Higgs-gauge boson interactions in the economical 3-3-1 model

Interactions among the standard model gauge bosons and scalar fields in the framework of SU(3)_C X SU(3)_L X U(1)_X gauge model with minimal (economical) Higgs content are presented. From these couplings, all scalar fields including the neutral scalar $h$ and the Goldstone bosons can be identified and their couplings with the usual gauge bosons such as the photon, the charged $W^\pm$ and the neutral $Z$, without any additional condition, are recovered. In the effective approximation, full content of scalar sector can be recognized. The CP-odd part of Goldstone associated with the neutral non-Hermitian bilepton gauge boson $G_{X^0}$ is decouple, while its CP-even counterpart has the mixing by the same way in the gauge boson sector. Masses of the new neutral Higgs boson $H^0_1$ and the neutral non-Hermitian bilepton $X^0$ are dependent on a coefficient of Higgs self-coupling ($\lambda_1$). Similarly, masses of the singly-charged Higgs boson $H_2^\pm$ and of the charged bilepton $Y^\pm$ are proportional through a coefficient of Higgs self-interaction ($\lambda_4$). The hadronic cross section for production of this Higgs boson at the LHC in the effective vector boson approximation is calculated. Numerical evaluation shows that the cross section can exceed 260 $fb$.Comment: 22 pages, 1 figure, submitted to Phys. Rev.

A Machine Learning-based Approach to Vietnamese Handwritten Medical Record Recognition

Handwritten text recognition has been an active research topic within computer vision division. Existing deep-learning solutions are practical; however, recognizing Vietnamese handwriting has shown to be a challenge with the presence of extra six distinctive tonal symbols and extra vowels. Vietnam is a developing country with a population of approximately 100 million, but has only focused on digitalization transforms in recent years, and so Vietnam has a significant number of physical documents, that need to be digitized. This digitalization transform is urgent when considering the public health sector, in which medical records are mostly still in hand-written form and still are growing rapidly in number. Digitization would not only help current public health management but also allow preparation and management in future public health emergencies. Enabling the digitalization of old physical records will allow efficient and precise care, especially in emergency units. We proposed a solution to Vietnamese text recognition that is combined into an end-to-end document-digitalization system. We do so by performing segmentation to word-level and then leveraging an artificial neural network consisting of both convolutional neural network (CNN) and a long short-term memory recurrent neural network (LSTM) to propagate the sequence information. From the experiment with the records written by 12 doctors, we have obtained encouraging results of 6.47% and 19.14% of CER and WER respectively

On Non-Elitist Evolutionary Algorithms Optimizing Fitness Functions with a Plateau

We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are applied to a family of fitness functions with a plateau of second-best fitness in a Hamming ball of radius r around a unique global optimum. On one hand, using the level-based theorems, we obtain polynomial upper bounds on the expected runtime for some modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular. On the other hand, we show that the EA with fitness proportionate selection is inefficient if the bitwise mutation is used with the standard settings of mutation probability.Comment: 14 pages, accepted for proceedings of Mathematical Optimization Theory and Operations Research (MOTOR 2020). arXiv admin note: text overlap with arXiv:1908.0868

Room temperature ammonia gas sensor based on p-type-like V2O5 nanosheets towards food spoilage monitoring

Gas sensors play an important role in many areas of human life, including the monitoring of production processes, occupational safety, food quality assessment, and air pollution monitoring. Therefore, the need for gas sensors to monitor hazardous gases, such as ammonia, at low operating temperatures has become increasingly important in many fields. Sensitivity, selectivity, low cost, Citation: Van Duy, L.; Nguyet, T.T.; Le, D.T.T.; Van Duy, N.; Nguyen, H.; Biasioli, F.; Tonezzer, M.; Di Natale, C.; Hoa, N.D. Room Temperature AmmoniaGasSensor Based on p-Type-like V2O5 Nanosheets towards Food Spoilage Monitoring. Nanomaterials 2023, 13, 146. https:// doi.org/10.3390/nano13010146 Academic Editors: Sergei Kulinich and Li Hai Received: 17 November 2022 Revised: 23 December 2022 Accepted: 24 December 2022 Published: 28 December 2022 Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). and ease of production are crucial characteristics for creating a capillary network of sensors for the protection of the environment and human health. However, developing gas sensors that are not only efficient but also small and inexpensive and therefore integrable into everyday life is a difficult challenge. In this paper, we report on a resistive sensor for ammonia detection based on thin V2O5 nanosheets operating at room temperature. The small thickness and porosity of the V2O5 nanosheets give the sensors good performance for sensing ammonia at room temperature (RT), with a relative change of resistance of 9.4% to 5 ppm ammonia (NH3) and an estimated detection limit of 0.4 ppm. The sensor is selective with respect to the seven interferents tested; it is repeatable and stable over the long term (four months). Although V2O5 is generally an n-type semiconductor, in this case the nanosheets show a p-type semiconductor behavior, and thus a possible sensing mechanism is proposed. The device’s performance, along with its size, low cost, and low power consumption, makes it a good candidate for monitoring freshness and spoilage along the food supply chai

Water quality modelling of the Mekong River basin: climate change and socioeconomics drive flow and nutrient flux changes to the Mekong Delta

The Mekong delta is recognised as one of the world's most vulnerable mega-deltas, being subject to a range of environmental pressures including sea level rise, increasing population, and changes in flows and nutrients from its upland catchment. With changing climate and socioeconomics there is a need to assess how the Mekong catchment will be affected in terms of the delivery of water and nutrients into the delta system. Here we apply the Integrated Catchment model (INCA) to the whole Mekong River Basin to simulate flow and water quality, including nitrate, ammonia, total phosphorus and soluble reactive phosphorus. The impacts of climate change on all these variables have been assessed across 24 river reaches ranging from the Himalayas down to the delta in Vietnam. We used the UK Met Office PRECIS regionally coupled climate model to downscale precipitation and temperature to the Mekong catchment. This was accomplished using the Global Circulation Model GFDL-CM to provide the boundary conditions under two carbon control strategies, namely representative concentration pathways (RCP) 4.5 and a RCP 8.5 scenario. The RCP 4.5 scenario represents the carbon strategy required to meet the Paris Accord, which aims to limit peak global temperatures to below a 2 °C rise whilst seeking to pursue options that limit temperature rise to 1.5 °C. The RCP 8.5 scenario is associated with a larger 3–4 °C rise. In addition, we also constructed a range of socio-economic scenarios to investigate the potential impacts of changing population, atmospheric pollution, economic growth and land use change up to the 2050s. Results of INCA simulations indicate increases in mean flows of up to 24%, with flood flows in the monsoon period increasing by up to 27%, but with increasing periods of drought up to 2050. A shift in the timing of the monsoon is also simulated, with a 4 week advance in the onset of monsoon flows on average. Decreases in nitrogen and phosphorus concentrations occur primarily due to flow dilution, but fluxes of these nutrients also increase by 5%, which reflects the changing flow, land use change and population changes

Antigenic characterization of highly pathogenic avian influenza A(H5N1) viruses with chicken and ferret antisera reveals clade-dependent variation in hemagglutination inhibition profiles.

Highly pathogenic avian influenza (HPAI) A(H5N1) viruses pose a significant economic burden to the poultry industry worldwide and have pandemic potential. Poultry vaccination against HPAI A(H5N1) viruses has been an important component of HPAI control measures and has been performed in Vietnam since 2005. To systematically assess antigenic matching of current vaccines to circulating field variants, we produced a panel of chicken and ferret antisera raised against historical and contemporary Vietnamese reference viruses representing clade variants that were detected between 2001 and 2014. The antisera were used for hemagglutination inhibition (HI) assays to generate data sets for analysis by antigenic cartography, allowing for a direct comparison of results from chicken or ferret antisera. HI antigenic maps, developed with antisera from both hosts, revealed varying patterns of antigenic relationships and clustering of viruses that were dependent on the clade of viruses analyzed. Antigenic relationships between existing poultry vaccines and circulating field viruses were also aligned with in vivo protection profiles determined by previously reported vaccine challenge studies. Our results establish the feasibility and utility of HPAI A(H5N1) antigenic characterization using chicken antisera and support further experimental and modeling studies to investigate quantitative relationships between genetic variation, antigenic drift and correlates of poultry vaccine protection in vivo

D-Serine Is a Substrate for Neutral Amino Acid Transporters ASCT1/SLC1A4 and ASCT2/SLC1A5, and Is Transported by Both Subtypes in Rat Hippocampal Astrocyte Cultures

N-methyl-D-aspartate (NMDA) receptors play critical roles in synaptic transmission and plasticity. Activation of NMDA receptors by synaptically released L-glutamate also requires occupancy of co-agonist binding sites in the tetrameric receptor by either glycine or D-serine. Although D-serine appears to be the predominant co-agonist at synaptic NMDA receptors, the transport mechanisms involved in D-serine homeostasis in brain are poorly understood. In this work we show that the SLC1 amino acid transporter family members SLC1A4 (ASCT1) and SLC1A5 (ASCT2) mediate homo- and hetero-exchange of D-serine with physiologically relevant kinetic parameters. In addition, the selectivity profile of D-serine uptake in cultured rat hippocampal astrocytes is consistent with uptake mediated by both ASCT1 and ASCT2. Together these data suggest that SLC1A4 (ASCT1) may represent an important route of Na-dependent D-serine flux in the brain that has the ability to regulate extracellular D-serine and thereby NMDA receptor activity