TẠO DÒNG CÁC GEN MÃ HÓA CHITINASE 42 kDa CỦA Trichoderma asperellum VÀO VECTOR BIỂU HIỆN THỰC VẬT pMYV719 ĐỂ PHỤC VỤ CHUYỂN GEN

In this study, chitinase genes containing a signal peptide sequence, such as Chi42, syncodChi42-1 and syncodChi42-2, were cloned in the plant expression vector pMYV719 and successfully transferred into Agrobacterium tumefaciens LBA 4404. Among them, Chi42 is a wild-type gene of Trichoderma asperellum SH16. Both genes syncodChi42-1 and syncodChi42-2 are derived from Chi42, which was optimized for codon usage for plant expression. Agrobacterium bacteria-harbouring pMYV719/chitinase vector was used for genetic transformation into peanuts (Arachis hypogaea L.) to enhance resistance to phytopathogenic fungi in further studies.Trong nghiên cứu này, các gen chitinase mang trình tự peptide tín hiệu như Chi42, syncodChi42-1 và syncodChi42-2 đã được tạo dòng trong vector biểu hiện thực vật pMYV719 và biến nạp thành công vào vi khuẩn Agrobacterium tumefaciens LBA 4404. Trong đó, gen Chi42 là kiểu gen hoang dại từ chủng nấm Trichoderma asperellum SH16. Hai gen syncodChi42-1 và syncodChi42-2 có nguồn gốc từ gen Chi42 đã được tối ưu hóa bộ ba sử dụng để biểu hiện thực vật. Vi khuẩn A. tumefaciens mang các gen chitinase được sử dụng để chuyển gen vào cây lạc (Arachis hypogaea L.) trong các nghiên cứu tiếp theo để cải thiện khả năng kháng nấm bệnh của chúng

Impact of Education and Network for Avian Influenza H5N1 in Human: Knowledge, Clinical Practice, and Motivation on Medical Providers in Vietnam

BACKGROUND: Knowledge, clinical practice, and professional motivation of medical providers relating to H5N1 infection have an important influence on care for H5N1 patients who require early diagnosis and early medical intervention. METHODS/PRINCIPAL FINDINGS: Novel educational programs including training and workshops for medical providers relating to H5N1 infection in Vietnam were originally created and implemented in 18 provincial hospitals in northern Vietnam between 2008 and 2010. A self-administered, structured questionnaire survey was conducted in 8 provincial hospitals where both educational training and workshops were previously provided. A total of 326 medical providers, including physicians, nurses, and laboratory technicians who attended or did not attend original programs were enrolled in the survey. Knowledge, clinical attitudes and practice (KAP), including motivation surrounding caring for H5N1 patients, were evaluated. The study indicated a high level of knowledge and motivation in all professional groups, with especially high levels in laboratory technicians. Conferences and educational programs were evaluated to be the main scientific information resources for physicians, along with information from colleagues. The chest radiographs and the initiation of antiviral treatment in the absence of RT-PCR result were identified as gaps in education. Factors possibly influencing professional motivation for caring for H5N1 patients included healthcare profession, the hospital where the respondents worked, age group, attendance at original educational programs and at educational programs which were conducted by international health-related organizations. CONCLUSIONS: Educational programs provide high knowledge and motivation for medical providers in Vietnam caring for H5N1 patients. Additional educational programs related to chest radiographs and an initiation of treatment in the absence of RT-PCR are needed. Networking is also necessary for sharing updated scientific information and practical experiences. These enhanced KAPs by educational programs and integrated systems among hospitals should result in appropriate care for H5N1 patients and may reduce morbidity and mortality

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Performance evaluation and enhancement of massive MIMO communication systems

The increasing popularity of smart terminals and their multimedia applications, as well as social networks, leads to tremendous growth in demands for capacity and quality of service (QoS) in cellular networks. To meet these demands, multiple-input multiple-output (MIMO) wireless systems have been developed and they are now a part of current standards such as IEEE 802.11 and the fourth generation (4G) long term evolution (LTE). However, there are several challenges, i.e., spectral crisis, spectral efficiency (SE) and high energy consumption, which cannot be accommodated by current generation networks. The capacity of 4G networks with current technologies is reaching theoretical limit soon. Therefore, we focus on performance analyses and enhancement of massive MIMO system, which is considered as a potential technology for future wireless and mobile communication systems. With massive MIMO technology, a base station (BS) is equipped with a large antenna array to serve users simultaneously over the same radio resources. The main contribution of this thesis is to investigate fundamental performance in terms of SE and energy efficiency (EE) for downlink massive MIMO systems with different precoding schemes under perfect and imperfect channel state information (CSI). In particular, in single-cell scenarios, asymptotic achievable capacities of block diagonalization (BD) precoding and BD-based with space-time block code (STBC) are analyzed. Assuming that the number of BS antennas and the number of antennas per users are large while their ratio remains bounded, the capacity expressions for these two schemes are derived. The optimal number of users and optimal length of training sequence for maximizing the SE are derived for practical implementation. For the case of single-antenna users, the SE of a massive MIMO system with signal-to-leakage-plus-noise ratio precoding scheme (SLNR-PS) is studied. By applying a realistic power consumption model, under the assumption of equal power allocation for all users, the EE maximization problem with respect to number of BS antennas, transmit power and length of training sequence is investigated. Through analysis, the optimal value of each parameter for maximizing the EE is derived when the other parameters are assumed to be known. Moreover, a closed-form expression of the optimal length of training sequence for maximizing SE is derived at high signal-to-noise ratio (SNR) region. Based on these expressions, an alternating optimization algorithm is used to solve the EE maximization problem. It has been shown that the SLNR-PS is lower bounded by that of the zero-forcing precoding scheme (ZF-PS). The optimum EE of SLNR-PS is obtained by a massive MIMO setup with optimal values of transmit power and training sequence. If the quality of channel estimation is low, the SLNR-PS needs to use more BS antennas to achieve the optimum EE, as compared to that with better channel qualities. In addition, under the constraints of transmit power and QoS, we also obtain an energy-efficient power allocation scheme to optimize the EE. The problem of rate profile optimization is also considered while satisfying the QoS and EE target constraints. In multicell scenarios, the pilot contamination affects significantly the performance of massive MIMO systems. This thesis also presents a scheme, which consists of a two-layer approach of optimal tilt adaptation based on the users’ locations and optimal power allocation based on the game theory, to minimize the effect of pilot contamination, and hence to maximize the network sum rate. The proposed scheme has low computational complexity and it can avoid a heavy signalling exchange among base stations via backhaul links. Numerical results show that the proposed scheme outperforms the conventional fixed-downtilt systems with equal power allocation and waterfilling power allocation, respectively. A coordinated multipoint transmission for two-tier HetNets with massive MIMO technology and practical deployment is also proposed in this thesis. The small cell base stations (SBSs) are utilized outside the inner region of macrocell base stations (MBSs) to improve the performance of macrocell edge users. Based on the stochastic geometry approach, the SE and EE of the proposed system are analyzed. The EE maximization problem is formulated and solved effectively by using the alternating optimization algorithm under the constraints of QoS, density of SBS, available number of MBS antennas and MBS transmit power. The algorithm is shown to converge quickly. The impacts of the small cell density, inner region size and massive MIMO on the network performance are explicitly examined. By approximating the interference distribution by moment matching with the Gamma distribution, the coverage probability of the two-tier Hetnet is also derived. Numerical results are provided to validate the theoretical analysis. It has been shown that the proposed scheme outperforms the conventional maximum receive power association scheme. Based on the combinational use of the small cell deployment, massive MIMO and joint transmission, it has been shown that the two-tier HetNet can provide high spectral efficiency and energy efficiency.Doctor of Philosophy (EEE

Error probability analysis of a novel adaptive beamforming receiver for large-scale multiple-input-multiple-output communication system

A novel adaptive beamforming receiver is proposed for a multiple-input multiple-output (MIMO) communication system over multipath fading channels. By dividing a large number of receive antennas into many adaptive beamformers (ABFs), the proposed system reduces the array dimension in order to simplify the signal detection process and enjoys the benefit of beamforming techniques to improve the symbol-error rate (SER) performance. The effectiveness of the proposed system depends on the number of ABFs and the number of antennas per ABF. The statistical properties of complex Wishart matrices are applied to analyze the SER performance of the proposed system with both maximum-likelihood (ML) detection and zero-forcing (ZF) detection. Furthermore, we have derived an upper bound for SER of the ML detection based on the smallest eigenvalue distribution. Through our analysis, it has been shown that the proposed system using ML detection provides comparable SER performance, but with a lower complexity as compared to that of a conventional ML receiver due to reduced array dimensions.Accepted versio

Energy and spectral efficiency of leakage-based precoding for large-scale MU-MIMO systems

We study the capacity performance of signal-toleakage- and-noise ratio precoding scheme (SLNR-PS) for largescale multiuser multiple-inputmultiple-output systems.We derive capacity bounds of SLNR-PS when the number of base station antennas N is large. A trade-off between energy efficiency (EE) and spectral efficiency (SE) is defined for the case of equal power allocation. Based on this trade-off, the closed-form expressions of optimal SE and optimal number of BS antennas for maximizing EE are derived, respectively. In addition, we consider the EE optimization problem under both maximum transmit power and quality of service constraints. The energy-efficient power allocation scheme is obtained to solve this optimization problem. Numerical simulations verify the benefits of the proposed scheme.Accepted versio

Spectral and energy efficiency analysis for SLNR precoding in massive MIMO systems with imperfect CSI

We derive tractable bound expressions on achievable spectral efficiency for a multiple-input multiple-output (MIMO) system with a signal-to-leakage-plus-noise ratio precoding scheme (SLNR-PS) under the condition of imperfect channel state information. These bounds are tight and approach exact values when the number of base station (BS) antennas is large. A problem of energy efficiency (EE) maximization is investigated by using a practical power consumption model. The effects of the system parameters and quality of channel estimation, including the number of BS antennas, transmit power, and training length on the performance metrics, are explicitly analyzed. Following that, an alternating optimization algorithm is employed to obtain the optimum EE. It has been shown that the proposed SLNR-PS performs better than the matched-filtering and zero-forcing schemes and a deployment of massive MIMO with the optimal transmit power and training length can achieve high EE.Accepted versio

Nonlinear energy harvesting for millimeter wave networks with large-scale antennas

In this paper, an analytical framework is proposed to explore the potential of wireless power transfer (WPT) for a millimeter wave (mmWave) network with large-scale antennas. Prior works mostly focus on WPT systems with a linear energy harvesting (EH) model, which cannot properly capture the power dependent EH efficiency. On the other hand, based on a nonlinear EH model, the effect of practical EH circuit specifications on the EH performance can be analyzed. By using stochastic geometry approach, analytical and asymptotic expressions for the energy coverage probability, average harvested energy, and achievable rate are derived under different base station (BS) configuration and deployment scenarios. Numerical results provide interesting design insights that the EH circuit specifications significantly affect the network performance. Increasing the BS density and number of BS antennas can improve the network performance. Due to saturation of EH circuits, the typical receiver can only achieve finite maximum amount of harvested energy and achievable rate even when the BS has a large number of antennas.MOE (Min. of Education, S’pore)Accepted versio