A new root-knot nematode, Meloidogyne moensi n. sp. (Nematoda : Meloidogynidae), parasitizing Robusta coffee from Western Highlands, Vietnam

A new root-knot nematode, parasitizing Robusta coffee in Dak Lak Province, Western Highlands of Vietnam, is described as Meloidogyne moensi n. sp. Morphological and molecular analyses demonstrated that this species differs clearly from other previously described root-knot nematodes. Morphologically, the new species is characterized by a swollen body of females with a small posterior protuberance that elongated from ovoid to saccate; perineal patterns with smooth striae, continuous and low dorsal arch; lateral lines marked as a faint space or linear depression at junction of the dorsal and ventral striate; distinct phasmids; perivulval region free of striae; visible and wide tail terminus surrounding by concentric circles of striae; medial lips of females in dumbbell-shaped and slightly raised above lateral lips; female stylet is normally straight with posteriorly sloping stylet knobs; lip region of second stage juvenile (J2) is not annulated; medial lips and labial disc of J2 formed dumbbell shape; lateral lips are large and triangular; tail of J2 is conoid with rounded unstriated tail tip; distinct phasmids and hyaline; dilated rectum. Meloidogyne moensi n. sp. is most similar to M. africana, M. ottersoni by prominent posterior protuberance. Results of molecular analysis of rDNA sequences including the D2-D3 expansion regions of 28S rDNA, COI, and partial COII/16S rRNA of mitochondrial DNA support for the new species status

Differential spatial modulation for high-rate transmission systems

This paper introduces a new differential spatial modulation (DSM) scheme which subsumes both the previously introduced DSM and high-rate spatial modulation (HR-SM) for wireless multiple input multiple output (MIMO) transmission. By combining the codeword design method of the HR-SM scheme with the encoding method of the DSM scheme, we develop a high-rate differential spatial modulation (HR-DSM) scheme equipped with an arbitrary number of transmit antennas that requires channel state information (CSI) neither at the transmitter nor at the receiver. The proposed approach can be applied to any equal energy signal constellations. The bit error rate (BER) performance of the proposed HR-DSM schemes is evaluated by using both theoretical upper bound and computer simulations. It is shown that for the same spectral efficiency and antenna configuration, the proposed HR-DSM outperforms the DSM in terms of bit error rate (BER) performance

Secure information transmission and power transfer in cellular networks

This letter studies simultaneous data transmission and power transfer for multiple information receivers (IRs) and energy-harvesting receivers (ERs) in cellular networks. We formulate an optimization problem to minimize the total transmit power across the network subject to the following three sets of constraints: i) data reliability by maintaining the required level of signal to interference plus noise ratio (SINR) for all IRs; ii) information security by keeping all SINR levels of the intended IRs measured at each ER below a predefined value, which helps prevent possible eavesdroppers, i.e., ERs, from detecting information aimed for the IRs; and iii) energy harvesting by guaranteeing the required level of received power at each ER. Using semidefinite relaxation technique, the proposed problem is then transformed into a convex form which is proved to always yield rank-one optimal solution

Extremely Hot Ambient Temperature and Injury-related Mortality

This pilot study aimed to evaluate the effects of extremely hot ambient temperatures on the total number of fatal injuries. Data were collected from a population-based mortality registry of Thanh Hoa, a province in the North Central region of Vietnam. This study qualified the distributed lag non-linear model and calculated the RR and 95% CI adjusted for long-term trend and absolute humidity. For the entire study population with 3,949 registered deaths due to injuries collected during 2005-2007, after the onset of extremely hot ambient temperatures, an increased risk of death was observed on the 9th day RR (95% CI) = 1.44 (1.06–1.97) and reached the peak on the 12th day RR (95% CI) = 1.58 (1.14–2.17), and at the 15th day RR (95% CI) = 1.49 (1.08–2.06). Men and old adults were identified as the most vulnerable groups. This study confirmed a positive association between hot temperatures and injury-related deaths in the province of 3.6 million people. The findings motivated further investigation into the effect of warm climate changes and the risk of deaths related to other specific causes such as road traffic, work-related injury, and etc

Participatory agro-climate information services: A key component in climate resilient agriculture

The brief promotes participatory agro-climate information services as a key component in achieving climate-smart agriculture. The brief emphasizes that actionable agro-climate information starts with—and responds to—gender-based needs of farmers, integrated at all stages of the value chain. Timely forecasts and accurate agroclimate advisories have been proven to provide farmers with production, adaptation, and mitigation benefits

A Stackelberg-game approach for disaster-recovery communications utilizing cooperative D2D

In this paper, we investigate disaster-recovery com- munications utilizing two-cell cooperative D2D communications. Specifically, one cell is in a healthy area while the other is in a disaster area. A user equipment (UE) in the healthy area aims to assist a UE in the disaster area to recover wireless information transfer (WIT) via an energy harvesting (EH) relay. In the healthy area, the cellular BS shares the spectrum with the UE, however, both of them may belong to different service providers. Thus, the UE pays an amount of price as incentive to the BS as part of two processes: energy trading and interference pricing. We formulate these two processes as two Stackelberg games, where their equilibrium is derived as closed- form solutions. The results help provide a sustainable framework for disaster recovery when the involving parties juggle between energy trading, interference compromise and payment incentives in establishing communications during the recovery process

Synthesis and Photocatalytic Activity for Toluene Removal of CDs/TiO2 - Zeolite Y

Hydrothermally synthesized carbon nanodots (CDs) were impregnated on TiO2. The product (CDs/TiO2) was mechanically mixed with zeolite Y for application in toluene photocatalytic oxidation reaction under UV radiation. Material properties of the samples were investigated by different methods. Toluene vapor was chosen as a typical volatile organic compound to investigate the performance of CDs/TiO2 – zeolite Y photocatalyst when these technological parameters were changed: toluene concentration, gas flow rate, humidity and UV light intensity. In each reaction, only one parameter was changed and the remaining conditions were fixed. The toluene concentrations at the beginning and the end of each reaction were analyzed with the use of gas chromatography (GC). The results of different reaction conditions show the trends for toluene treatment of the CDs/TiO2 – zeolite Y catalyst, thereby providing specific explanations for these trends. The experiments also show that toluene removal is highest when the toluene concentration in the inlet gas is 314 ppmv, the flow rate is 3 L/h, the humidity is 60%, and the catalyst (CDs/TiO2 – zeolite Y composite with 70% zeolite in weight) is illuminated by 4 UV lamps. Copyright © 2022 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

LEGION: Harnessing Pre-trained Language Models for GitHub Topic Recommendations with Distribution-Balance Loss

Open-source development has revolutionized the software industry by promoting collaboration, transparency, and community-driven innovation. Today, a vast amount of various kinds of open-source software, which form networks of repositories, is often hosted on GitHub - a popular software development platform. To enhance the discoverability of the repository networks, i.e., groups of similar repositories, GitHub introduced repository topics in 2017 that enable users to more easily explore relevant projects by type, technology, and more. It is thus crucial to accurately assign topics for each GitHub repository. Current methods for automatic topic recommendation rely heavily on TF-IDF for encoding textual data, presenting challenges in understanding semantic nuances. This paper addresses the limitations of existing techniques by proposing Legion, a novel approach that leverages Pre-trained Language Models (PTMs) for recommending topics for GitHub repositories. The key novelty of Legion is three-fold. First, Legion leverages the extensive capabilities of PTMs in language understanding to capture contextual information and semantic meaning in GitHub repositories. Second, Legion overcomes the challenge of long-tailed distribution, which results in a bias toward popular topics in PTMs, by proposing a Distribution-Balanced Loss (DB Loss) to better train the PTMs. Third, Legion employs a filter to eliminate vague recommendations, thereby improving the precision of PTMs. Our empirical evaluation on a benchmark dataset of real-world GitHub repositories shows that Legion can improve vanilla PTMs by up to 26% on recommending GitHubs topics. Legion also can suggest GitHub topics more precisely and effectively than the state-of-the-art baseline with an average improvement of 20% and 5% in terms of Precision and F1-score, respectively.Comment: Accepted to EASE'2