Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon Flux with DAMPE Using Machine Learning Methods

DAMPE space-borne cosmic ray experiment has been collecting data since December 2015. Many high-impact results on the ion, electron and photon fluxes were obtained. This submission presents the carbon flux analysis with DAMPE using machine learning techniques. The readout electronics would saturate at energy deposits above several TeV in a single BGO bar of the DAMPE calorimeter. The total energy loss per event due to saturation can sometimes reach over a hundred TeV. We present a convolutional neural network model which can accurately recover the energy lost due to saturation and thus significantly increase the dynamic range of DAMPE. Another machine learning model combines the resolution of the hodoscopic BGO calorimeter and the high-resolution tracker of DAMPE to provide the best possible prediction of the direction of the incoming particle. This allows measuring charges at energies up to several hundred TeV. In this work, we present the application of these methods to carbon flux analysis.
Artificial Intelligence in the Pathology of Gastric Cancer

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.
Online support for research activities by high school and junior high school students

H. Enomoto,a,b,∗ H. Abe,a,c R. Hoashi,a M. Kimura,a,d R. Kita,a N. Kobayashi,a,e R. Kono,a K. Kumagai,a, f K. Maruta,a,g R. Nakagawa,a,h C. Nose,a,i R.J. Saito,a, j M. Sasaki,a,k M. Takanashia,l and K. S. Tanakaa,m aAccel Kitchen LLC, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan bTokyo Institute of Technology, Department of Earth and Planetary Science, 2-12-1 Ookayama, Meguro-ku, Tokyo, Japan cTohoku University, Department of Mechanical and Aerospace Engineering, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan dTohoku University, Department of Earth Science, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japa eTokyo Denki University, Department of Robotics and Mechatronics, 5 Senju Asahi-cho, Adachi-ku, Tokyo, Japan f University of Tokyo, Natural Sciences I 3-8-1 Komaba, Meguro-ku, Tokyo, Japan gTohoku University, Department of Quantum Science and Energy Engineering, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan hTohoku University, Department of Chemistry, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan iTohoku University, Planetary Plasma and Atmospheric Research Center, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan jTohoku University, Department of Physics, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai, Japan kTohoku University, Department of Health Sciences, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan lUniversity of Electro-Communications, Cluster III (Fundamental Science and Engineering), 1-5-1 Chofugaoka, Chofu, Tokyo Japan mWaseda University, Faculty of Science and Engineering, 3-4-1 Okubo, Shinjuku-ku, Tokyo, Japan
An X-Band Low Phase Noise Parallel-Feedback Oscillator Based on SIW Dual-Mode Filtering Power Divider

In this brief, a new low phase noise feedback oscillator based on substrate integrated waveguide (SIW) dual-mode filtering power divider (DMFPD) is proposed. Several via perturbations are added to the cavity to make the TM010 and TM110 modes form a two order DMFPD. In the oscillator design, the DMFPD can achieve both frequency stabilization and power distribution by using only one single circular cavity. Therefore, high circuit integration and low insertion loss can be realized. Meanwhile, the controllable transmission zero near the upper passband edge can increase the group delay peak to improve the phase noise performance. For verification, the proposed oscillator has been investigated, fabricated and measured. The measured result shows that the parallel-feedback oscillator works at 9.97 GHz and the phase noise is −139.6 dBc/Hz at 1-MHz frequency offset from the oscillation frequency.
Overexpression of NT-3 in the hippocampus suppresses the early phase of the adult neurogenic process

The dentate gyrus (DG) of the hippocampus regulates stress-related emotional behaviors and ensures neurogenesis throughout life. Neurotrophin-3 (NT-3) is a neurotrophic factor that regulates neuronal differentiation, survival, and synaptic formation in both the peripheral and central nervous systems. NT-3 is expressed in the adult DG of the hippocampus; several chronic stress conditions enhance NT-3 expression in rodents. However, functional modulation of the adult DG by NT-3 signaling remains unclear. To directly investigate the impact of NT-3 on DG function, NT-3 was overexpressed in the hippocampal ventral DG by an adeno-associated virus carrying NT-3 (AAV-NT-3). Four weeks following the AAV-NT-3 injection, high NT-3 expression was observed in the ventral DG. We examined the influence of NT-3 overexpression on the neuronal responses and neurogenic processes in the ventral DG. NT-3 overexpression significantly increased the expression of the mature DG neuronal marker calbindin and immediate early genes, such as Fos and Fosb, thereby suggesting DG neuronal activation. During neurogenesis, the number of proliferating cells and immature neurons in the subgranular zone of the DG significantly decreased in the AAV-NT-3 group. Among the neurogenesis-related factors, Vegfd, Lgr6, Bmp7, and Drd1 expression significantly decreased. These results demonstrated that high NT-3 levels in the hippocampus regulate the activation of mature DG neurons and suppress the early phase of neurogenic processes, suggesting a possible role of NT-3 in the regulation of adult hippocampal function under stress conditions.
Leadership competencies developed during a short-term domestic study tour: An exploration of participants’ perceptions

As short-term study abroad tours seek to develop globally competent leaders within the agricultural industry, the rich diversity present within the United States has led to the inception of short-term domestic study tours. To improve how global leadership competencies are developed among adolescent participants, understanding competencies gained during short-term international and domestic cultural immersion trips is vital. This case study analysis sought to explore state FFA officer perceptions of leadership competencies developed through participation in the National FFA Organization’s International Leadership Seminar for State Officers (ILSSO) which pivoted to a domestic study tour for 2022. The findings indicate participants perceived agricultural exposure and networking with peers as the development of leadership competencies. Participants also expressed perspective shifts around agricultural production methods and varied cultural experiences in the state of California. Recommendations include designing leadership curriculum for both short-term abroad and domestic tours with a framework grounded in leadership theory and replicating this study to compare findings in various contexts. Similar studies should also be conducted to assess outcomes of leadership development programs designed by the National FFA Organization.
Comment: Bayes, Model Uncertainty, and Learning from Data

Robert M. O’Brien is a professor emeritus at the University of Oregon. He specializes in criminology and quantitative methods. Within criminology, he focuses on the methods used to gather criminological data, on the analysis of crime rates, and on the task of extricating the effects of ages, periods, and cohorts on crime rates. His most recent publication on that topic, “Homicide Arrest Rate Trends in the United States: The Contributions of Periods and Cohorts (1965–2015),” appeared in 2018 in the Journal of Quantitative Criminology. In quantitative methods, some of his contributions involve the effects of using interval data as ordinal, generalizability theory, identification in structural equation modeling measurement models, the use of multicollinearity indices, and an obsession with age-period-cohort models. In 2015 he published a book on this topic, Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data (Chapman & Hall, 2015).
Deformation Due to Inclined Loads in Thermoporoelastic Half Space

The present investigation is concerned with the deformation of thermoporoelastic half space with incompressible fluid as a result of inclined load of arbitrary orientation. The inclined load is assumed to be linear combination of normal load and tangential load. The Laplace and Fourier transform technique are used to solve the problem. The concentrated force, uniformly distributed force and a moving force in time and frequency domain are taken to illustrate the utility of the approach. The transformed components of displacement, stress, pore pressure and temperature change are obtained and inverted by using a numerical inversion techniques. The variations of resulting quantities are depicted graphically. A particular case has also been deduced. © 2016 IAU, Arak Branch.All rights reserved.
Estimation of the yield curve for Costa Rica using metaheuristic optimization

The term structure of interest rates or yield curve is a function relating the interest rate with its own term. Nonlinear regression models of Nelson-Siegel and Svensson were used to estimate the yield curve using a sample of historical data supplied by the National Stock Exchange of Costa Rica. The optimization problem involved in the estimation process of model parameters is addressed by the use of metaheuristics: Ant colony, Genetic algorithm, Particle swarm and Simulated annealing. The aim of the study is to improve the local minimum obtained by an optimization method using descent direction. Good results with at least two metaheuristics are achieved, Particle swarm and Simulated annealing.
The components discrimination of CRs by LHAASO-KM2A from 1 PeV to 10 PeV with deep neural network

The origin of the cosmic rays(CRs) in the knee region has been a controversial issue, and how to distinguish their composition for ground-based detectors is still very challenging. The most common method currently used to identify the components of CRs is based on calculation and extraction of composition sensitive variables from the reconstructed information. This method can be constrained by the limited computing power so that deeper relationships between the features of the CR components cannot be extracted. In this research, an updated deep neural network (DNN) model is developed to distinguish between primary CR components from extensive air showers detected by KM2A arrays. Our preliminary result shows that the DNN model with AUC value 0.900 in Proton-Helium identification is more effective for identification of CR in the knee region than the traditional method with AUC value 0.750, and similar result is obtained for Fe-MgAlSi identification.
Computing heteroclinic orbits using adjoint-based methods

Transitional turbulence in shear flows is supported by a network of unstable exact invariant solutions of the Navier–Stokes equations. The network is interconnected by heteroclinic connections along which the turbulent trajectories evolve between invariant solutions. While many invariant solutions in the form of equilibria, travelling waves and periodic orbits have been identified, computing heteroclinic connections remains a challenge. We propose a variational method for computing orbits dynamically connecting small neighbourhoods around equilibrium solutions. Using local information on the dynamics linearized around these equilibria, we demonstrate that we can choose neighbourhoods such that the connecting orbits shadow heteroclinic connections. The proposed method allows one to approximate heteroclinic connections originating from states with multi-dimensional unstable manifold and thereby provides access to heteroclinic connections that cannot easily be identified using alternative shooting methods. For plane Couette flow, we demonstrate the method by recomputing three known connections and identifying six additional previously unknown orbits.
Magnetic energy dissipation through multiple collisions of jets and winds

We demonstrate the eﬃcient internal shock dissipation through the multiple interactions between magnetized relativistic jets with weakly magnetized winds by our implemented spherically symmetrical one-dimensional special relativistic magneto-hydrodynamic simulation. We estimated an energy dissipation eﬃciency through multiple interactions with alternately injected magnetized jets and weakly magnetized winds. Our numerical results show the magnetic energy of the jet is converted into the kinetic energy of the shocked external medium by the magnetic pressure, then dissipated into the internal energy by the shock waves. Multiple magnetic energy conversion processes can produce kinetically dominated relativistic outﬂows with almost 10% average dissipation eﬃciency. Such outﬂows are relevant for observed non-thermal emissions in blazars or gamma-ray bursts.
Stability of Levitating Objects

In this paper we revisit the levitation phenomenon using the nonlocal physical description of this levitation phenomenon. This approach can identify the conditions when the levitation can take place under the influence of correlated electromagnetic and gravitational fields. The sufficient mathematical conditions of levitation are used. It means that the regime of levitation could be realized from the position of the non-local hydrodynamics. The stability of the spherical levitating objects is investigated. The appearance of the strong radial fluctuations leads to the destruction of the levitation regime.
Goodness-of-Fit Test in Multivariate Jump Diffusion Models

In this article, we develop a new goodness-of-fit test for multivariate jump diffusion models. The test statistic is constructed by a contrast between an “in-sample” likelihood (or a likelihood of observed data) and an“out-of-sample” likelihood (or a likelihood of predicted data). We show that under the null hypothesis of a jump diffusion process being correctly specified, the proposed test statistic converges in probability to a constant that equals to the number of model parameters in the null model. We also establish the asymptotic normality for the proposed test statistic. To implement this method, we invoke a closed-form approximation to transition density functions, which results in a computationally efficient algorithm to evaluate the test. Using Monte Carlo simulation experiments, we illustrate that both exact and approximate versions of the proposed test perform satisfactorily. In addition, we demonstrate the proposed testing method in several popular stochastic volatility models for time series of weekly S&P 500 index during the period of January 1990 and December 2014, in which we invoke a linear affine relationship between latent stochastic volatility and the implied volatility index.
Effect of Potato Vine and Leaf Mixed Silage to Whole Corn Crops on Rumen Fermentation and the Microbe of Fatten Angus Bulls

The objective of this study was to evaluate the effects of potato vine and leaf mixed silage (PVS) on rumen fermentation and the microbe in ruminants and to improve the utilization of PVS resources in ruminants through in vitro gas production and feeding trials. The experiment was divided into three groups: PVS1 (50% corn + 50% potato vine and leaf silage), PVS2 (75% potato vine and leaf + 15% rice straw + 10% cornmeal silage) and whole-plant corn silage (CS). The in vitro gas production results showed that there was a significant reduction in PVS groups in the indexes of total gas (p < 0.05) and CH4 production (p < 0.05). The digestibility of dry matter (p < 0.05), neutral detergent fiber (NDF) (p < 0.05), and acid detergent fiber (ADF) (p < 0.05) at 48 h were decreased in the PVS group. For the rumen fermentation indexes, the pH (p < 0.05), microbial crude protein (MCP) (p < 0.05), and acetate to propionate (p < 0.05) showed an increase in the PVS group, but a decrease in the total volatile fatty acid concentration (p < 0.05). In the feeding trial, different silages in diets had no significant effect on the rumen fermentation indexes (p > 0.05). In the rumen microbe composition, the PVS diet significantly reduced the abundance of Prevotella (p < 0.05) compared with the CS diet group. The PVS2 diet significantly increased the abundance of the Lachnospiraceae_XPB1014_group (p < 0.05) and Bacteroidales_bacterium_Bact_22 (p < 0.05) compared with the CS diet group. In conclusion, PVS had no negative effect on rumen fermentation characteristics and rumen microbial flora and could significantly reduce rumen gas production compared to CS, positively mitigating animal husbandry CH4 emissions and environmental protection.
Identification of Ultra High Energy neutrino induced acoustic pulses

According to the thermo-acoustic model introduced by Askaryan, the instantaneous energy deposition of a particle’s shower in a medium produces a sound wave. The concept of acoustic neutrino detection is based on this principle. As the extremely low ﬂux of Ultra-High Energy cosmic neutrinos is a limiting factor for the study of related astrophysical phenomena, large detector conﬁgurations have to be built. As sound has a much larger attenuation length than light in water, the development of hydrophone array-based detectors is a feasible solution. The ability to identify Ultra-High Energy neutrino induced acoustic pulses in underwater sound is discussed in this contribution. Acoustic pulses from Ultra-High Energy hadronic showers in the sea water simulated in the EeV regime are added to sea-state 0 noise recordings collected at a water depth of 1600 meters, Southwest of Peloponnese, Greece. Sophisticated signal processing and artiﬁcial intelligence techniques are developed and used for signal identiﬁcation.
Abnormal diagnosis of acoustic emission pipeline working conditions based on PSO-LSTM-DAE

To solve the problem of difficult identification of pipeline working conditions, acoustic emission was used to extract abnormal pipeline data, and a PSO-Lstm-DAE model was proposed to classify and identify abnormal working conditions of acoustic emission pipelines. The algorithm took advantage of the timing characteristics of LSTM and the noise reduction ability of DAE and set the optimal superparameters through PSO. In this paper, four commonly used abnormal condition detection data sets were collected, and algorithm tests were carried out on the data sets and compared with other anomaly detection algorithms. The classification accuracy of the proposed PSO-LSTM-DAE model was 95.68%. The results of multiple indexes show that the PSO-LSTM-DAE model proposed in this paper has significant advantages in the diagnosis of abnormal pipeline conditions.
Optical emission spectroscopy characterizations of micro-air plasma used for simulation of cell membrane poration

A micro-air corona discharge, which is one of the plasmas successfully used for gene transfection in terms of high transfection and cell viability rates, is characterized by optical emission spectroscopy. This non-equilibrium low temperature plasma is generated from the tip of a pulsed high voltage micro-tube (0.2 mm inner diameter and 0.7 mm for outer diameter) placed 2 mm in front of a petri dish containing deionized water and set on a grounded copper plate. The electron temperature, equal to about 6.75 eV near the electrode tip and decreased down to 3.4 eV near the plate, has been estimated, with an error bar of about 30%, from an interesting approach based on the experimental ratio of the closest nitrogen emission spectra of N2+(FNS) at 391.4 nm and N2(SPS) at 394.3 nm. This is based on one hand on a balance equation between creations and losses of the excited upper levels of these two UV spectra and on the other hand on the electron impact rates of the creation of these upper levels calculated from solution of the multi-term Boltzmann equation. Then using the measured Hα spectrum, electron density ne has been estimated from Stark broadening versus the inter-electrode position with an average error bar of about 50%. ne ≈ 1 × 1015 cm−3 is near the tip coherent with the usual magnitude of electron density in the streamer head developed near the tip of the corona discharges. Rotational temperatures, estimated from comparison of synthetic and experimental spectra of OH(A − X), N2+(FNS) at 391.4 nm, and N2(SPS) at 337 nm are respectively equal to 2350 K, 2000 K and 700 K in the gap space. This clearly underlines a thermal non-equilibrium of the corresponding excited species generated inside the thin streamer filaments. But, due to the high dilution of these species in the background gas, these high rotational temperatures do not affect the mean gas temperature that remains close to 300 K. Then, N2+(FNS) for (0,0) and (1,1) head bands spectra at 391.4 nm and 388.4 nm allowed estimation of the vibrational temperature Tvib from around 3000 K near the tip electrode up to about 6500 K near the plate. Last, the spatial variation along the z axis of the nitrogen ion density has been determined, with an error bar of about 50%, from the relative intensities of the same close wavelength spectra (N2(SPS) at 394.3 nm and N2+(FNS) at 391.4 nm) when assuming a prior calibration of 1015 cm−3 at z = 0 mm taken from literature streamer dynamics simulations. The present experimental plasma characteristics are used to better understand the mechanisms and the processes involved during plasma gene transfections in a Monte Carlo poration model previously developed to simulate the membrane permeabilization and pore formation when the cells are impacted by the present micro-air plasma fluxes.
Variation, during Shelf Life, of Functional Properties of Biscuits Enriched with Fibers Extracted from Artichoke (Cynara scolymus L.)

To boost revaluation of industrial by-products of artichoke, this research tries to determine the stability throughout storage of phenolic compounds and their antioxidant activity in biscuits enriched with fiber-rich powders extracted from b y-products of artichokes (FRPA). To determine the most stable extraction method, biscuits were formulated with FRPA extracted by two different environmentally friendly extraction solvents: water (W) and a solution of 1% CaCl2∙5H2O (CA) and compared with biscuits made with pea fiber (P) and control biscuits (B) without fiber added. Initially and during storage, the biscuits enriched with FRPA (W, CA) showed a higher content of bioavailable polyphenols and antioxidant activity compared to the control biscuits (B) and the reference fiber (P, pea fiber). In conclusion, FRPA are an excellent source of bioavailable fiber with antioxidant activity, but especially the FRPA extracted with 1% CaCl2∙5H2O (CA), and they could present a good alternative to the use of pea fiber.