Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Transmembrane Water Exchange in Glioma Invasion/Migration: In Vivo Preclinical Study by Relaxometry at Very Low Magnetic Field

Simple Summary Since the pioneering work of Damadian (1971), the longitudinal T1-relaxation of nuclear magnetic resonance (NMR) has been reported to generate significant contrast between cancer and healthy tissues at low magnetic fields. However, low NMR sensitivity was a substantial obstacle. Fast field cycling NMR (FFC-NMR) can overcome this problem and is commercially available for physics/chemistry research since around the years 2000s. Herein, using FFC-NMR in vivo, we show that T1-relaxation measured at very low fields is sensitive to transmembrane water exchange, thus allowing the discrimination between glioma invasion/migration and proliferation. Aquaporins 4 and 1 are found to be upregulated in invasion/migration, indicating that water exchange modulates T1-relaxations in glioma, via these aquaporins action. Overall, results suggest that, by blocking the aquaporin functions, the T1-relaxation should decrease in invasion/migration glioma. Results also stipulate that the entire invasion/migration volume could be visualized by FFC imaging, noninvasively. This may impact the medical community since invasion/migration delineation remains challenging by any medical imaging modality. Abstract This work shows that the longitudinal relaxation differences observed at very low magnetic fields between invasion/migration and proliferation processes on glioma mouse models in vivo are related to differences in the transmembrane water exchange basically linked to the aquaporin expression changes. Three glioma mouse models were used: Glio6 and Glio96 as invasion/migration models and U87 as cell proliferation model. In vivo proton longitudinal relaxation-rate constants (R1) at very low fields were measured by fast field cycling NMR (FFC-NMR). The tumor contribution to the observed proton relaxation rate, R1tum (U87: 12.26 ± 0.64 s−1; Glio6: 3.76 ± 0.88 s−1; Glio96: 6.90 ± 0.64 s−1 at 0.01 MHz), and the intracellular water lifetime, τin (U87: 826 ± 19 ms; Glio6: 516 ± 8 ms; Glio96: 596 ± 15 ms), were found to be good diagnostic hallmarks to distinguish invasion/migration from proliferation (p < 0.01 and 0.001). Overexpression of AQP4 and AQP1 were assessed in invasion/migration models, highlighting the pathophysiological role of these two aquaporins in water exchange that, in turn, determine the lower values in the observed R1 relaxation rate constant in glioma invasion/migration. Overall, our findings demonstrate that τin and R1 (measured at very low fields) are relevant biomarkers, discriminating invasion/migration from proliferation in vivo. These results highlight the use of FFC-NMR and FFC-imaging to assess the efficiency of drugs that could modulate aquaporin functions.
Research of Command Entity Intelligent Decision Model based on Deep Reinforcement Learning

The paper intends to conduct research on deep reinforcement learning and its application in intelligent decision models. A framework of command entity intelligent decision model based on deep reinforcement learning is proposed, through the description of the decision-making process and the Markov decision process. This paper clarifies the relationship between operational objectives, operational effectiveness and reinforcement learning objectives.
Unified Orbital Description of the Envelope Dynamics in Two‐Dimensional Simple Periodic Lattices

The propagation of wave envelopes in two‐dimensional (2‐D) simple periodic lattices is studied. A discrete approximation, known as the tight‐binding (TB) approximation, is employed to find the equations governing a class of nonlinear discrete envelopes in simple 2‐D periodic lattices. Instead of using Wannier function analysis, the orbital approximation of Bloch modes that has been widely used in the physical literature, is employed. With this approximation the Bloch envelope dynamics associated with both simple and degenerate bands are readily studied. The governing equations are found to be discrete nonlinear Schrödinger (NLS)‐type equations or coupled NLS‐type systems. The coefficients of the linear part of the equations are related to the linear dispersion relation. When the envelopes vary slowly, the continuous limit of the general discrete NLS equations are effective NLS equations in moving frames. These continuous NLS equations (from discrete to continuous) also agree with those derived via a direct multiscale expansion. Rectangular and triangular lattices are examples.
Steady-State Sensitivity Analysis of Continuous Time Markov Chains

In this paper we study Monte Carlo estimators based on the likelihood ratio approach for steady-state sensitivity. We first extend the result of Glynn and Olvera-Cravioto [doi:doi: 10.1287/stsy.2018. 002] to the setting of continuous time Markov chains with a countable state space which include models such as stochastic reaction kinetics and kinetic Monte Carlo lattice system. We show that the variance of the centered likelihood ratio estimators does not grow in time. This result suggests that the centered likelihood ratio estimators should be favored for sensitivity analysis when the mixing time of the underlying continuous time Markov chain is large, which is typically the case when systems exhibit multi-scale behavior. We demonstrate a practical implication of this analysis on a numerical benchmark of two examples for the biochemical reaction networks.
Comparison of two multiple plankton samplers: MOCNESS and Multinet Mammoth

To ensure an optimal continuation of a long time series of zooplankton monitoring surveys, two types of equipment for depth‐stratified mesozooplankton sampling were compared. The Institute of Marine Research (Norway) has applied the MOCNESS with good results since 1985, but recent events have made it necessary to change to the Multinet Mammoth. During a cruise in March 2019, both sampling devices were calibrated before 17 paired deployments of the 2 gears were undertaken. During each deployment, three nets and depth‐strata covering ~ 425–200, 200–100, and 100–0 m were sampled. All samples were size‐fractionated or taxonomically fractionated into 10 different biomass categories. The results revealed no significant differences between the two gears when comparing total depth‐integrated biomass (2.46 ± 0.36 vs. 2.61 ± 0.59 gDW m−2) or depth‐integrated biomass of any specific biomass category. Running paired t‐tests separately for all combinations of biomass categories and nets, the differences were only significant for zooplankton biomasses in the 180–1000 μm size fraction and only for Net 2. Possible reasons for this result are discussed in the paper. Gears produced similar catches whether sampling during day or night. We conclude that the MOCNESS and Multinet Mammoth in this study provided comparable results regarding abundances of various zooplankton categories.
Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model.
Robust Scheduler Prioritizing UEs with Time-Variant Channels in Small-Delay Slots from Channel Estimation Timing for 5G Large-Scale MU-MIMO

In fifth-generation (5G) mobile communication systems, it is necessary to significantly increase system capacity compared with 4G in order to support rapidly increasing mobile data traffic. The multi-user (MU) MIMO, which spatially multiplexes multiple user equipments (UE) in the same time and frequency resource, is the most promising technology. We have been studying large-scale coordinated MIMO, which uses zero forcing (ZF) precoding at the transmitter side, for a distributed antenna system. However, channel mismatch between channel estimation timing and data transmission timing drastically degrades throughput performance. In this paper, we propose a novel scheduler that preferentially schedules high speed UEs in small-delay slots from channel estimation timing by exploiting the diversity in terms of UE moving speed. The proposed scheduling is realized by the signal to interference plus noise ratio (SINR) prediction from channel variation between two most recent channel estimates and by inputting the predicted SINR into the proportional fairness (PF) scheduler. Computer simulations show that the proposed method significantly improves the mean UE throughput for high speed UEs while keeping almost the same mean UE throughput for low speed UEs.
E-WBM: An Effort-Based Vulnerability Discovery Model

Vulnerability discovery models (VDMs) have recently been proposed to estimate the cumulative number of vulnerabilities that will be disclosed after software is released. A precise VDM would offer an available quantitative insight to assess software security. Even though VDM has demonstrated its effectiveness in multiple software, it remains limited in accuracy, especially with weak versatility. We propose a novel effort-based VDMs, named E-WBM, to improve critical vulnerability discovery rate algorithm using Weibull probability distribution function towards efficient vulnerability discovery models. E-WBM accurately portrays the trend of software security vulnerabilities disclosure. We evaluate E-WBM on eight popular real-world operating systems and show the feasibility of the proposed model. We further compare E-WBM with a state-of-the-art effort-based model AME and time-based model JW on the above eight operating systems. Our comparison also demonstrates that E-WBM consistently outperforms AME and JW both at reducing the deviations and fitting curve trends. In addition to the model fitting, predictive capabilities of two effort-based models E-WBM and AME are also examined. The results show that the E-WBM model yields a more stable prediction with a significantly less error than AME.
Implementation of CART (Classification and Regression Trees) Algorithm for Determining Factors Affecting Employee Performance

The purpose of this research is to identify the problems that affect the performance of employees in the company. This research is a type of quantitative research involving data with different types ranging from nominal, continuous, categorical, ordinal and using 15 independent variables and 1 dependent variable. The population in this research are all employees of some companies in Sukabumi Indonesia. The sample used was 120 employees and the determination of the sample used a random sampling method. Methods of data collection in this study were questionnaires, interviews, and documentation. Data analysis method uses CART (Classification and Regression Trees) algorithm because it involves many kinds of data. The results showed that there are five variables that can be used for work motivation, corporate social environment, job type, leadership style, and organizational support (company policy). From these variables, the best formula can be generated to improve the performance of the employee is: increase the motivation of work (X1), making the company more conducive social environment (x11), divide the types of work (X14), which became more specific to be done individually, and if an employee is required to work in a team, it should be supported by specific policy organization/company (X3). Of the overall variables, the most influential factor in the performance of employees is the motivation of work, when higher the motivation of work, then the possibility of increased employee performance could be higher.
The applications of the general and reduced Yangian algebras

The applications of the general and reduced Yangian Y(sl(2)) and Y(su(3)) algebras are discussed. By taking a special constraint, the representation of Y(sl(2)) and Y(su(3)) can be divided into two 2 \times 2 and three 3 \times 3 blocks diagonal respectively. The general and reduced Yangian Y(sl(2)) and Y(su(3)) are applied to the bi-qubit system and the mixed light pseudoscalar meson state, respectively. We can find that the general ones are not able to make the initial states disentangled by acting on the initial states, however the reduced ones are able to make the initial state disentangled. In addition, we show the effects of Y(su(3)) generators on the the decay channel.
Application of Model -Free Adaptive Control in Managed Pressure Drilling

Aiming at the characteristics of large lag, strong interference, nonlinearity and difficult pressure control in pressure controlled drilling, this paper designs an automatic control system for pressure controlled drilling without model adaptive control. The automatic control system consists of signal input device, pressure controlled drilling electronic control unit, actuator and other devices. In order to improve the speed and stability of pressure control in pressure drilling, a model-free adaptive control scheme is proposed. The control scheme only needs on-line I/O data of the controlled system to complete the design of the controller, which has strong resistance to nonlinearity and is suitable for more complicated control projects. The system is modeled and simulated in MATLAB. The experimental results show that compared with cascade PID control, the pressure regulating time of the automatic control system of pressure controlled drilling using model-free adaptive control scheme is shorter and the pressure change curve is smoother, which can better meet the control requirements of the automatic control system of pressure controlled drilling.
Low Complexity Signal Detection in MIMO Systems

The Maximum Likelihood Detector (MLD) offers an optimal bit-error-ratio for an un-coded multiple-input-multiple-output (MIMO) communication system. The computational complexity, however, of MLD increases significantly for detection of higher order modulated signal streams with multiple transmit antennas. To reduce this complexity while simultaneously also achieving near optimal performance, we propose a novel technique that modifies the sub-optimal Zero Forcing Detector (ZFD) by using the minimum eigen vector of the matrix $\mathbf{HH}^{H}$, where H is the channel matrix and $\mathbf{H}^{H}$ is its Hermitian. The performance in terms of BER and computational complexity of the proposed technique is compared to that of the MLD. Simuations show that the BER performance of the proposed technique is near optimal whereas the computational complexity is signiflcantly reduced.
Geostatistical Predictions Based on Block Data

Block-to-block and block-to-point kriging predictions based on block data are proposed. Blocks may be regular (mesh data) or of more general shapes. Under the assumptions of second-order stationarity and isotropicity, we show how to lessen the number of calculations of relevant block-to-block or block-to-point covariances. As illustrations, a mesh data of population and a simulated block data on convex polygons are analyzed.
Challenges for financial institutes in implementing robust customer due diligence in Pakistan

Purpose This study aims to investigates the challenges faced by Pakistani financial institutes (FIs) and regulators in implementing robust customer due diligence measures. Design/methodology/approach The study adopted a qualitative technique. Twenty-five semi-structured interviews with chief compliance officers and regulators were conducted. Findings The study concluded that the main challenges are name screening, obsolete nature and quality of databases and undocumented, unregistered and unregulated portions of the economy and society. In addition, identification and verification of high-profile customers and beneficial owners, lack of specialised staff and cost of compliance are the significant challenges faced by FIs in Pakistan. Originality/value The Pakistani financial sector is less researched on anti-money laundering front, especially concerning customer due diligence. Further, the social, cultural and economic norms of the Indian sub-continent are more or less the same. Therefore, the study findings could be generalised to the region.
Emojis in Deceptive Online Communication: The Frequency and Type of Emoji in Deceptive and NonDeceptive Online Messages

Little research has been done on nonverbal deception cues in computer-mediated communication (CMC). However, deception is a daily occurrence and since much communication is shifting towards CMC, it is important to understand the difference between truthful and deceptive messages. This research obtained more insight in the use of emoji in deceptive messages by answering the question: Are the frequency and type of emoji different in deceptive compared to truthful online messages? Participants sent three screenshots of deceptive, and truthful messages to WhatsApp. The used emoji were counted and sorted into levels of valence (positive, negative, and neutral) and intensity (strong versus weak). The results indicated that participants used more negative, weak emoji in deceptive compared with truthful messages and more positive, weak, and strong emoji in truth compared with deceit. No difference was found for the emoji frequency. The results are discussed in the light of earlier research. However, this is the first study investigating the use of emoji in the context of computer-mediated deception. The type of emoji can be indicative of used as a nonverbal deception cue in online messages.
Effects of Methods and Durations of Extraction on Total Flavonoid and Phenolic Contents and Antioxidant Activity of Java Cardamom (Amomum compactum Soland Ex Maton) Fruit

Free radicals contribute to the pathophysiology of degenerative diseases which increase mortality globally, including mortality in Indonesia. Amomum compactum Soland. Ex Maton fruit from the Zingiberaceae family, also known as Java cardamom, contains secondary metabolites that have high antioxidant activities. The antioxidant activity of the methanol extract of Java cardamom fruit correlates with its flavonoid and phenolic compound contents, which can be affected by different methods and durations of extraction. This study aimed to measure and compare the effects of extraction methods and durations on total flavonoid and phenolic contents (TFCs and TPCs) and subsequent antioxidant activities by the 2,2′-diphenyl-1-picrylhydrazyl (DPPH) radical, ferric reducing antioxidant power (FRAP), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS), and cupric ion reducing antioxidant capacity (CUPRAC) assays. Methanol extracts of Java cardamom were produced by continuous shaking (CSE), microwave-assisted (MAE), or ultrasonic-assisted extractions (UAE) for three different durations. CSE for 360 min resulted in the highest TFCs (3.202 mg Quercetin Equivalent/g dry weight), while the highest TPCs (1.263 mg Gallic Acid Equivalent/g dry weight) were obtained by MAE for 3 min. Out of the investigated methods, MAE for 3 min resulted in the highest antioxidant activity results for the extracts. We conclude that the polyphenolic antioxidant yield of Java cardamom depends on two parameters: the method and the duration of extraction.
Manifolds and modular forms

During the winter term 1987/88 I gave a course at the University of Bonn under the title "Manifolds and Modular Forms. " Iwanted to develop the theory of "Elliptic Genera" and to leam it myself on this occasion. This theory due to Ochanine, Landweber, Stong and others was relatively new at the time. The word "genus" is meant in the sense of my book "Neue Topologische Methoden in der Algebraischen Geometrie" published in 1956: A genus is a homomorphism of the Thom cobordism ring of oriented compact manifolds into the complex numbers. Fundamental examples are the signature and the A-genus. The A-genus equals the arithmetic genus of an algebraic manifold, provided the first Chem class of the manifold vanishes. According to Atiyah and Singer it is the index of the Dirac operator on a compact Riemannian manifold with spin structure. The elliptic genera depend on a parameter. For special values of the parameter one obtains the signature and the A-genus. Indeed, the universal elliptic genus can be regarded as a modular form with respect to the subgroup r (2) of the modular group; the two cusps o giving the signature and the A-genus. Witten and other physicists have given motivations for the elliptic genus by theoretical physics using the free loop space of a manifold.
(g−2)μ and Δα: recent developments and status report

We briefly review the Standard Model prediction of g−2 and confront it with the formidably accurate measurement from BNL. The focus is on recent improvements of the hadronic vacuum polarisation contributions. We also calculate the running QED coupling at the scale of the Z boson mass, α(MZ2), an important ingredient in electroweak precision fits.
Asynchronous Tracking Control of Amplitude Signals in Vibratory Gyroscopes With Partially Unknown Mode Information

Vibratory gyroscopes are the most ideal inertial sensors in the 21st century. The amplitude is an important index of vibratory gyroscopes. This article investigates an asynchronous tracking control approach for amplitude signals in vibratory gyroscopes. Since the manufacturing error of vibratory gyroscopes can result in the stochastic signal of the amplitude, Markov stochastic systems are adopted to approximate vibratory gyroscopes. Because the stochastic signal results in the amplitude jitter, a novel doubly fed tracking controller with the stochastic stability performance is proposed for reducing the amplitude jitter. In the practical application, regarding the known degree of the stochastic process, the partially unknown mode information is approximately given. By considering the asynchronous phenomenon between the system mode and controller mode, a hidden Markov model is constructed to name the resultant tracking error system. It is proved that the tracking error system is stochastically stable. Furthermore, the presented asynchronous tracking controller can well track the reference amplitude signal and significantly reduce the amplitude jitter. Finally, comparative results show the control precision of amplitude signals is significantly improved such that the better precision and performance of vibratory gyroscopes are achieved, which demonstrates the effectiveness and practicability of the proposed control approach.