Application of short tandem repeats (STRs) in the preimplantation genetic diagnosis (PGD) of α-thalassemia.

OBJECTIVES: α-thalassemia is an autosomal recessive monogenic blood disorder, affecting up to 5% of the world's population. The occurrence rate of the disease in Vietnam varies up to up to 51.5%, with high rate of mutation carriers, of couples consisting of two carriers at risk of bearing a child with fetal Hb Bart, which can develop into hydrops fetalis syndrome, threatening the well-being of the mother and the child. Our study aims to facilitate birth of healthy/asymptomatic children of α-thalassemia carrier couples who received reproductive service at our centre during the period of 2019-2022. MATERIALS AND METHODS: 89 couples at risks of having α-thalassemia offsprings requested IVF procedures and PGD at Post Hospital during 2019-2022 were recruited for investigation. Couple and additional family members' peripheral blood samples of couples and additional family members were subjected to haemoglobin electrophoresis, DNA extraction for α-thalassemia gene mutation detection and STRs linkage analysis. Data were observed and analysed on GeneMarker software. RESULTS: 91 cycles of PGD for α-thalassemia were carried out for 89 couples. α-thalassemia large deletion (--SEA/αα) was the most common mutation identified in 88 couples, in which 4 cases also carried ß-thalassemia point mutations. Combining results of PGS and PGD, 278/424 amplified embryos were transferable (HBA-mutation free or carriers of single heterozygous HBA mutation, without chromosomal abnormality). 64/89 couples have been transferred with the embryos (prioritizing mutation free ones over carriers), resulting in the birth of 36 α-thalassemia disease-free children, 17 ongoing pregnancies, and 11 with miscarriages. CONCLUSION: Successful application of microsatellite-based method in PGD facilitated the birth of 36 healthy children and 17 ongoing pregnancies for 53/64 couples with embryo-transferred. All resulted clinical births displayed confirmation results in line with the PGD results, thus demonstrating the feasibility and credibility of the use of STR markers in PGD.

A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome.

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

Computer-Aided Detection for Chest Radiography to Improve the Quality of Tuberculosis Diagnosis in Vietnam's District Health Facilities: An Implementation Study.

In Vietnam, chest radiography (CXR) is used to refer people for GeneXpert (Xpert) testing to diagnose tuberculosis (TB), demonstrating high yield for TB but a wide range of CXR abnormality rates. In a multi-center implementation study, computer-aided detection (CAD) was integrated into facility-based TB case finding to standardize CXR interpretation. CAD integration was guided by a programmatic framework developed for routine implementation. From April through December 2022, 24,945 CXRs from TB-vulnerable populations presenting to district health facilities were evaluated. Physicians interpreted all CXRs in parallel with CAD (qXR 3.0) software, for which the selected TB threshold score was ≥0.60. At three months, there was 47.3% concordance between physician and CAD TB-presumptive CXR results, 7.8% of individuals who received CXRs were referred for Xpert testing, and 858 people diagnosed with Xpert-confirmed TB per 100,000 CXRs. This increased at nine months to 76.1% concordant physician and CAD TB-presumptive CXRs, 9.6% referred for Xpert testing, and 2112 people with Xpert-confirmed TB per 100,000 CXRs. Our programmatic CAD-CXR framework effectively supported physicians in district facilities to improve the quality of referral for diagnostic testing and increase TB detection yield. Concordance between physician and CAD CXR results improved with training and was important to optimize Xpert testing.

Anopheles diversity, biting behaviour and transmission potential in forest and farm environments of Gia Lai province, Vietnam.

BACKGROUND: Despite recent reductions in Vietnam, malaria transmission persists in some areas in forests and farmlands where a high density of Anopheles mosquitoes relative to other environments occurs. To inform effective malaria control measures, it is important to understand vector bionomics and the malaria transmission role of Anopheles spp. in the highland regions of Vietnam. This study was conducted to quantify the abundance, composition and biting behaviour of the Anopheles mosquito population, and the proportion of Plasmodium spp. infected mosquitoes collected from forest and agricultural farm sites in Gia Lai province, Vietnam. METHODS: Forest and agricultural farm sites in Gia Lai province were selected for mosquito collections (total eight sites). Mosquito collection was performed by Human-baited Double Net Trap (HDNT), animal-baited traps (ABT) using cattle, and CDC light traps. Captured mosquitoes were identified morphologically, and salivary glands of Anopheles mosquitoes were examined for sporozoites using microscopy. Plasmodium infection was determined by Polymerase Chain Reaction (PCR), and identification of blood meal type was determined by PCR and diffuse serum agglutination assay. RESULTS: A total of 1815 Anopheles mosquitoes belonging to 19 species were collected by ABT (n = 1169), HDNT (n = 471) and CDC light trap (n = 175). Anopheles abundance and diversity varied by district and environment. Capture by HDNT of Anopheles of vectorial concern was observed between early evening and early morning. Plasmodium vivax infection was determined by PCR in two Anopheles dirus specimens captured by HDNT in forest sites. Blood from a range of hosts could, including human blood, could be detected in species considered primary and secondary vectors An. dirus, and Anopheles aconitus, and Anopheles maculatus, respectively. CONCLUSIONS: A low number of Anopheles spp. considered primary vectors of concern and very low numbers of Plasmodium spp. infected Anopheles mosquitoes were captured at the end of the rainy season in the Central Highlands of Vietnam. However, capture species of vectorial concern by HDNT throughout the early to late evening demonstrates that use of additional personal protective measures could supplement current preventative measures, such as bed nets to prevent exposure to vectors of concern in this region.

Feasibility of combining short tandem repeats (STRs) haplotyping with preimplantation genetic diagnosis (PGD) in screening for beta thalassemia.

ß-thalassemia is an autosomal recessive disease with the reduction or absence in the production of ß-globin chain in the hemoglobin, which is caused by mutations in the Hemoglobin subunit beta (HBB) gene. In Vietnam, the number of ß-thalassemia carriers range from 1.5 to 25.0%, depending on ethnic and geographical areas, which is much higher than WHO's data worldwide (1.5%). Hence, preimplantation genetic diagnosis (PGD) plays a crucial role in reducing the rate of ß-thalassemia affected patients/carriers. In this research, we report the feasibility and reliability of conducting PGD in combination with the use of short tandem repeat (STR) markers in facilitating the birth of healthy children. Six STRs, which were reported to closely linked with the HBB gene, were used on 15 couples of ß-thalassemia carriers. With 231 embryos, 168 blastocysts were formed (formation rate of 72.73%), and 88 were biopsied and examined with STRs haplotyping and pedigree analysis. Thus, the results were verified by Sanger sequencing, as a definitive diagnosis. Consequently, 11 over 15 couples have achieved pregnancy of healthy or at least asymptomatic offspring. Only three couples failed to detect any signs of pregnancy such as increased Human Chorionic Gonadotropin (HCG) level, foetal sac, or heart; and one couple has not reached embryo transfer as they were proposed to continue with HLA-matching to screen for a potential umbilical cord blood donor sibling. Thus, these results have indicated that the combination of PGD with STRs analysis confirmed by Sanger sequencing has demonstrated to be a well-grounded and practical clinical strategy to improve the detection of ß-thalassemia in the pregnancies of couples at-risk before embryo transfer, thus reducing ß-thalassemia rate in the population.

Accurate discharge and water level forecasting using ensemble learning with genetic algorithm and singular spectrum analysis-based denoising.

Forecasting discharge (Q) and water level (H) are essential factors in hydrological research and flood prediction. In recent years, deep learning has emerged as a viable technique for capturing the non-linear relationship of historical data to generate highly accurate prediction results. Despite the success in various domains, applying deep learning in Q and H prediction is hampered by three critical issues: a shortage of training data, the occurrence of noise in the collected data, and the difficulty in adjusting the model's hyper-parameters. This work proposes a novel deep learning-based Q-H prediction model that overcomes all the shortcomings encountered by existing approaches. Specifically, to address data scarcity and increase prediction accuracy, we design an ensemble learning architecture that takes advantage of multiple deep learning techniques. Furthermore, we leverage the Singular-Spectrum Analysis (SSA) to remove noise and outliers from the original data. Besides, we exploit the Genetic Algorithm (GA) to propose a novel mechanism that can automatically determine the prediction model's optimal hyper-parameters. We conducted extensive experiments on two datasets collected from Vietnam's Red and Dakbla rivers. The results show that our proposed solution outperforms current techniques across a wide range of metrics, including NSE, MSE, MAE, and MAPE. Specifically, by exploiting the ensemble learning technique, we can improve the NSE by at least [Formula: see text]. Moreover, with the aid of the SSA-based data preprocessing technique, the NSE is further enhanced by more than [Formula: see text]. Finally, thanks to GA-based optimization, our proposed model increases the NSE by at least [Formula: see text] and up to [Formula: see text] in the best case.

Interpolation Methods with Phase Control for Backprojection of Complex-Valued SAR Data.

Time-domain backprojection algorithms are widely used in state-of-the-art synthetic aperture radar (SAR) imaging systems that are designed for applications where motion error compensation is required. These algorithms include an interpolation procedure, under which an unknown SAR range-compressed data parameter is estimated based on complex-valued SAR data samples and backprojected into a defined image plane. However, the phase of complex-valued SAR parameters estimated based on existing interpolators does not contain correct information about the range distance between the SAR imaging system and the given point of space in a defined image plane, which affects the quality of reconstructed SAR scenes. Thus, a phase-control procedure is required. This paper introduces extensions of existing linear, cubic, and sinc interpolation algorithms to interpolate complex-valued SAR data, where the phase of the interpolated SAR data value is controlled through the assigned a priori known range time that is needed for a signal to reach the given point of the defined image plane and return back. The efficiency of the extended algorithms is tested at the Nyquist rate on simulated and real data at THz frequencies and compared with existing algorithms. In comparison to the widely used nearest-neighbor interpolation algorithm, the proposed extended algorithms are beneficial from the lower computational complexity perspective, which is directly related to the offering of smaller memory requirements for SAR image reconstruction at THz frequencies.

Early-phase risk assessments during the first epidemic year of African swine fever outbreaks in Vietnamese pigs.

BACKGROUND: African swine fever (ASF) is a notifiable viral disease of pigs and wild boars that could lead to serious economic losses for the swine industry. OBJECTIVES: The aim of this study was to identify risk factors in the early phase of ASF outbreaks in Vietnamese swine herds during the first epidemic year. METHODS: The period of interest for this case-control study was February to July 2019. A questionnaire was administered in northern Vietnam where all early cases of ASF were reported. Producers of herds with reported cases were asked to provide information starting from the day of onset of clinical signs as well as 30 days prior to that day. The period of interest for controls was within the 6 months of the first outbreak in Vietnam (February 2019). Questionnaires included 55 questions; responses were received from 67 cases and 115 controls. Logistic regression analysis was used to identify factors associated with ASF status. RESULTS: Thirty-seven variables of interest (among a total of 55 variables) were associated with ASF status in univariate analysis (p < 0.05). These 37 variables were assessed for inclusion in the multivariate analysis by backward stepwise selection. Six variables remained significant as ASF risk factors in the final model: distance to farm within 500 m, distance of irrigation systems within 200 m, total number of pigs (≤500), absence of dressing rooms for workers/visitors before entering the farm, poor hygienic practices for people within the farm, and poor hygienic practices at pig loading/unloading locations. CONCLUSIONS: These results may help in understanding the epidemiology of ASF in Vietnam and provide a scientific basis for optimization of current interventions and development of new tools and strategies to reduce transmission of ASF.

Dynamic Models of Within-Herd Transmission and Recommendation for Vaccination Coverage Requirement in the Case of African Swine Fever in Vietnam.

African swine fever (ASF) is a highly contagious disease that is caused by the ASF virus (ASFV) with a high fatality rate in domestic pigs resulting in a high socio-economic impact. The pig business in Vietnam was recently affected by ASF for the first time. This study thus aimed to develop a disease dynamic model to explain how ASFV spreads in Vietnamese pig populations and suggest a protective vaccine coverage level required to prevent future outbreaks. The outbreak data were collected from ten private small-scale farms within the first wave of ASF outbreaks in Vietnam. Three methods were used to estimate the basic reproduction number (R0), including the exponential growth method, maximum likelihood method, and attack rate method. The average R0 values were estimated at 1.49 (95%CI: 1.05-2.21), 1.58 (95%CI: 0.92-2.56), and 1.46 (95%CI: 1.38-1.57), respectively. Based on the worst-case scenario, all pigs in a herd would be infected and removed within 50 days. We suggest vaccinating at least 80% of pigs on each farm once a commercially approved ASF vaccine is available. However, an improvement in biosecurity levels in small-scale farms is still greatly encouraged to prevent the introduction of the virus.

Machine-learning reinforcement for optimizing multilayered thin films: applications in designing broadband antireflection coatings.

The design and fabrication of nanoscale multilayered thin films play an essential role in regulating the operation efficiency of sensitive optical sensors and filters. In this paper, we introduce a packaged tool that employs flexible electromagnetic calculation software with machine learning in order to find the optimized double-band antireflection coatings in intervals of wavelength from 3 to 5 µm and 8 to 12 µm. Instead of computing or modeling an extremely enormous set of thin film structures, this tool enhanced with machine learning can swiftly predict the optical properties of a given structure with >99.7% accuracy and a substantial reduction in computation costs. Furthermore, the tool includes two learning methods that can infer a global optimal structure or suitable local optimal ones. Specifically, these well-trained models provide the highest accurate double-band average transmission coefficient combined with the lowest number of layers or the thinnest total thickness starting from a reference multilayered structure. Finally, the more sophisticated enhancement method, called the double deep Q-learning network, exhibited the best performance in finding optimal antireflective multilayered structures with the highest double-band average transmission coefficient of about 98.95%.

Learning acoustic responses from experiments: A multiscale-informed transfer learning approach.

A methodology to learn acoustical responses based on limited experimental datasets is presented. From a methodological standpoint, the approach involves a multiscale-informed encoder used to cast the learning task in a finite-dimensional setting. A neural network model mapping parameters of interest to the latent variables is then constructed and calibrated using transfer learning and knowledge gained from the multiscale surrogate. The relevance of the approach is assessed by considering the prediction of the sound absorption coefficient for randomly-packed rigid spherical beads of equal diameter. A two-microphone method is used in this context to measure the absorption coefficient on a set of configurations with various monodisperse particle diameters and sample thicknesses, and a hybrid numerical approach relying on the Johnson-Champoux-Allard-Pride-Lafarge model is deployed as the multiscale-based predictor. It is shown that the strategy allows for the relationship between the micro-/structural parameters and the experimental acoustic response to be well approximated, even if a small physical dataset (comprised of ten samples) is used for training. The methodology, therefore, enables the identification and validation of acoustical models under constraints related to data limitation and parametric dependence. It also paves the way for an efficient exploration of the parameter space for acoustical materials design.

Reduction in Plasmodium falciparum Pfk13 and pfg377 allele diversity through time in southern Vietnam.

BACKGROUND: Plasmodium falciparum has acquired resistance to artemisinin in Southeast Asia, with mutations in the P. falciparum Kelch-13 (Pfk13) gene associated with the resistance phenotype. The widespread use of Artemisinin-based combination therapy (ACT)s in Southeast Asia has led to the selection and spread of parasites carrying mutations in Pfk13. We characterised the allele diversity of Pfk13 and pfg377, an artemisinin-resistance neutral polymorphic gene, in parasite DNA extracted human blood from in southern Vietnam in 2003, 2012, 2015 and 2018. METHOD: This study was conducted in Bu Gia Map commune, Binh Phuoc province, Vietnam, from May 2018 to January 2019. Twenty-four samples from 2018 to 2019, 30 from 2003, 24 from 2012 and 32 from 2015 were analysed. Malaria-infected human blood was collected by finger-prick and used for molecular analysis. A nested-PCR targeting the small subunit ribosomal RNA gene was used for Plasmodium species identification, followed by amplification and nucleotide sequencing of Pfk13 and region 3 of pfg377. Archived blood samples collected in the same region in 2012 and 2015 were also analysed as above for comparison. RESULTS: The genetic diversity of Pfk13 and pfg377 was lower in 2018-2019 compared to 2012 and 2015. The number of distinct Pfk13 mutants decreased from three in 2012 and 2015, P553L, V568G and C580Y, to one, C580Y in 2018-2019. In 2018-2019, the frequency of C580Y mutant strains was 71% (17/24 isolates). All samples were wild type in 2003. In 2012 and 2015, there were single-strain infections as well as co-infections with two mutant strains or with mutant and wild strains, whereas there were no co-infections in 2018. pfg377 allele diversity decreased from five alleles in 2012 to two alleles in 2018-2019. CONCLUSION: The genetic diversity of P. falciparum was reduced at the two genetic loci surveyed in this study, Pfk13 and pfg377. In the case of the former gene, we observed an increase in the prevalence of parasites carrying the C580Y gene, known to confer reduced susceptibility to ACTs. The reduction in the diversity of pfg377 may be linked to the clonal expansion of parasite strains carrying the C580Y mutation, leading to an overall reduction in parasite genetic diversity across the population.

Association Between Soluble Notch Ligand Delta-like Ligand 1 and Bleeding Complications in Patients With Dengue Fever Infection.

Bleeding associated with endothelial damage is a key feature of severe dengue fever. In the current study, we investigated whether Notch ligands were associated with bleeding in 115 patients with confirmed dengue infection in Vietnam. Soluble Notch ligands were determined by means of enzyme-linked immunosorbent assay. Seventeen of 115 patients (14.8%) experienced bleeding manifestations. High soluble delta-like ligand 1 (sDLL1) plasma levels was associated with bleeding (median, 15 674 vs 7117 pg/mL; P < .001). Receiver operating characteristic (ROC) curve analysis demonstrated that sDLL1 had the best test performance (area under the ROC curve, 0.852), with 88% sensitivity and 84% specificity. The combination with alanine aminotransferase and aspartate aminotransferase slightly increased sDLL1 performance. sDLL1 may be useful to guide clinical management of patients with patients in endemic settings.

Estimation of the herd-level basic reproduction number for African swine fever in Vietnam, 2019.

Background and Aim: African swine fever (ASF) is a notifiable viral disease of pigs and wild boars that causes severe economic losses to the swine industry. The pig industry in Vietnam was recently attacked by the ASF virus (ASFV) for the first time in history. However, we lack information regarding the transmissibility of ASF within indoor production systems communities, such as those in Vietnam. Therefore, we aimed to estimate the basic reproduction number (R0) for ASF during the early stages of transmission between farms in indoor production system communities from local and national data in Vietnam. Materials and Methods: The linear regression model approach for the susceptible infectious method was used in this study to estimate the transmission rate and, consequently, the R0 value. Results: The R0 values between-farm of ASF ranged from 1.41 to 10.8 in different scenarios of infectious period duration, from 15 to 30 days at the national and local levels. Conclusion: These results help to understand the scale and speed of ASF infection in Vietnam and to provide a scientific basis to implement control measures to restrict the spread of ASFV in other locations.

Antidiabetic Activity of Gomphogyne bonii Gagnep. Extract against High-Fat Diet and Alloxan-Induced Type 2 Diabetes in Mice.

So far, diabetes mellitus has become a health threat to society all over the world. Especially, people with diabetes have always coped with complications related to this disease and unexpected side effects of synthetic drugs. Thus, there has been a current trend for researchers to find out new natural ingredients which were safer and still effective in the treatment of diabetes. Gomphogyne bonii Gagnep. extract (G. bonii extract) was an herbal-derived product of the Pharmacy Department, Vietnam University of Traditional Medicine. This study was designed to assess the antidiabetic effect of G. bonii extract on a high-fat diet (HFD) and alloxan-induced diabetes in mice. Mice were first fed a high-fat diet for 8 weeks and then given an intraperitoneal injection of alloxan (ALX) at the dose of 180 mg/kg b.w. After the diabetic mice model was successfully established, mice were administered orally with G. bonii extract at two doses of 4 mL/kg b.w/day and 12 mL/kg b.w/day for 2 weeks. The results revealed that G. bonii extract at both doses ameliorated the effects of ALX on the concentration of glucose, total cholesterol (TC), triglyceride (TG), and low-density lipoprotein-cholesterol (LDL-C) and microhistological images of livers. Besides, the antidiabetic effect of G. bonii extract at the dose of 12 mL/kg b.w/day was better than that at the dose of 4 mL/kg b.w/day. This suggested that G. bonii extract could be a potential agent for treating diabetes mellitus in clinical practice.

Circulating miR-147b as a diagnostic marker for patients with bacterial sepsis and septic shock.

BACKGROUND: Early diagnosis, precise antimicrobial treatment and subsequent patient stratification can improve sepsis outcomes. Circulating biomarkers such as plasma microRNAs (miRNAs) have proven to be surrogates for diagnosis, severity and case management of infections. The expression of four selected miRNAs (miR-146-3p, miR-147b, miR-155 and miR-223) was validated for their prognostic and diagnostic potential in a clinically defined cohort of patients with sepsis and septic shock. METHODS: The expression of plasma miRNAs was quantified by quantitative PCR (qPCR) in patients with bacterial sepsis (n = 78), in patients with septic shock (n = 52) and in patients with dengue haemorrhagic fever (DHF; n = 69) and in healthy controls (n = 82). RESULTS: The expression of studied miRNA was significantly increased in patients with bacterial sepsis and septic shock. The plasma miR-147b was able to differentiate bacterial sepsis from non-sepsis and septic shock (AUC = 0.77 and 0.8, respectively, p≤ 0.05), while the combination of plasma miR-147b and procalcitonin (PCT) predicted septic shock (AUC = 0.86, p≤ 0.05). CONCLUSIONS: The plasma miR-147b may be an useful biomarker independently or in combination with PCT to support clinical diagnosis of sepsis and equally prognosis of patients with septic shock.

Molecular detection of blaCTX-M gene to predict phenotypic cephalosporin resistance and clinical outcome of Escherichia coli bloodstream infections in Vietnam.

BACKGROUND: Blood stream infections (BSI) caused by Extended Spectrum Beta-Lactamases (ESBLs) producing Enterobacteriaceae is a clinical challenge leading to high mortality, especially in developing countries. In this study, we sought to describe the epidemiology of ESBL-producing Escherichia coli strains isolated from Vietnamese individuals with BSI, to investigate the concordance of genotypic-phenotypic resistance, and clinical outcome of ESBL E. coli BSI. METHODS: A total of 459 hospitalized patients with BSI were screened between October 2014 and May 2016. 115 E. coli strains from 115 BSI patients were isolated and tested for antibiotic resistance using the VITEK®2 system. The ESBL phenotype was determined by double disk diffusion method following the guideline of Clinical and Laboratory Standards Institute. Screening for beta-lactamase (ESBL and carbapenemase) genes was performed using a multiplex-PCR assay. RESULTS: 58% (67/115) of the E. coli strains were ESBL-producers and all were susceptible to both imipenem and meropenem. Resistance to third-generation cephalosporin was common, 70% (81/115) were cefotaxime-resistant and 45% (52/115) were ceftazidime-resistant. blaCTX-M was the most common ESBL gene detected (70%; 80/115) The sensitivity and specificity of blaCTX-M-detection to predict the ESBL phenotype was 87% (76-93% 95% CI) and 54% (39-48% 95% CI), respectively. 28%% (22/80) of blaCTX-M were classified as non-ESBL producers by phenotypic testing for ESBL production. The detection of blaCTX-M in ESBL-negative E. coli BSI was associated with fatal clinical outcome (27%; 6/22 versus 8%; 2/26, p = 0.07). CONCLUSION: A high prevalence of ESBL-producing E. coli isolates harbouring blaCTX-M was observed in BSI patients in Vietnam. The genotypic detection of blaCTX-M may have added benefit in optimizing and guiding empirical antibiotic therapy of E. coli BSI to improve clinical outcome.

Mapping the potential aggregation values of ecotourism landscapes from stakeholder survey, structural equation modeling and GIS: Case study of Moc Chau site, Vietnam.

The primary aim of this study is to propose a potential landscape value assessment from different dimensions rather than the traditional approach of a composite indicator. The method used in this study is the combination of data collection from stakeholder survey, score measurement for landscape value dimensions using Structural Equation Modeling (SEM), and spatial representation with the support of Geographic Information System (GIS). From a large-scale (n = 400) investigation in the Moc Chau district, the statistical data extracted from the survey provides input data for the score determination process. SEM analysis shows that each landscape site has 11 determinants influencing the landscape value assessment. Using the RMSE comparison (for validation) with different interpolation methods, the ordinary kriging method is chosen to model the aggregation landscape value map of Moc Chau District. About 24.97% total area of the study area has great potential for tourism development, being mainly distributed in the center of a high mountainous area. This approach can be used as a model to advocate local and regional assessment and enhance value-based management in other territories in Vietnam and beyond.

Microstructure, Texture and Mechanical Properties in Aluminum Produced by Friction-Assisted Lateral Extrusion.

The Friction-Assisted Lateral Extrusion Process (FALEP) is a severe plastic deformation (SPD) technique for producing metal sheets from bulk metal or powder in one single deformation step at room temperature. In the present work, aluminum Al-1050 was deformed by FALEP. Then, its microstructure was examined by EBSD; the crystallographic texture by X-ray; material strength, ductility, and the Lankford parameter by tensile testing; the latter also by polycrystal plasticity simulations. It is shown that the microstructure was highly refined, with the grain size reduced more than 160 times down to 600 nm under the imposed shear strain of 20. The obtained texture was a characteristic simple shear texture with a shear plane nearly parallel to the plane of the sheet. The yield and ultimate strengths increased by about 10 times and three times, respectively. The Lankford parameter was 1.28, which is very high for aluminum, and due to the specific shear texture, unusual in a sheet. All these exceptional characteristics of Al-1050 were obtained thanks to the efficiency of the FALEP SPD process, which is a promising candidate for industrial applications.

Computational methods for cancer driver discovery: A survey.

Identifying the genes responsible for driving cancer is of critical importance for directing treatment. Accordingly, multiple computational tools have been developed to facilitate this task. Due to the different methods employed by these tools, different data considered by the tools, and the rapidly evolving nature of the field, the selection of an appropriate tool for cancer driver discovery is not straightforward. This survey seeks to provide a comprehensive review of the different computational methods for discovering cancer drivers. We categorise the methods into three groups; methods for single driver identification, methods for driver module identification, and methods for identifying personalised cancer drivers. In addition to providing a "one-stop" reference of these methods, by evaluating and comparing their performance, we also provide readers the information about the different capabilities of the methods in identifying biologically significant cancer drivers. The biologically relevant information identified by these tools can be seen through the enrichment of discovered cancer drivers in GO biological processes and KEGG pathways and through our identification of a small cancer-driver cohort that is capable of stratifying patient survival.