Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Involvement of Type 1 IFN Choriomeningitis Virus Infection of Mice: Subsets following Lymphocytic Rapid Activation of Spleen Dendritic Cell

In this study, we report the dynamic changes in activation and functions that occur in spleen dendritic cell (sDC) subsets following infection of mice with a natural murine pathogen, lymphocytic choriomeningitis virus (LCMV). Within 24 h postinfection (pi), sDCs acquired the ability to stimulate naive LCMV-speciﬁc CD8 (cid:1) T cells ex vivo. Conventional (CD11c high CD8 (cid:1) and CD4 (cid:1) ) sDC subsets rapidly up-regulated expression of costimulatory molecules and began to produce proinﬂammatory cytokines. Their tendency to undergo apoptosis ex vivo simultaneously increased, and in vivo the number of conventional DCs in the spleen decreased markedly, dropping (cid:1) 2-fold by day 3 pi. Conversely, the number of plasmacytoid (CD11c low B220 (cid:1) ) DCs in the spleen increased, so that they constituted almost 40% of sDCs by day 3 pi. Type 1 IFN production was up-regulated in plasmacytoid DCs by 24 h pi. Analysis of DC activation and maturation in mice unable to respond to type 1 IFNs implicated these cytokines in driving infection-associated phenotypic activation of conventional DCs and their enhanced tendency to undergo apoptosis, but also indicated the existence of type 1 IFN-independent pathways for the functional maturation of DCs during LCMV infection. The Journal of Immunology, 2005, 174: 1851–1861.
Retraction Retracted : Technique of Intravesical Laparoscopy for Ureteric Reimplantation to Treat VUR Advances in Urology

The article titled “Technique of Intravesical Laparoscopy for Ureteric Reimplantation to Treat VUR” [1] has been retracted as it was found to be substantially similar to a previously published article by the same authors. The first article, “Laparoscopy in the management of pediatric vesicoureteral reflux,” by Atul A. Thakre, B. Sreedhar, and C. K. Yeung was published in Indian J Urol. 2007 Oct–Dec; 23(4): 414– 419, while the second article, “Technique of Intravesical Laparoscopy for Ureteric Reimplantation to Treat VUR” was published in Advances in Urology in June 2008.
OPTIMIZATION OF TRITERPENOIDS EXTRACTION FROM VIETNAMESE GANODERMA LUCIDUM USING RESPONSE SURFACE METHODOLOGY AND ANTICANCER EVALUATION OF THE EXTRACT

Triterpenoids are considered to be the major pharmaceutical active compounds found in the macrofungus Ganoderma lucidum (G. lucidum). Extraction conditions of triterpenoids from the Vietnamese red G. lucidum were optimized by response surface methodology using ultrasound –assisted extraction (UAE) method. A Box – Behnken experimental design was used to determine the simultaneous influences of three independent variables, namely solvent-tomaterial ratio, extraction time, and ultrasonic power on the yield of triterpenoids. The highest yield of triterpenoids obtained under optimum conditions including extraction time of 55 min, ultrasonic power of 480 W, solvent-to-material ratio of 27:1 mL/g was 9.5768 ± 0.228 mg/g according to ultraviolet-visible spectroscopy (UV-Vis) analysis. Besides, the hot water extraction method was carried out in order to compare with UAE in terms of the yield of triterpenoids. The results of anticancer evaluation of the extract obtained indicated that with the half-maximal inhibitory concentration value of 67.25 ± 0.82 μg/mL on the human Hep-G2 liver cancer cell lines, triterpenoids extracted from G. lucidum could be regarded as a potential agent for medicinal treatment.
The Impact of Flaky Tests on Historical Test Prioritization on Chrome

Test prioritization algorithms prioritize probable failing tests to give faster feedback to developers in case a failure occurs. Test prioritization approaches that use historical failures to run tests that have failed in the past may be susceptible to flaky tests as these tests often fail and then pass without identifying a fault. Traditionally, flaky failures like other types of failures are considered blocking, i. e. a test that needs to be investigated before the code can move to the next stage. However, on Google Chrome, flaky failures are non-blocking and the code still moves to the next stage in the CI pipeline. In this work, we explain the Chrome testing pipeline and classification. Then, we re-implement two important history based test prioritization algorithms and evaluate them on over 276 million test runs from the Chrome project. We apply these algorithms in two scenarios. First, we consider flaky failures as blocking and then, we use Chrome's approach and consider flaky failures as non-blocking. Our investigation reveals that 99.58% of all failures are flaky. These types of failures are much more repetitive than non-flaky failures, and they are also well distributed over time. We conclude that the prior performance of the prioritization algorithms have been inflated by flaky failures. We release our data and scripts in our replication package [8].
Probe-based Syscall Tracing for Efficient and Practical File-level Test Traces

Efficiently collecting per-test execution traces is a common prerequisite of dynamic regression test optimization techniques. However, as these test traces are typically recorded through language-specific code instrumentation, non-code artifacts and multi-language source code are usually not included. In contrast, more complete test traces can be obtained by instrumenting operating system calls and thereby tracing all accessed files during a test’s execution. Yet, existing test optimization techniques that use syscall tracing are impractical as they either modify the Linux kernel or operate in user space, thus raising transferability, performance, and security concerns. Recent advances in operating system development provide versatile, lightweight, and safe kernel instrumentation frameworks: They allow to trace syscalls by instrumenting probes in the operating system kernel. Probe-based Syscall Tracing (ProST), our novel technique, harnesses this potential to collect file-level test traces that go beyond language boundaries and consider non-code artifacts. To evaluate ProST’s efficiency and the completeness of obtained test traces, we perform an empirical study on 25 multi-language open-source software projects and compare our approach to existing language-specific instrumentation techniques. Our results show that most studied projects use source files from multiple languages (22/25) or non-code artifacts during testing (22/25) that are missed by language-specific techniques. With the low execution time overhead of 4.6% compared to non-instrumented test execution, ProST is more efficient than language-specific instrumentation. Furthermore, it collects on average 89% more files on top of those collected by language-specific techniques. Consequently, ProST paves the way for efficiently extracting valuable information through dynamic analysis to better understand and optimize testing in multi-language software systems. CCS CONCEPTS • Software and its engineering → Software testing and debugging.
Comparing and Combining Analysis-Based and Learning-Based Regression Test Selection

Regression testing–rerunning tests on each code version to detect newly–broken functionality-is important and widely practiced. But, regression testing is costly due to the large number of tests and the high frequency of code changes. Regression test selection (RTS) optimizes regression testing by only rerunning a subset of tests that can be affected by changes. Researchers showed that RTS based on program analysis can save substantial testing time for (medium-sized) open-source projects. Practitioners also showed that RTS based on machine learning (ML) works well on very large code repositories, e.g., in Facebook’s monorepository. We combine analysis-based RTS and ML-based RTS by using the latter to choose a subset of tests selected by the former. We first train several novel ML models to learn the impact of code changes on test outcomes using a training dataset that we obtain via mutation analysis. Then, we evaluate the benefits of combining ML models with analysis-based RTS on 10 projects, compared with using each technique alone. Combining ML-based RTS with two analysis-based RTS techniques-Ekstazi and STARTS-selects 25.34% and 21.44% fewer tests, respectively. CCS CONCEPTS • Software and its engineering $\rightarrow$Software testing and debugging.
MetaBoost: A Novel Heterogeneous DCNNs Ensemble Network With Two-Stage Filtration for SAR Ship Classification

Current synthetic aperture radar (SAR) ship classification research mainly focuses on modifying deep convolutional neural networks (DCNNs) and injecting manual features on DCNNs. Yet, the weak robustness of individual models in high-risk scenarios makes it difficult to gain the trust of SAR experts. In this letter, an automated method of heterogeneous DCNNs model ensemble based on two-stage filtration (MetaBoost) is proposed, effectively achieving robustness and high accuracy recognition on SAR ship classification. The principle of MetaBoost is generating a pool of diverse heterogeneous classifiers, selecting a subset of the most diverse and accurate classifiers, and finally fusing meta-features from the optimal subset. MetaBoost is a self-configuring algorithm that automatically determines the optimal type and the number of base classifiers to be combined. Extensive experiments on the OpenSARShip and FUSAR-Ship datasets show that MetaBoost significantly outperforms individual classifiers, traditional ensemble models, and feature injection techniques.
Estimating the VIIRS Thermal Emissive Band Response Versus Scan (RVS) and Calibration Offsets Using On-Orbit Pitch Maneuver Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (S-NPP) and the National Oceanic and Atmospheric Administration - 20 (NOAA-20) satellites. This study presents a method for estimating VIIRS Thermal Emissive Bands (TEB) Response Versus Scan (RVS) and calibration offsets simultaneously using on-orbit pitch maneuver data (METHOD2021). Raw Earth View (EV) RVS is estimated using an existing method (METHOD2019), with prelaunch RVS and calibration offsets as first guesses. Errors in the calibration offset are derived based on a prelaunch data-based assumption. Moreover, RVS and calibration offsets are optimized iteratively using the updated calibration coefficients until results converge. Compared to the METHOD2019, the METHOD2021 derived RVS is not affected by errors in the calibration offsets. Evaluation results using independent co-located Cross-track Infrared Sounder (CrIS) observations indicate that the METHOD2021 could effectively mitigate NOAA-20 scan angle and scene temperature dependent biases in M15-M16 and I5, as well as the cold bias in S-NPP M15. S-NPP TEB striping at cold scene temperatures can also be significantly reduced. Furthermore, NOAA-20 I5 and M15 measurements become more in family with S-NPP VIIRS and other radiometers at extremely low temperatures. Our analysis indicates that the impacts of the METHOD2021 and METHOD2019 on TEB SDRs are generally comparable. The METHOD2019 is simpler, while the METHOD2021 better explains the root causes of the VIIRS TEB scan angle and scene temperature dependent biases. Both can be used for improving VIIRS TEB on-orbit calibration, especially at cold scenes.
CAR-Lite: A Multi-Rate Cochlear Model on FPGA for Spike-Based Sound Encoding

Filters in cochlear models use different coefficients to break sound into a 2-D time-frequency representation. On digital hardware with a single sampling rate, the number of bits required to represent these coefficients requires substantial computational resources such as memory storage. In this paper, we present a cochlear model operating at multiple sampling rates. As a result, fewer bits are required to represent filter coefficients on hardware as opposed to all the filters operating at a single sampling rate; with a 108-filter cochlear implementation, up to nine times fewer coefficients are needed. We present an implementation of this model in Matlab and on an Altera Cyclone V field-programmable gate array. We also demonstrate the capability of our model to encode sound at various intensity levels and with real-world signals.
The Implications of Integrating the Theory of Multiple Intelligences into English Language Learning Methodologies

The achievement gap between English Language Learners and their peers has emerged as a problem in our nation's school system. Although the Theory of Multiple Intelligences has been used in education, it is not often applied to English Language Learners. This research analyzed the application of Multiple Intelligence Theory as it pertained to the achievement of EL’s. The results show that by using MI to dictate what teaching method to use, EL’s benefited both socio-emotionally and academically. Overall, the findings show the importance of 1) ESL training for all teachers, 2) the consideration of students' Funds of Knowledge, and 3) the incorporation of MI in classrooms.
Institut de Science Financière et d’Assurances T HE WIN - FIRST PROBABILITY UNDER INTEREST FORCE

In a classical risk model under constant interest force, we study the probability that the surplus of an insurance company reaches an upper barrier before a lower barrier. We deﬁne this probability as win-ﬁrst probability. Borrowing ideas from life-insurance theory, hazard rates of the maximum of the surplus before ruin, re-garded as a remaining future lifetime random variable, are studied, and provide an original derivation of the win-ﬁrst probability. We propose an algorithm to eﬃ-ciently compute this risk-return indicator and its derivatives in the general case, as well as bounds of these quantities. The eﬃciency of the proposed algorithm is compared with adaptations of other existing methods, and its interest is illustrated by the computation of the expected amount of dividends paid until ruin in a risk model with a dividend barrier strategy.
AABC_A_360787 21..27

Purpose: Spike protein on SARS-CoV-2 virus plays an integral part during infection as cell entry depends on binding of this protein to human ACE2 receptor. Understanding of infectivity by these variants necessitates a comparative structural analysis of complexes of spike protein-receptor binding domain (RBD) of these variants to receptor. Methodology: Wild type SARS-CoV-2 spike protein sequence was retrieved from the UniProt database, and mutations of five variants at receptor binding domain were manually incorporated and aligned using Clustal Omega. Crystal structure complexes of human ACE2 receptor with spike protein RBD domain of SARS-CoV-2 variants of wild type, α, β, and δ were extracted from the RCSB database. Wild type SARS-CoV-2 complex with receptor was used as template to generate model complexes of receptor with spike protein RBD of γ and omicron variants through WinCoot program. These were energy minimized and validated and molecular dynamic simulation was performed using Desmond simulation program. Results: Mutations are distributed across the entire length of RBD, but the maximum number of mutations are seen at 11 positions within binding interfacemotifs of six variant sequences. Interface of spike protein RBDswith humanACE2-receptor shows different mix of hydrogen bonded and ionic interactions. Alpha and β variants have few interactions, while γ and δ variants have higher number of interactions compared to wild type variant. Omicron variant, with 10 polar interactions including two ionic bonds, has the highest binding energy. Conclusion: Different mutations on RBD of spike protein results in varying quantity and quality of interactions, thereby affecting potency of each variant. Variations in binding are due to interactions of mutant residues and induced conformational changes on loops of RBDs. Variants α and β have a low potency, while, γ, δ, and omicron have a higher potency. These results correlate with viral infectivity and place clinical observations in the right perspective.
Developing the Dimensions of a Social Content Management Framework

The rise of social media has transformed the way of collaboration between organisations and customers. Social content resulting from the active collaboration between both parties on a social media platform should be managed accordingly. Thus, a social content management (SCM) framework should be developed as a guide to manage the social content. Such SCM framework should be able to augment existing frameworks, which mainly focuses on the value of social content for the organisations. Hence, based on the service science perspective, this article proposes a SCM framework that focusses on value to both organisations and its customers. In order to do this, the concept of Service Dominant Logic and the DART model are adopted to explore and extract the elements and factors that collectively become the dimensions of the proposed SCM framework. Experts’ review of the elements and factors is conducted to ensure that the dimensions in the SCM framework are acceptable and have practical value. The proposed framework is then validated via an instrument whose content validity is investigated by using Lawshe’s Technique. This framework could assist the organisations in decision-making process towards innovating services and in the management of social content.
Your Board Independence and CEO Turnover

It is widely believed that the ideal board in corporations is composed almost entirely of independent (outside) directors. In contrast, this paper shows that some lack of board independence can be in the interest of shareholders. This follows because a lack of board independence serves as a substitute for commitment. Boards that are dependent on the incumbent CEO adopt a less aggressive CEO replacement rule than independent boards. While this behavior is inefficient ex post, it has positive ex ante incentive effects. The model suggests that independent boards (dependent boards) are most valuable to shareholders if the problem of providing appropriate incentives to the CEO is weak (severe).
Wearable Sensor for Measurement of Gait Walking and Running Motion

In this work, we developed a smart wearable device for gait speed measurement with dual wireless communication on the feet by using an inertia measurement unit (IMU) sensor. To discover step counts and speed information, pitch and yaw angles were calculated successfully from IMU signals using a Kalman filter and a moving average algorithm. Walking step counts were calculated using the sensor; the results demonstrated almost zero errors and averaged more than 90% accuracy in walking and running measurements. The observable speed for two-foot indication and adapted variation can be implemented on the sensor to gauge walking and running speeds for different subjects. Step counts and the swing frequency were tested and compared with results over a treadmill using a commercial chip in the insole of a shoe. Experimental results were validated using fast Fourier transform from the acquired pitch angle history. The pitch and yaw angles of users’ tibias can be used as controllable monitoring tags for personal health information in the future.
Insulating barriers efficiency on the dielectric strength of organic ester oil gaps

The article deals with the influence of the position and shape of insulating barrier on the dielectric strength of cone-plane electrode arrangement immersed in natural ester oil. It is shown that the effectiveness of the barrier is the highest when the barrier is located at the tip of cone electrode whatever the electrode gaps and/or the shape of barrier
Numerical Modeling of Spectral Hardening at a Finite-width Shock

Spectral hardening has been identified in solar flare hard X-ray observations for several decades and remains a puzzle. We examine spectral hardening under the diffusive shock acceleration mechanism using numerical simulations. The hardening is related to the finite width of the shock and is controlled by the shock Péclet number. We implement two different types of Monte Carlo simulations. The first is based on the backward stochastic differential equation method, where the Parker transport equation is solved by casting it to a set of stochastic different equations, and by following the trajectories of individual quasiparticles. In the second approach, we follow real particles and particles are assumed to move freely between scatterings from magnetic turbulence in the plasma. The scattering is modeled as either large-angle hard-sphere elastic collision, or small-angle pitch-angle scattering. We show that the results from these two approaches agree well with each other and agree with analytical results. We also use a Pan-spectrum form to fit the resulting spectra.
Three-month Monitoring of the Variability toward W51 IRS2 with Ammonia, Water, and Methanol Transitions

A four-epoch monitoring program spanning ∼three months (from 2020 January 8 to April 7) for ammonia, water, and methanol transitions toward the high-mass star-forming region W51 IRS2 was conducted using the Shanghai 65 m Tianma Radio Telescope with its K-band (18–26.5 GHz) receiver. In total, 33 ammonia transitions and 16 methanol transitions were detected toward the target at least once during this monitoring program. Among them, 14 ammonia and 4 methanol transitions show maser emission characteristics. Rapid variabilities (including both increases and decreases) in the ammonia and methanol transitions were detected from both maser and thermal emissions during the three months of the monitoring. In addition, H2O masers with obvious variability were also detected. The results of the rotation diagram analysis for the ammonia and methanol quasi-thermal transitions show the variations in their rotational temperatures during the monitoring. The derived temperatures from the transitions with larger upper energies (E u /κ) generally decreased over the whole monitoring period, from January 8 to April 7, but those with smaller E u /κ first increased from January 8 to April 1, then rapidly decreased from April 1 to April 7. These findings support the suggestion that an inside-out heatwave propagation in W51 IRS2 was involved with the accretion burst over a short duration (only on the order of months) and caused the drastic variability behaviors of the different line transitions during high-mass star formation.
Quench dynamics of the Anderson impurity model at finite temperature using matrix product states: entanglement and bath dynamics

We study the dynamics of the quenched Anderson model at finite temperature using matrix product states (MPSs). Exploiting a chain mapping for the electron bath, we investigate the entanglement structure in the MPS for various orderings of the two chains, which emerge from the thermofield transformation employed to deal with nonzero temperature. We show that merging both chains can significantly lower the entanglement at finite temperatures as compared to an intuitive nearest-neighbor implementation of the Hamiltonian. Analyzing the population of the free bath modes—possible when simulating the full dynamics of impurity plus bath—we find clear signatures of the Kondo effect in the quench dynamics.