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The train horn sound is an active audible warning signal used for warning commuters and railway employees of the oncoming train(s), assuring a smooth operation and traffic safety, especially at barrier-free crossings. This work studies deep learning-based approaches to develop a system providing the early detection of train arrival based on the recognition of train horn sounds from the traffic soundscape. A custom dataset of train horn sounds, car horn sounds, and traffic noises is developed to conduct experiments and analysis. We propose a novel two-stream end-to-end CNN model (i.e., THD-RawNet), which combines two approaches of feature extraction from raw audio waveforms, for audio classification in train horn detection (THD). Besides a stream with a sequential one-dimensional CNN (1D-CNN) as in existing sound classification works, we propose to utilize multiple 1D-CNN branches to process raw waves in different temporal resolutions to extract an image-like representation for the 2D-CNN classification part. Our experiment results and comparative analysis have proved the effectiveness of the proposed two-stream network and the method of combining features extracted in multiple temporal resolutions. The THD-RawNet obtained better accuracies and robustness compared to those of baseline models trained on either raw audio or handcrafted features, in which at the input size of one second the network yielded an accuracy of 95.11% for testing data in normal traffic conditions and remained above a 93% accuracy for the considerable noisy condition of-10 dB SNR. The proposed THD system can be integrated into the smart railway crossing systems, private cars, and self-driving cars to improve railway transit safety.

Ibuprofen contamination from water sources has been increasingly alarming due to its environmentally accumulative retention; however, the strategies for ibuprofen-containing water treatment are still an enormous challenge. Herein, we described the utilization of metal-organic frameworks MIL-53(Fe) (MIL = Materials of Institute Lavoisier) for the adsorption of ibuprofen in synthetic solution. Firstly, the MIL-53(Fe) was solvothemally synthesized and then characterized using the X-ray diffraction and Fourier-transform infrared spectroscopy techniques. The optimization of ibuprofen adsorption over MIL-53(Fe) was performed with three independent variables including ibuprofen concentration (1.6–18.4 mg/L), adsorbent dosage (0.16–1.84 g/L), and pH (2.6–9.4) according to the experimental design from response surface methodology. Under the optimized conditions, more than 80% of ibuprofen could be eliminated from water, indicating the promising potential of the MIL-53(Fe) material for treatment of this drug. Kinetic and isotherm models also were used to elucidate the chemisorption and monolayer behavior mechanisms of ibuprofen over MIL-53(Fe).

A non-isolated high boost DC-DC converter topology based on a switched-capacitor (SC) structure is introduced in this paper. By controlling the duty cycle in each period, the voltage gain of the converter is adjusted. The main features of the proposed SC converter are the continuous input current, achieving high voltage gain with low voltage and current stress on the power components, no use of a high-frequency transformer, and easy to increase the voltage by adding the SC cell. To correct the operating analysis, a 200-W output power prototype was built with the input voltage in the range of [25 V, 50 V] and the output voltage of 200 V. The proposed inverter reaches a maximum efficiency of 93% at the input voltage of 25 V and the output power of 150 W. The simulation and experimental verifications match the analysis.

In this research, structural, magnetic properties and photocatalytic activity of cobalt ferrite spinel (CoFe2O4) nanoparticles were studied. The samples were characterized by X-ray powder diffraction (XRD), energy dispersive X-ray (EDX), scanning electron microscopy (SEM), transmission electronic microscopy (TEM), Brunauer–Emmett–Teller (BET), Fourier transform infrared spectroscopy (FTIR), and UV-visible diffused reflectance spectroscopy (DRS) analysis. The XRD analysis revealed the formation of the single-phase CoFe2O4 with a cubic structure that is annealed at 500–700 °C in 3 h. The optical band gap energy for CoFe2O4 was determined to be in the range of 1.57–2.03 eV. The effect on the magnetic properties of cobalt ferrites was analyzed by using a vibrating sample magnetometer (VSM). The particle size and the saturation magnetization of cobalt ferrite nanoparticles increased with increasing annealing temperature. The photocatalytic activity of CoFe2O4 nanoparticles was investigated by using rhodamine B dye under visible light. The decomposition of rhodamine B reached 90.6% after 270 min lighting with the presence of H2O2 and CF500 sample.

In this study, a minimum-run resolution IV and central composite design have been developed to optimize tetracycline removal efficiency over mesoporous carbon derived from the metal-organic framework MIL-53 (Fe) as a self-sacrificial template. Firstly, minimum-run resolution IV, powered by the Design–Expert program, was used as an efficient and reliable screening study for investigating a set of seven factors, these were: tetracycline concentration (A: 5–15 mg/g), dose of mesoporous carbons (MPC) (B: 0.05–0.15 g/L), initial pH level (C: 2–10), contact time (D: 1–3 h), temperature (E: 20–40 °C), shaking speed (F: 150–250 rpm), and Na+ ionic strength (G: 10–90 mM) at both low (−1) and high (+1) levels, for investigation of the data ranges. The 20-trial model was analyzed and assessed by Analysis of Variance (ANOVA) data, and diagnostic plots (e.g., the Pareto chart, and half-normal and normal probability plots). Based on minimum-run resolution IV, three factors, including tetracycline concentration (A), dose of MPC (B), and initial pH (C), were selected to carry out the optimization study using a central composite design. The proposed quadratic model was found to be statistically significant at the 95% confidence level due to a low P-value (<0.05), high R2 (0.9078), and the AP ratio (11.4), along with an abundance of diagnostic plots (3D response surfaces, Cook’s distance, Box-Cox, DFFITS, Leverage versus run, residuals versus runs, and actual versus predicted). Under response surface methodology-optimized conditions (e.g., tetracycline concentration of 1.9 mg/g, MPC dose of 0.15 g/L, and pH level of 3.9), the highest tetracycline removal efficiency via confirmation tests reached up to 98.0%–99.7%. Also, kinetic intraparticle diffusion and isotherm models were systematically studied to interpret how tetracycline molecules were absorbed on an MPC structure. In particular, the adsorption mechanisms including “electrostatic attraction” and “π–π interaction” were proposed.

Energy security and pollution are becoming critical issues in the context of climate change and the circular economy, calling for sustainable resources. Asteraceae species, commonly referred as the aster, daisy, composite, or sunflower family, are among the largest flowering plants with 23,000 species belonging to 1600 genera, and are a major source of biomass. Here we review botanical characteristics and applications of Asteraceae for bioenergy, remediation, nanotechnology, medicine, food and agriculture. Sunflower is the most used to produce bio-oils with a yearly production of 47 million tons. Sunflower is also used for phytoremediation of heavy metals such as cadmium, lead, uranium, and chromium. Artichoke, chicory, purple coneflower, and wormwood display medicinal potential with 27–103 bioactive compounds. Artemisia, calendula, and sunflower oil are precursors for cosmetic and perfume production. Asteraceae species exhibited high efficiencies of 90−96% for removal of remazol red, and reactive blue dyes. Asteraceae species are used for fabrication of nanoparticles, biochar, activated carbon and biocomposites.

Background and Objectives: To determine the nutritional status of patients with esophageal cancer, and to investigate its relationship with performance status and prognosis. Methods and Study Design: This clinical, cross-sectional study was conducted from August 2014 to February 2015 at National Cancer Hospital, Hanoi, Vietnam. Stage III/IV esophageal cancer patients were assessed for their nutritional status (patient-generated subjective global assessment (PG-SGA) and SGA scores, BMI, mid-arm circumference (MAC), energy and protein intakes, weight changes, Karnofsky and Eastern cooperative oncology group performance scores (KPS/ECOG), and Glasgow prognostic score (GPS). Results: Sixty-four male patients were enrolled. The mean standard deviation of PG-SGA score was 9.88 4.41. SGA revealed 44% as class B and 6.2% as class C. The BMI revealed 43.8% of patients were underweight. MAC measurement revealed 29.7% of undernourished patients. Patients with an energy intake <25 kcal/kg/d comprised 54.7%, and 48.4% with <1 g/kg/day of protein. Totally, 68.8%, 84.4% and 92.2% patients exhibited weight loss past 2-weeks, one-month and six-months, respectively. The PG-SGA and SGA strongly correlated with the KPS (r=-0.717 and 0.632, both p<0.001) and ECOG (r=0.672 and 0.626, both p<0.001), but were weakly correlated with the GPS (r=0.332 and 0.278, p<0.01 and 0.05). The KPS, ECOG, BMI, MAC, energy and protein intakes, and weight change were not correlated with the GPS. Conclusions: Malnutrition, weight change, and insufficient intake were noteworthy in esophageal cancer patients. The PG-SGA and SGA were strongly correlated with the performance status, but weakly correlated with prognostic indices.

The emergent occurrence of sulfonamide species involving sulfadiazine (SDZ) and sulfamethazine (SMZ) in aquatic systems can cause a wide range of potential risks; hence, remediation strategies need to be necessary. Here, we develop the novel metal-organic framework-derived nanocomposite, and apply for the adsorption of SDZ and SMZ antibiotics. To assess the best-fitting kinetic (pseudo first-order, pseudo second-order) and isotherm (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Redlich-Peterson, Sips, Toth, and Khan) models, a series of numerous statistical analysis was performed. Numerous error functions including squares of the errors (SSE), hybrid fractional error function (HYBRID), Marquardt’s percent standard deviation (MPSD), and mean relative error (MRE) were also analyzed to assess the linear and nonlinear models. The results indicated that both linear and nonlinear kinetic models were mostly fitted well with pseudo second-order models ( R adj ) 2  > 0.97. Although linear kinetics gave better ( R adj ) 2 , error functions (MRE, SSE, HYBRID, and MPSD) were mostly higher than those of nonlinear kinetics. For adsorption isotherm, nonlinear Redlich-Peterson was the most compatible model with extremely high adjusted coefficients of determination ( R adj ) 2  ~ 1.0000. While nonlinear Langmuir model gave relatively high ( R adj ) 2 (0.9898–0.9960) and acceptable error functions, we found the considerable difference of error functions and parameters among four types of linear Langmuir (Types I, II, III, IV). The findings indicate potential errors as selecting one of linearized Langmuir types in equilibrium study. It is suggested that nonlinear models should be applied for better fitness.

Background: Data about the risk factors and pancreatic cancer in developing countries remain limited. We investigated for the first time the role of a number of risk factors (family cancer history, smoking, alcohol consumption, diabetes, inflammation disease, HBV infection) associated with pancreatic cancer among Vietnamese patients. Methods: We included all patients hospitalized at 4 Northern Vietnamese hospitals (Vietnam National Cancer Hospital, Bach Mai, Viet Duc, Thai Nguyen) and diagnosed with pancreatic cancer during the period from 2017 to 2019. Risk factors of eligible patients were collected and assessed the associations using a matched control study and logistic regression model analysis. Results: We identified 196 patients with diagnosis of pancreatic cancer of which 114 males and 82 females. The average age of the patient at the time of diagnosis was 58.28 years (standard deviation of 12.94, ranging from 25 to 87). Most of patients were diagnosed at advanced stage (85%). Smoking, diabetes, inflammation disease significantly increased the cancer risks (OR and 95% CI were 2.42 (1.38-4.37), 3.09 (1.54-6.68), 2.21 (1.42-3.45), respectively). HBV infection demonstrated a significant link with pancreatic cancer in univariate model (OR = 2.94 (1.08-9.36)), but not in multivariate model. However, cancer family history and alcohol drinkers did not show any significantly increased risk related to pancreatic cancer. Conclusions: Our finding showed smoking, diabetes, inflammation disease significantly increased the risk of pancreatic cancer in Vietnam.

Accurate public perceptions on the risk factors associated with cancer are important in promoting primary, secondary, and tertiary prevention. Limited studies have explored this topic among patients with cancer in non-western, low-to-middle-income countries. A cross-sectional survey to compare Australian and Vietnamese cancer patients’ perceptions of what caused their cancer was undertaken. Adult, patients with cancer from both countries, receiving radiotherapy treatment completed a standardized survey, which included a 25-item module assessing their beliefs on the causes of their cancer. Items ranged from known evidence-based causes (eg, smoking, sun exposure) to non-evidence-based beliefs (eg, stress or anxiety, physical injury, or trauma). Country-specific logistic regression analyses were conducted to identify differences in the determinants of patients’ top perceived causes. A total of 585 patient surveys were completed (75% response rate; 285 from Australia, and 300 from Vietnam). Most patients were male (58%) and aged 60 years and older (55%). The most frequently reported risk factor overall and for the Australian sample was “getting older” (overall = 42%, Australia = 49%, and Vietnam = 35%). While the most frequently reported risk factor for the Vietnamese sample was “poor diet” (overall = 39%, Australia = 11%, and Vietnam = 64%). There were differences in the characteristics associated with the top causes of cancer identified by Australian and Vietnamese patients. Patients’ beliefs about what may have caused their cancer are complex and likely to be impacted by multiple factors, including the country from which they reside. Developing public awareness campaigns that are accurate and tailored to address the specific beliefs and possible misconceptions held by the target community are needed.