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Twenty three different Xylariaceae Tul. & C. Tul were isolated from samples collected from forest zones of Thailand and Philippines. The fungal samples were characterized based on morphological characteristics and nuclear ITS1-5.8S rDNA-ITS2 region sequences. Ten species of Xylaria, two species of Hypoxylon, Biscogniauxia, Rosellinia and one species of Annulohypoxylon and Entonaema were found. Entonaema the distinctive genus of Xylariaceae, isolated in the study from Thailand samples showed a close relationship withXylaria in phylogenetic tree. Xylariaceous species identified at molecular level showed significant similarity of the morphological characters, such as stromal structure, ascal apex and the germ slit of ascospores. In addition, three species of Arthrinium, two species of Pestalotiopsis were also isolated and characterized in the study. A phylogenetic affinity of Pestalotiopsis with Xylariaceae was found.

This paper presents a Q-learning-based pending zone adjustment for received signal strength indicator (RSSI)-based proximity classification (QPZA). QPZA aims to improve the accuracy of RSSI-based proximity classification by adaptively adjusting the size of the pending zone, taking into account changes in the surrounding environment. The pending zone refers to an area in which the previous result of proximity classification is maintained and is expressed as a near boundary and a far boundary. QPZA uses Q-learning to expand the size of the pending zone when the noise level increases and reduce it otherwise. Specifically, it calculates the noise level using the estimation error of a device deployed at a specific location. Then, QPZA adjusts the near boundary and far boundary separately by inputting the noise level into the near and far boundary adjusters, consisting of the Q-learning agent and reward calculator. The Q-learning agent determines the next boundary using the Q-table, and the reward calculator calculates the reward using the noise level. QPZA updates the Q-table of the Q-learning agent using the reward. To evaluate the performance of QPZA, we conducted an experimental implementation and compared the accuracy of QPZA with that of the existing approach. The results showed that QPZA achieves 11.69% higher accuracy compared to the existing approach, on average. [ABSTRACT FROM AUTHOR]

This study aims at identifying the optimal fermentation temperature for dry-fermented sausage using strains isolated from Kimchi (GK1, Pediococcus pentosaceus-GK1; NK3, P. pentosaceus-NK3), Doenjang (D1, Debaryomyces hansenii-D1), and commercial fermented sausage (S6, spontaneously generated Penicillium nalgiovense-S6). The microbial population, pH, moisture content, color, thiobarbituric acid reactive substance (TBARS), volatile basic nitrogen (VBN), and electronic nose (E-nose) were analyzed to identify the optimal fermentation temperature. The dry-fermented sausages were inoculated with three types of starter cultures [CS (commercial starter culture), GD (GK1 + D1 + S6), and ND (NK3 + D1 + S6)]. The fermentation was performed for 3 days at 20 °C and 25 °C, and dried for 28 days. The Lactobacillus spp. plate count and TBARS showed significantly higher values in the 25 °C group than in the 20 °C group (p < 0.05). The Staphylococcus spp. plate count of GD and ND were significantly higher than CS group at all temperatures. On day 31, the moisture content and VBN values of all groups were less than 35 % and 20 mg%, respectively. According to E-nose, the highest amount of acetoin was detected at the GD group fermented at 25 °C. Thus, the optimal fermentation temperature is expected at 25 °C after using GD in the manufacturing of dry-fermented sausages. [ABSTRACT FROM AUTHOR]

2D semiconductor devices have been studied due to their unique potential in architecture and properties. As one of the unique devices approaches, 2D hetero‐stack channel field‐effect transistors (FETs) have recently been reported, but homo‐stack FETs are rare to find. Here, MoSe2/MoSe2 homo‐stack transistors are rather fabricated for study. Unlike the equivalently‐thick single MoSe2 FET, homo‐stack FETs show n‐type memory behavior that originates from stack interface‐induced traps. Particularly, when their stack interfaces are engineered by surface oxidation of bottom MoSe2, more stable nonvolatile memory behavior turns out. Short‐term ultraviolet ozone (UVO)‐induced oxidation only results in n‐type memory, but 15 min‐long oxidation surprisingly enables both n‐ and p‐type nonvolatile memory behavior due to nm‐thin MoOx embedded between upper and lower MoSe2. Furthermore, by alternating gate voltage pulse to the 15 min‐long UVO‐treated FETs, channel polarity conversion appears reversible in a small gate voltage (VGS) sweep range, which means that the channel type of a transistor can be reversibly modulated via stack interface engineering. It is believed that homo‐stack interface engineering must be one of the approaches to maximize the potential of 2D devices. [ABSTRACT FROM AUTHOR]

Achieving high-performance electromagnetic interference (EMI) shielding materials with ultra-low reflectivity, minimal volume, and light weight is challenging. This study addresses this by introducing a nanofiber (NF)-based structure composed of MXene nanoflakes and ferroelectric barium titanate oxide (BTO) nanoparticles embedded within polyurethane (PU) fibers, and surface-bound branched polyethyleneimine (PEI(b)) on the NFs. This design enhances the flexibility and lightness of the EMI shielding materials while effectively minimizing reflectivity. A key approach in this study is the functionalization of the NFs with branched polyethyleneimine (PEI(b)), which reduces reflectivity and enhances EMI shielding effectiveness (SE). The surface-bound molecules increase the effective surface area, improving the absorption efficiency of incident electromagnetic waves without adding weight or volume. Additionally, the surface-bound PEI(b) molecules synergistically enhance the polarization of the embedded BTO nanoparticles and amplify the triboelectric charging effect, crucial for achieving ultra-low reflectivity and high EMI SE. Combining the optimized composite NF design with these enhancement methods, this study achieves significant advancements in EMI SE, reaching an EMI SE of 72 dB, an absolute EMI SE (SSE t) of 28,460 dB·cm²g−1, and a reflectivity of 0.09, all without increasing weight or volume. This approach exemplifies how the strategic application of surface-bound molecules can enhance EMI shielding effectiveness and achieve ultra-low reflectivity through the effective expansion of the absorption surface and synergistic enhancement of piezoelectric and triboelectric effects. [Display omitted] • To achieve ultra-low reflectivity and high EMI SE, the surface of the composite NFs was functionalized with PEI(b) molecules. • These surface-bound molecules expanded the surface area and synergistically improved polarization and triboelectrification. • The optimized material achieved a SSEt of 28,460 dB·cm²·g⁻¹ with a low reflectivity of 0.09, offering a promising approach for developing high-performance ultra-low reflective EMI shielding materials. [ABSTRACT FROM AUTHOR]