Isolation endophytic bacteria from elephant grass (pennisetum purpureum schumach) and their potential application

In this study, 25 endophytic bacteria were isolated and purified from rhizome, stem and leaf of the elephant grass, which were tested for their biological control properties. The number of living and dead brown plant hoppers were recorded and the mortality rate was analyzed by using Abbott’s formula. The results indicated that three endophytic bacteria including VBL1, VBT1 and VBT5 showed the highest biological control of Nilaparvata lugens at the mortality rate 46.95%, 55.02% and 55.02%, respectively after 8 days of screening and significant difference compared to other isolates (

Numerical modeling of thermal dust polarization from aligned grains in the envelope of evolved stars with updated POLARIS

Magnetic fields are thought to influence the formation and evolution of evolved star envelopes. Thermal dust polarization from magnetically aligned grains is potentially a powerful tool for probing magnetic fields and dust properties in these circumstellar environments. In this paper, we present numerical modeling of thermal dust polarization from the envelope of IK Tau using the magnetically enhanced radiative torque (MRAT) alignment theory implemented in our updated POLARIS code. Due to the strong stellar radiation field, the minimum size required for RAT alignment of silicate grains is $\sim 0.005 - 0.05\,\rm\mu m$. Additionally, ordinary paramagnetic grains can achieve perfect alignment by MRAT in the inner regions of $r < 500\,\rm au$ due to stronger magnetic fields of $B\sim 10$ mG - 1G, producing thermal dust polarization degree of $\sim 10\,\%$. The polarization degree can be enhanced to $\sim 20-40\%$ for grains with embedded iron inclusions. We also find that the magnetic field geometry affects the alignment size and the resulting polarization degree due to the projection effect in the plane-of-sky. We also study the spectrum of polarized thermal dust emission and find the increased polarization degree toward $\lambda > 50\,\rm\mu m$ due to the alignment of small grains by MRAT. Furthermore, we investigate the impact of rotational disruption by RATs (RAT-D) and find the RAT-D effect cause a decrease in the dust polarization fraction. Finally, we compare our numerical results with available polarization data observed by SOFIA/HAWC+ for constraining dust properties, suggesting grains are unlikely to have embedded iron clusters and might have slightly elongated shapes. Our modeling results suggest further observational studies at far-infrared/sub-millimeter wavelengths to understand the properties of magnetic fields and dust in AGB envelopes.Comment: 27 pages, 23 figures, 1 table, to be submitte

Energy Transformer

Transformers have become the de facto models of choice in machine learning, typically leading to impressive performance on many applications. At the same time, the architectural development in the transformer world is mostly driven by empirical findings, and the theoretical understanding of their architectural building blocks is rather limited. In contrast, Dense Associative Memory models or Modern Hopfield Networks have a well-established theoretical foundation, but have not yet demonstrated truly impressive practical results. We propose a transformer architecture that replaces the sequence of feedforward transformer blocks with a single large Associative Memory model. Our novel architecture, called Energy Transformer (or ET for short), has many of the familiar architectural primitives that are often used in the current generation of transformers. However, it is not identical to the existing architectures. The sequence of transformer layers in ET is purposely designed to minimize a specifically engineered energy function, which is responsible for representing the relationships between the tokens. As a consequence of this computational principle, the attention in ET is different from the conventional attention mechanism. In this work, we introduce the theoretical foundations of ET, explore it's empirical capabilities using the image completion task, and obtain strong quantitative results on the graph anomaly detection task

FPGA-Based Multiple DDoS Countermeasure Mechanisms System Using Partial Dynamic Reconfiguration

In this paper, we propose a novel FPGA-based high-speed DDoS countermeasure system that can flexibly adapt to DDoS attacks while still maintaining system performance. The system includes a packet decoder module and multiple DDoS countermeasure mechanisms. We apply dynamic partial reconfiguration technique in this system so that the countermeasure mechanisms can be flexibly changed or updated on-the-fly. The proposed system architecture separates DDoS protection modules (which implement DDoS countermeasure techniques) from the packet decoder module. By using this approach, one DDoS protection module can be reconfigured without interfering with other modules. The proposed system is implemented on a NetFPGA 10G board. The synthesis results show that the system can work at up to 116.782 MHz while utilizing up to 39.9% Registers and 49.85% BlockRAM of the Xilinx Virtex xcv5tx240t FPGA device on the NetFPGA 10G board. The system achieves the detection rate of 100% with the false negative rate at 0% and false positive rate closed to 0.16%. The prototype system achieves packet decoding throughput at 9.869 Gbps in half-duplex mode and 19.738 Gbps in full-duplex mode

A comparison between Hydrochloric acid and Trifluoroacetic acid in hydrolysis method of exopolysaccharide from Ophiocordyceps sinensis in Monosaccharide composition analysis by GC-FID

The monosaccharide composition is one of the crucial factors affecting the bioactivity of exopolysaccharide (EPS) in Cordyceps species. Therefore, many scientists have studied, analyzed monosaccharide composition and structure of EPS from Cordyceps species, especially Ophiocordyceps sinensis (O. sinensis). This study aimed to compare hydrochloric acid (HCl) with trifluoroacetic acid (TFA) in the EPS hydrolysis process in monosaccharide composition analysis by Gas Chromatography with Flame-Ionization Detection (GC-FID). The hydrolysis is a crucial step in forming the acetyl derivative, which helps the GC-FID technique to have good results in monosaccharide composition analysis. The results showed that hydrolysis with HCl gave a higher hydrolysis efficiency and was more suitable than hydrolysis by TFA in pretreatment to EPS for GC-FID. Hydrolysis results were analyzed through thin-layer chromatography and high-performance liquid chromatography (HPLC), then Acetyl derivatives were produced and finally analyzed by GC-FID to determine the monosaccharide composition of EPS. For EPS hydrolyzed by HCl, the analytical results presented that this sample had 6 kinds of monosaccharides, including rhamnose, arabinose, xylose, mannose, glucose, and galactose; the most monosaccharide was glucose. The EPS hydrolyzed by TFA only detected three kinds of monosaccharides, including mannose, arabinose, and galactose, mainly mannose. The study has set a foundation for further analysis of monosaccharide composition and structure of EPS from O. sinensis

Studying Magnetic Fields and Dust in M17 Using Polarized Thermal Dust Emission Observed by SOFIA/HAWC

We report on the highest spatial resolution measurement to date of magnetic fields (B-fields) in M17 using thermal dust polarization measurements taken by SOFIA/HAWC+ centered at a wavelength of 154 μm. Using the Davis–Chandrasekhar–Fermi method, in which the polarization angle dispersion calculated using the structure function technique is the quantity directly observed by SOFIA/HAWC+, we found the presence of strong B-fields of 980 ± 230 and 1665 ± 885 μG in the lower-density M17-N and higher-density M17-S regions, respectively. The B-field morphology in M17-N possibly mimics the fields in gravitationally collapsing molecular cores, while in M17-S the fields run perpendicular to the density structure. M17-S also displays a pillar feature and an asymmetric large-scale hourglass-shaped field. We use the mean B-field strengths to determine Alfvénic Mach numbers for both regions, finding that B-fields dominate over turbulence. We calculate the mass-to-flux ratio, λ, finding λ = 0.07 for M17-N and 0.28 for M17-S. These subcritical λ values are consistent with the lack of massive stars formed in M17. To study dust physics, we analyze the relationship between dust polarization fraction, p, emission intensity, I, gas column density, N(H2), polarization angle dispersion function, S, and dust temperature, T d. p decreases with intensity as I −α with α = 0.51. p tends to first increase with T d, but then decreases at higher T d. The latter feature, seen in M17-N at high T d when N(H2) and S decrease, is evidence of the radiative torque disruption effect

The 80-year development of Vietnam mathematical research: Preliminary insights from the SciMath database on mathematicians, their works and their networks

Starting with the first international publication of Le Van Thiem (Lê Văn Thiêm) in 1947, modern mathematics in Vietnam is a longstanding research field. However, what is known about its development usually comes from discrete essays such as anecdotes or interviews of renowned mathematicians. We introduce SciMath—a database on publications of Vietnamese mathematicians. To ensure this database covers as many publications as possible, data entries are manually collected from scientists’ publication records, journals’ websites, universities, and research institutions. Collected data went through various verification steps to ensure data quality and minimize errors. At the time of this report, the database covered 8372 publications, profiles of 1566 Vietnamese, and 1492 foreign authors since 1947. We found a growing capability in mathematics research in Vietnam in various aspects: scientific output, publications on influential journals, or collaboration. The database and preliminary results were presented to the Scientific Council of Vietnam Institute for Advanced Study in Mathematics (VIASM) on November 13th, 2020

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions