Required flows for aquatic ecosystems in Ma River, Vietnam

Ecological flow requirements for the Ma River in dry season were assessed in three reaches of Ma – Buoi, Ma – Len and Ma – Chu. 5 indictor fish species was chosen based on biodiversity survey and roles of those species in aquatic ecosystem as well as local communities. Biological and hydrological data (dry season of 2016- 2017) and 35 year recorded hydrological data were collected and analyzed as input data for a physical habitat model River HYdraulic and HABitat SImulation Model – RHYHABSIM. Model results shown that the optimal flows of the reaches were very much higher compare with the minimum annual low flow - MALF. In this study, MALF7day were applied to calculate the recommended minimum flows of the three reaches. The recommended required minimum flows for Ma – Buoi, Ma – Len and Ma – Chu reaches were 51 m3/s, 49 m3/s and 61 m3/s, respectively. It must be stressed that this study only assessed whether or not there is enough habitat available for the river to sustain a healthy ecosystem

Synthesis, Biological Evaluation, and Molecular Modeling Studies of 1-Aryl-1H-pyrazole-Fused Curcumin Analogues as Anticancer Agents

Addressing the growing burden of cancer and the shortcomings of chemotherapy in cancer treatment are the current research goals. Research to overcome the limitations of curcumin and to improve its anticancer activity via its heterocycle-fused monocarbonyl analogues (MACs) has immense potential. In this study, 32 asymmetric MACs fused with 1-aryl-

Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications

This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message into two parts: (i) the active-transmit message transmitted by the transmitter using conventional RF signals and (ii) the backscatter message transmitted by an ambient backscatter tag that backscatters upon the active signals emitted by the transmitter. Notably, the backscatter tag does not generate its own signal, making it difficult for an eavesdropper to detect the backscattered signals unless they have prior knowledge of the system. Here, we assume that without decoding/knowing the backscatter message, the eavesdropper is unable to decode the original message. Even in scenarios where the eavesdropper can capture both messages, reconstructing the original message is a complex task without understanding the intricacies of the message-splitting mechanism. A challenge in our proposed framework is to effectively decode the backscattered signals at the receiver, often accomplished using the maximum likelihood (MLK) approach. However, such a method may require a complex mathematical model together with perfect channel state information (CSI). To address this issue, we develop a novel deep meta-learning-based signal detector that can not only effectively decode the weak backscattered signals without requiring perfect CSI but also quickly adapt to a new wireless environment with very little knowledge. Simulation results show that our proposed learning approach, without requiring perfect CSI and complex mathematical model, can achieve a bit error ratio close to that of the MLK-based approach. They also clearly show the efficiency of the proposed approach in dealing with eavesdropping attacks and the lack of training data for deep learning models in practical scenarios

Enabling Technologies for Web 3.0: A Comprehensive Survey

Web 3.0 represents the next stage of Internet evolution, aiming to empower users with increased autonomy, efficiency, quality, security, and privacy. This evolution can potentially democratize content access by utilizing the latest developments in enabling technologies. In this paper, we conduct an in-depth survey of enabling technologies in the context of Web 3.0, such as blockchain, semantic web, 3D interactive web, Metaverse, Virtual reality/Augmented reality, Internet of Things technology, and their roles in shaping Web 3.0. We commence by providing a comprehensive background of Web 3.0, including its concept, basic architecture, potential applications, and industry adoption. Subsequently, we examine recent breakthroughs in IoT, 5G, and blockchain technologies that are pivotal to Web 3.0 development. Following that, other enabling technologies, including AI, semantic web, and 3D interactive web, are discussed. Utilizing these technologies can effectively address the critical challenges in realizing Web 3.0, such as ensuring decentralized identity, platform interoperability, data transparency, reducing latency, and enhancing the system's scalability. Finally, we highlight significant challenges associated with Web 3.0 implementation, emphasizing potential solutions and providing insights into future research directions in this field

Carbonization and H3PO4 activation of fern Dicranopteris linearis and electrochemical properties for electric double layer capacitor electrode

Today, the world’s climate change is a growing problem, plant carbon sequestration is one of the effective ways to mitigate climate change by reducing greenhouse gases, mostly carbon gases. Dicranopteris linearis (D. linearis), a common fern species in the tropic or subtropic ecoregions, has been recently recognized as a potential feedstock to produce highly porous biochar. This study aims to enhance the specific surface area (SSA) and pore volumes of biochars derived from the D. linearis by H3PO4 activation and examine electrical properties of the activated biochars and their possible usage for the electric double-layer capacitor (EDLC) electrode. The treated raw fern was activated with H3PO4 85% by the three different mixing ratios 1:0, 1:1, and 1:3 (w/w) and then pyrolysis under N2 flow maintained at 500 °C for 1 h. The performance as the electrode for an EDLC was evaluated in 1 mol L−1 H2SO4 solution for the H3PO4-activated samples. The SSA and pore volumes were drastically increased after activation. The maximum SSA and pore volume were 1212 m2 g−1 and 1.43 cm3 g−1, respectively for the biochar activated at 400 °C with a weight mixing ratio 1:3 (w/w) between the fern and H3PO4 acid while these values of the biochar at 400 °C were 12 m2 g−1 and 0.02 cm3 g−1, respectively. The biochar activated at 600 °C with the mixing ratio 1:1 (w/w) showed the maximum capacitance value, ca. 108 F g−1 at 1 mV s−1. The activation using H3PO4 showed a positive tendency to enhance electrochemical properties and it could be a premise toward a higher performance of EDLC from the D. linearis derived activated biochar

Reference Ranges for Bone Mineral Density and Prevalence of Osteoporosis in Vietnamese Men and Women

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to examine the effect of different reference ranges in bone mineral density on the diagnosis of osteoporosis.</p> <p>Methods</p> <p>This cross-sectional study involved 357 men and 870 women aged between 18 and 89 years, who were randomly sampled from various districts within Ho Chi Minh City, Vietnam. BMD at the femoral neck, lumbar spine and whole body was measured by DXA (Hologic QDR4500). Polynomial regression models and bootstraps method were used to determine peak BMD and standard deviation (<it>SD</it>). Based on the two parameters, we computed T-scores (denoted by <it>T</it>_VN) for each individual in the study. A similar diagnosis was also done based on T-scores provided by the densitometer (<it>T</it>_DXA), which is based on the US White population (NHANES III). We then compared the concordance between <it>T</it>_VNand <it>T</it>_DXAin the classification of osteoporosis. Osteoporosis was defined according to the World Health Organization criteria.</p> <p>Results</p> <p>In post-menopausal women, the prevalence of osteoporosis based on femoral neck <it>T</it>_VNwas 29%, but when the diagnosis was based on <it>T</it>_DXA, the prevalence was 44%. In men aged 50+ years, the <it>T</it>_VN-based prevalence of osteoporosis was 10%, which was lower than <it>T</it>_DXA-based prevalence (30%). Among 177 women who were diagnosed with osteoporosis by <it>T</it>_DXA, 35% were actually osteopenia by <it>T</it>_VN. The kappa-statistic was 0.54 for women and 0.41 for men.</p> <p>Conclusion</p> <p>These data suggest that the <it>T-</it>scores provided by the Hologic QDR4500 over-diagnosed osteoporosis in Vietnamese men and women. This over-diagnosis could lead to over-treatment and influence the decision of recruitment of participants in clinical trials.</p