculations, plus a number of applications, are given in an accompanying paper.
Predicting Chinese Commodity Futures Price: An EEMD-Hurst-LSTM Hybrid Approach

This paper proposes an EEMD-Hurst-LSTM prediction method based on the ensemble learning framework, which is applied to the prediction of typical commodities in China’s commodity futures market. This method performs ensemble empirical mode decomposition (EEMD) on commodity futures prices, and incorporates the components obtained by EEMD decomposition and the adaptive fractal Hurst index calculated by using intraday high-frequency data as new features into the LSTM model to decompose its correlation with the external market to detect changes in market conditions. The results show that the EEMD-Hurst-LSTM method has better predictive performance compared to other horizontal single models and longitudinal deep learning combined models. Meanwhile, the trading strategy designed according to this ensemble model can obtain more returns than other trading strategies and have the best risk control level. The research of this paper provides important implications for the trend following of commodity markets and the investment risk management of statistical arbitrage strategies.
Dislocation propagation and emitter edge defects in silicon wafers

Some transistor defects show a tendency to occur near the edges of emitters. Like ’’area defects’’, these ’’edge defects’’ occur in silicon wafers in a distribution pattern reminiscent of thermal‐stress‐induced dislocations. A peculiar feature is that often a number of edge defects which are close replicas of one another occur in a string, each in one of the neighboring emitters. Such edge defects are preponderant in transistors having silicon nitride surface films. In our proposed model, these emitter edge defects are generated when thermal‐stress‐induced dislocations glide through a row of emitters and interact with the emitter edge stresses, thereby, and under appropriate conditions, casting off small dislocation half‐loops which straddle the edges. The model is shown to be consistent with all the observed phenomena pertaining to the emitter edge defect. To provide a foundation for the discussion of the finer details of the emitter edge defects, we also present an analysis of the nature and distributio.
On BIC's Selection Consistency for Discriminant Analysis

Linear and/or quadratic discriminant analysis (based on finite Gaussian mixture) is one of the most useful classification methods, for which the problem of variable selection is poorly understood. To fill this important theoretical gap, a novel BIC-type selection criterion in conjunction with a backward elimination procedure is proposed. We show theoretically that the new method is able to identify the true Gaussian structure consistently, even with a heteroscedastic covariance structure. Numerical studies are presented to demonstrate the new method's usefulness.
Unilateral hippocampal lesions and the navigational performance of homing pigeons as revealed by GPS-tracking

The left and right hippocampal formation (HF) of the avian brain have been reported to control some different aspects of homing in pigeons. In the current study, we employed GPS-tracking technology and unilateral HF lesions to further explore what if any aspects of a pigeon’s homing flight might be under dominant control by either the left or right HF. Pigeons were released from three locations prior to any experimental manipulation and released repeatedly from the same three sites as sham-lesioned control, right HF-lesioned and left HF-lesioned treatment groups. Analyses of homing performance and virtual vanishing bearings revealed no effect of either lesion treatment. A more in-depth analysis of path efficiency during the initial decision-making, en route and near home phases of a homing flight also revealed no effect of either lesion treatment. A last analysis on the learning and memory for positions along a previously flown route, a proxy for investigating the development of route fidelity, also revealed no effect of either unilateral lesion. However, independent of treatment group, some statistically significant effects were observed with respect to changes in performance across training and the different release sites. The current study revealed no detectable difference between the left and right HF-lesioned pigeons with respect to several navigational parameters of a homing flight. Although in need of supporting experimentation, the results are consistent with the hypothesis that both the left and right HF are similarly able to support several aspects of homing pigeon navigation. HIGHLIGHTS No effect of unilateral HF-lesions on pigeons’ homing was found. Both the left and right HF support local navigation and route fidelity development.
DYNAMICS OF A SMALL DENSITY OF HOLES IN A TWO-DIMENSIONAL QUANTUM ANTIFERROMAGNET

The hole dynamics in a quantum antiferromagnetic background for a small doping concentration is studied within the t-J model description. The noncrossing approximation for the hole self-energy is used. The correct quasiparticle pole structure (without artificial broadening) in the spectral density function is employed. Dyson's equation for the hole Green's function is solved numerically by introducing a lattice in momentum space. The evolution of the density of states and the momentum-distribution function for holes is investigated as a function of hole-magnon coupling constant t at fixed J. The momentum distribution function shows a sharp drop at the Fermi surface for several different hole-magnon coupling constants. This indicates the validity of the Fermi liquid description for the t-J model in the low doping concentration. The volume (surface) enclosed by the Fermi surface (curve) is found to be invariant for all the coupling strengths we have studied. The incoherent spectrum below the chemical potential in the density of states becomes more significant for stronger interaction constants. These features numerically verify Luttinger's theorem for a small density of doped holes in the t-J model. The optical conductivity is computed using the lowest-order diagrams. As the hole-magnon coupling constant t increases, absorption becomes stronger at \ensuremath{\omega}\ensuremath{\simeq}2J, the characteristic frequency for spin waves. This feature may be associated with the experimentally observed midinfrared absorption band in underdoped cuprates.
Konseling kelompok untuk menurunkan kecemasan pada orang tua anak berkebutuhan khusus

Penelitian ini bertujuan untuk mengetahui pengaruh konseling kelompok untuk menurunkan kecemasan pada orang tua anak berkebutuhan khusus. Desain yang digunakan dalam penelitian ini adalah pretest-posttest control group design yang melibatkan 2 kelompok subjek yang ditempatkan secara random dan diukur sebanyak tiga kali (pretest, posttest, follow up dalam 14 hari setelah perlakuan). Subjek penelitian ini sebanyak 10 orang tua anak berkebutuhan khusus yang berada dalam kategori kecemasan ringan hingga berat. Subjek dibagi menjadi 2 kelompok eksperimen dan kelompok kontrol. Metode yang digunakan wawancara, observasi dan skala HARS (Hamilton Rating Scale for Anxiety). Teknik analisis yang digunakan menggunakan Wilxocon dan Mann Whitney. Hasil analisis yang diperoleh Mann Whitney skor follow up diperoleh Z = 2.530 (p<0.050) yang artinya tingkat kecemasan kelompok eksperimen setelah diberi konseling kelompok lebih rendah dibandingkan dengan kelompok kontrol yang tidak diberi konseling kelompok. Hasil Wilcoxon untuk mengetahui perbedaan tingkat kecemasaan sebelum dan sesudah pemberian konseling kelompok pada kelompok eksperimen Z= 2.060 (p<0.050) menunjukkan adanya penurunan kecemasan sebelum dan sesudah konseling kelompok, begitu juga setelah 14 hari pemberian konseling kelompok didapatkan hasil Z = 2.121 (p<0.050) menunjukkan penurunan kembali tingkat kecemasan setelah 14 hari. Penelitian ini menunjukkan bahwa konseling kelompok sebagai salah satu cara untuk menurunkan kecemasan orang tua pada anak berkebutuhan khusus.
Multitarget Detection and Tracking by Mitigating Spot Jammer Attack in 77-GHz mm-Wave Radars: An Experimental Evaluation

Small form factor radar sensors at millimeter wavelengths find numerous applications in the industrial and automotive sectors. These radar sensors provide improved range resolution, good angular resolution, and enhanced Doppler resolution for short range and ultrashort ranges. However, it is challenging to detect and track the targets accurately when a radar is interfered by another radar. This article proposes an experimental evaluation of a 77-GHz IWR1642 radar sensor in the presence of a second 77-GHz AWR1642 radar sensor acting as a spot jammer. A real-time experiment is carried out by considering five different targets of various cross sections, such as a car, a larger size motorcycle, a smaller size motorcycle, a cyclist, and a pedestrian. The collected real-time data are processed by four different constant false alarm rate detectors, cell averaging (CA)-CFAR, ordered statistics (OS)-CFAR, greatest of CA (GOCA)-CFAR, and smallest of CA (SOCA)-CFAR. Following that, data from these detectors are fed into two different clustering algorithms (density-based spatial clustering of applications with noise (DBSCAN) and K-means), followed by the extended Kalman filter (EKF)-based tracker with global nearest neighbor (GNN) data association, which provide tracks of various targets with and without the presence of a jammer. Furthermore, four different metrics [tracks reported (TR), track segments (TSs), false tracks (FTs), and track loss (TL)] are used to evaluate the performance of various tracks generated for two clustering algorithms with four detection schemes. The experimental results show that the DBSCAN clustering algorithm outperforms the K-means clustering algorithm for many cases.
Reducing the complexity of linear optics quantum circuits

Integrated optical elements can simplify the linear optics used to simulate quantum circuits. These linear optical simulations of quantum circuits have been developed primarily in terms of the free space optics associated with single-photon interferometry. For an L -bit simulation the number of required free-space optical elements is } 2 L if 50/50 beam splitters are used. The implementation ~ construction and alignment ! of these circuits with these free-space elements is nontrivial. On the other hand, for the cases presented in this paper in which linear integrated optics ~ e.g., 2 L 3 2 L ﬁber couplers ! are used, the number of optical devices does not grow exponentially with L . The problem is changed from having an exponential growth of the number of devices to having devices with an exponential growth in the number of ports. In addition to simplifying the construction, the association of an N 3 N ﬁber coupler with the discrete Fourier transform suggests alternative formulations for the circuits. Several examples of circuit reductions are given.
Binaural interaction in human and cat brain stem evoked responses

Early (less than 10 ms latency) auditory evoked responses were recorded between vertex and midline nape from humans and anesthetized cats. For both monaural and binaural clicks, averaged responses were obtained as a function of intensity. The averaged responses to stimulation of each ear were then summed and compared with the binaural response. For both humans and cats, the early portions of the binaural response (through the third positive peak) were nearly identical to those in the summed monaural responses. In contrast, the later waves of the binaural response differed significantly from those in the combined monaural responses. This difference, indicating binaural interaction, was usually found at all intensity levels for which the responses could be accurately measured. The similar behavior of these responses in both humans and cats suggests a possible correspondence of specific response components between these two species which may prove useful in providing an animal model for studying the origins .
Empirical Edgeworth expansions for symmetric statistics

In this paper the validity of a one-term Edgeworth expansion for Studentized symmetric statistics is proved. We propose jackknife estimates for the unknown constants appearing in the expansion and prove their consistency. As a result we obtain the second-order correctness of the empirical Edgeworth expansion for a very general class of statistics, including U-statistics, L-statistics and smooth functions of the sample mean. We illustrate the application of the bootstrap in the case of a U-statistic of degree two.
CSN6 mediates nucleotide metabolism to promote tumor development and chemoresistance in colorectal cancer.

Metabolic reprogramming can contribute to colorectal cancer (CRC) progression and therapy resistance. Identification of key regulators of CRC metabolism could provide new approaches to improve treatment and reduce recurrence. Here, we demonstrate a critical role for the COP9 signalosome subunit CSN6 in rewiring nucleotide metabolism in CRC. Transcriptomic analysis of CRC patient samples revealed a correlation between CSN6 expression and purine and pyrimidine metabolism. A colitis-associated colorectal cancer model established that Csn6 intestinal conditional deletion decreased tumor development and altered nucleotide metabolism. CSN6 knockdown increased the chemosensitivity of CRC cells in vitro and in vivo, which could be partially reversed with nucleoside supplementation. Isotope metabolite tracing showed that CSN6 loss reduced de novo nucleotide synthesis. Mechanistically, CSN6 upregulated purine and pyrimidine biosynthesis by increasing expression of PHGDH, a key enzyme in the serine synthesis pathway. CSN6 inhibited β-Trcp-mediated DDX5 polyubiquitination and degradation, which in turn promoted DDX5-mediated PHGDH mRNA stabilization, leading to metabolic reprogramming and CRC progression. Butyrate treatment decreased CSN6 expression and improved chemotherapy efficacy. These findings unravel the oncogenic role of CSN6 in regulating nucleotide metabolism and chemosensitivity in CRC.
Mechanical characterization of suspended GaN microstructures fabricated by GaN-on-patterned-silicon technique

The mechanical properties of high-quality suspended GaN microstructures fabricated by GaN-on-patterned-silicon technique are characterized. Micro-Raman scattering is used to study the stress distribution in the GaN microstructures, and the measured results show that the stress in GaN microbeams decreases 47% when the silicon underneath the microbeams is removed. Microbeam bending test is used to measure the Young’s modulus of GaN films grown on silicon (111) substrate, yielding a Young’s modulus of 330 GPa.
The acoustics of the snapping shrimp Synalpheus parneomeris in Kaneohe Bay

Snapping shrimp are among the major sources of biological noise in shallow bays, harbors, and inlets, in temperate and tropical waters. Snapping shrimp sounds can severely limit the use of underwater acoustics by humans and may also interfere with the transmission and reception of sounds by other animals such as dolphins, whales, and pinnipeds. The shrimp produce sounds by rapidly closing one of their frontal chela (claws), snapping the ends together to generate a loud click. The acoustics of the species Synalpheus paraneomeris was studied by measuring the sound produced by individual shrimp housed in a small cage located 1 m from an H-52 broadband hydrophone. Ten clicks from 40 specimens were digitized at a 1-MHz sample rate and the data stored on computer disk. A low-frequency precursor signature was observed; this previously unreported signature may be associated with a “plunger” structure which directs a jet of water forward of the claw during a snap. The peak-to-peak sound pressure level and energy flux density at 1 m (source level and source energy flux density) varied linearly with claw size and body length. Peak-to-peak source levels varied from 183 to 189 dB re: 1 μPa. The acoustic power produced by a typical snap was calculated to be about 3 W. A typical spectrum of a click had a low-frequency peak between 2 and 5 kHz and energy extending out to 200 kHz. The spectrum of a click is very broad with only a 20-dB difference between the peak and minimum amplitudes across 200 kHz. A physical model of the snapping mechanism is used to estimate the velocity, acceleration, and force produced by a shrimp closing its claws.
Entrepreneurship and environmental sustainability in highly polluting Asian economies: the role of eco-innovation

We aim to investigate the impact of environmental entrepreneurship and green innovations on CO2 emissions in highly polluting Asian economies. For empirical estimation, we have applied ARDL and NARDL models. In the short run, the linear estimates of environmental entrepreneurship are significant in China and India. The short-run non-linear estimates of environmental entrepreneurship are significant in the case of China, India, and Japan. Similarly, the short-run linear estimates of green innovations are significant in China, India, and Japan, whereas the non-linear estimated coefficients of green innovation appeared to be significant in India, Japan, and Russia. In the long run, the linear estimates of environmental entrepreneurship are negative and significant in three countries, namely China, Japan, and Russia. Similarly, the estimates of green innovations are negative and significant in China, India, Japan, and Russia. In the non-linear model, the estimated coefficients of positive shock in environmental entrepreneurship are significant and negative in the case of China, India, and Japan; while, the estimates of negative shock in environmental entrepreneurship are negative and significant in India only.
Topics on Dynamic Panel Data Models with Random Effects Using Semi-Parametric Bayesian Approach

A common assumption in fitting panel data models is normality of stochastic subject effects. This can be extremely restrictive, making vague most potential features of true distributions. The objective of this article is to propose a modeling strategy, from a semi-parametric Bayesian perspective, to specify a flexible distribution for the random effects in dynamic panel data models. This is addressed here by assuming the Dirichlet process mixture model to introduce Dirichlet process prior for the random-effects distribution. We address the role of initial conditions in dynamic processes, emphasizing on joint modeling of start-up and subsequent responses. We adopt Gibbs sampling techniques to approximate posterior estimates. These important topics are illustrated by a simulation study and also by testing hypothetical models in two empirical contexts drawn from economic studies. We use modified versions of information criteria to compare the fitted models.
Lie group analysis for the effect of viscosity and thermophoresis particle deposition on free convective heat and mass transfer in the presence of suction/injection

An analysis has been carried out to study heat and mass transfer characteristics of an incompressible and Newtonian fluid having temperature-dependent fluid viscosity and thermophoresis particle deposition over a vertical stretching surface with variable stream condition. The Rosseland approximation is used to describe the radiative heat flux in the energy equation. The vertical surface is assumed to be permeable so as to allow for possible wall suction or injection. The governing differential equations are derived and transformed using Lie group analysis. The transformed equations are solved numerically by applying Runge-Kutta Gill scheme with shooting technique. Favorable comparisons with previously published work on various special cases of the problem are obtained. Numerical results for the velocity, temperature and concentration profiles for a prescribed temperature-dependent fluid viscosity and thermophoresis particle deposition parameters are presented graphically to elucidate the influence of the various physical parameters.