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To produce oil and gas from unconsolidated sandstone reservoirs, sand screens are necessary to control sand flowing from the formation into the wells, causing well pluggings. In open hole completion, stand-alone sand screen is an essential component to prevent sand production, thus, selection of suitable sand screens is critical to minimize sand production and optimize the well’s production life. Nowadays, premium screens with steel meshes make the openings of the screen slots complex in shape, resulting in a very different effect of sand retention compared to the traditional screens. The sand retention test is considered a standard and must be conducted to select screen opening and size, which decides the sand prevention capacity of the screen. The paper presents the factors affecting the results of laboratory sand retention tests and proposes solution in the direction of considering the data trend rather than relying completely on the output results. The paper also brings about the evaluation method through the change the screen’s permeability to have better qualitative results compared to the traditional methods.

In this study, we present a comprehensive dual-band ambient radio-frequency (RF) energy harvesting system, consisting of rectenna and power management circuit, to harvest energy from 2.45 and 5.8 GHz Wi-Fi. The rectenna employs a metamaterial antenna based on a split-ring resonator, which possesses omni-directional radiation pattern at both frequencies and compact size (0.18λ × 0.25λ at 2.45 GHz). The dual-band rectifier yields the highest efficiency of 42% at 2.45 GHz and 1 dBm input power, 30% at 5.8 GHz and − 7 dBm input power. The maximum RF-DC efficiency for each band is 72% at − 5 dBm and 27% at − 2 dBm, respectively. The power management circuit, consisting of a storing capacitor and a boost converter, is integrated to produce a stable, sufficient output voltage. The energy harvesting system, with its comprehensiveness, is suitable for supplying low-power wireless sensor nodes for indoor applications.

This article presents a new switched beam antenna (SBA) for indoor localization applications. The SBA consists of seven circularly polarized (CP) element antennas using a novel feeding network. The...

Keyword spotting (or wake-word detection) establishes a major component of human–machine interactions. Maximizing the detection accuracy at a low false alarm rate, while minimizing the footprint si...

Moisturizers play an essential role in maintaining the integrity of the skin barrier by increasing stratum corneum hydration (SCH) and reducing transepidermal water loss (TEWL). According to dermatology and allergy guidelines, moisturizers should be applied on the skin within 3 min after bathing or showering. However, there is very little evidence supporting this recommendation. This study aimed to investigate the effectiveness of immediate and delayed moisturizing after bathing/washing on the improvement of SCH and TEWL.This was a crossover study of 60 healthy Vietnamese volunteers aged 18-25 years. In each subject, SCH and TEWL levels were measured at three areas: non-moisturized, immediate moisturizing after washing, and delayed moisturizing at 30 min after washing.In non-moisturized skin, SCH and TEWL levels were significantly different from the baseline at 60 min after washing, while significantly decreased TEWL levels were observed immediately after moisturizing. In addition, moisturized skin had significantly higher SCH and lower TEWL levels compared with non-moisturized areas at every time point (p 0.05). Interestingly, the percentage changes of SCH and TEWL levels from baseline did not differ between immediately and delayed moisturized areas.Tested moisturizer helped increase SCH and decrease TEWL; however, there was no difference in moisturizing effectiveness between immediate and delayed moisturizing in healthy skin. The recommendation of immediate application of moisturizers after bathing/washing should be reconsidered, and more studies are needed to establish a stronger recommendation.

In this paper, a compact wearable U-shaped monopole antenna operating at 2.4 GHz frequency band is proposed for Medical Body Area Network applications. The antenna has a compact size of 0.37 λ × 0.31 λ , covering a band from 2.14 GHz to 3.03 GHz with a gain of 2.3 dBi at 2.45 GHz, and an efficiency of 93% in free space. In addition, an Electromagnetic Band Gap (EBG) metamaterial is utilized to isolate the integrated antenna on the circuit and the body, reducing the Specific Absorption Rate (SAR). In consequence, an integrated circuit employing the EBG ground plane provides a safe value of SAR (0.68 W/kg) when it is attached to a human arm followed by a 74% reduction of SAR value compared to the circuit without EBG (2.57 W/kg). Furthermore, the on-body efficiency of the EBG-based antenna is improved from 54% to 73.68%. Finally, experimental results of a wearable heart rate and blood oxygen level BLE sensor based on the proposed U-shaped EBG monopole antenna exhibit an average power consumption of 108 mW, a sensitivity of -74 dBm, and a maximum Bluetooth Low Energy (BLE) transmission distance with a mobile phone of 16 m in the complex environment.

Vietnam's mining industry has a long history with mines distributed throughout the country. Ithas contributed significantly to national economic growth. However, it also causes negative impacts onthe environment, thereby affecting sustainable development and mineral resource management.Therefore, mineral resource management is one of the most critical tasks of state management. The factorsthat directly affect this issue are the institutional system and state management tools by the law. Stateinstitutions are an essential tool to regulate behaviors and establish social orders and disciplines in allfields, including mineral resources management. This article presents the current law on managing andexploiting mineral resources to provide orientations and solutions to improve the state institution on theseactivities in Vietnam. Based on clarifying the theory of state institutions and analyzing the current legaldocument systems in Viet Nam, the paper emphasizes the role of appraisal in improving the quality oflegal documents and perfecting state institutions.

Real-world video scenes are usually very complicated as they are mixtures of many different audio-visual objects. Humans with normal hearing ability can easily locate, identify and differentiate sound sources which are heard simultaneously. However, this is an extremely difficult task for machines as the creation of machine listening algorithms that can automatically separate sound sources in difficult mixing conditions has remained very challenging. In this paper, we consider the use of a visual-guided audio source separation approach for separating sounds of different instruments in the video, where detected visual objects are used to assist the sound separation process. We particularly investigate the use of different object detectors for the task. In addition, as an empirical study, we analyze the effect of training datasets on separation performance. Finally, experiment results obtained from a benchmark dataset MUSIC confirm the advantages of the new object detector investigated in the paper.

Automatic segmentation of abdominal organs in CT scans plays an important role in clinical practice. However, most existing benchmarks and datasets only focus on segmentation accuracy, while the model efficiency and its accuracy on the testing cases from different medical centers have not been evaluated. To comprehensively benchmark abdominal organ segmentation methods, we organized the first Fast and Low GPU memory Abdominal oRgan sEgmentation (FLARE) challenge, where the segmentation methods were encouraged to achieve high accuracy on the testing cases from different medical centers, fast inference speed, and low GPU memory consumption, simultaneously. The winning method surpassed the existing state-of-the-art method, achieving a 19× faster inference speed and reducing the GPU memory consumption by 60% with comparable accuracy. We provide a summary of the top methods, make their code and Docker containers publicly available, and give practical suggestions on building accurate and efficient abdominal organ segmentation models. The FLARE challenge remains open for future submissions through a live platform for benchmarking further methodology developments at https://flare.grand-challenge.org/.

In this paper, the circularly polarized (CP) antenna is proposed based on the loop antenna for ambient RF energy harvesting (RFEH) applications. This loop antenna is meandered to achieve a compact size of 30 mm × 50 mm. The proposed CP meandered-loop antenna has a measured bandwidth of 150 MHz at – 10 dB with a center frequency of 2.14 GHz for 3G and 4G technologies. A maximum of 62 % RF-DC conversion efficiency is obtained using the proposed CP antenna and a load of 1.2 KΩ when the power of the incident wave is 0 dBm.

Capturing temporal sensory changes has been the focus in recent research to better understand how consumers perceive food products. This information can be linked to consumer expectations (e.g., liking, satiety) to study the sensory drivers throughout the eating experience, namely temporal drivers. This study explores the use of penalty-lift analyses for each time point in the temporal sensory description to identify the temporal drivers of liking/satiety for different groups of consumers with different patterns in their expectations of satiety. Eight yoghurt samples formulated based on an experimental design, with identical composition, varying in textural properties, were used in the study. Temporal Check-All-That-Apply (TCATA) was used to describe dynamic sensory profiles. Consumers (n = 101) tasted each yoghurt and rated their liking and expected satiety. Cluster analysis of variables around latent variables (CLV) method was applied to cluster consumers based on their expectations of satiety, detecting two relevant clusters. Penalty-lift analysis was used for each time point. Also, the false discovery rate (FDR) was applied to correct p-values for multiple tests responding to sequential time points. Differences were found related to how particle size attributes and flavour intensities drove liking for each cluster at different time points. For cluster 1, while Gritty was positive driver from the middle to the end, Sandy was negative driver in the middle; and Vanilla was positive driver of liking throughout the mastication. For cluster 2, only Sweet was pointed as positive driver at the beginning, and Dry as negative driver in some time points at the middle of the mastication. With regards to expected satiety, main difference was that Gritty (or Sandy) was considered as positive (or negative) driver for cluster 1, but not for cluster 2; significant over the entire time period. These findings demonstrate that the temporal driver approach appears as a suitable method to unveil the drivers of liking/satiety during the eating process in groups of consumers with different eating behaviours and preferences.

Rice is a staple food in Vietnam, and the concern about rice is much greater than that for other foods. Preventing fraud against this product has become increasingly important in order to protect producers and consumers from possible economic losses. The possible adulteration of this product is done by mixing, or even replacing, high-quality rice with cheaper rice. This highlights the need for analytical methodologies suitable for its authentication. Given this scenario, the present work aims at testing a rapid and non-destructive approach to detect adulterated rice samples. To fulfill this purpose, 200 rice samples (72 authentic and 128 adulterated samples) were analyzed by near infrared (NIR) spectroscopy coupled, with partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA). The two approaches provided different results, while PLS-DA analysis was a suitable approach for the purpose of the work, SIMCA was unable to solve the investigated problem. The PLS-DA approach provided satisfactory results in discriminating authentic and adulterated samples (both 5% and 10% counterfeits). Focusing on authentic and 10%-adulterated samples, the accuracy of the approach was even better (with a total classification rate of 82.6% and 82.4%, for authentic and adulterated samples, respectively).

In this work, we propose a smart shoe integrated with a very-low power wireless sensor node operating in Bluetooth Low Energy (BLE) 5.0 standard. The sensor node consists of a miniaturized printed inverted-F antenna, an accelerometer and a gyroscope being placed at the bottom of the shoe to measure footstep-length, running speed and foot landing angle. The maximum power consumption of the sensor is 11 mW and it is sustained by a triboeletric nanogenerator (TENG) which generates power from the friction causing by user's motion itself and an energy storage circuit. The triboelectric energy harvester, having the size of 6 cm × 6 cm, is made of multiple pairs of triboelectric materials can harvest up to 32 mW/m2, enough to supply the sensor node.

Different approaches for handling L-shaped data are compared for the first time in a study conducted with Norwegian consumers. Consumers (n = 101) valuated eight different yoghurt profiles varying in three intrinsic attributes such as viscosity, particle size, and flavour intensity following a full factorial design. Sensory attributes, consumers’ liking ratings, and consumer attributes were collected. Data were analysed using two different approaches of handling L-shaped data: approach one used two-step Partial Least Square (PLS) Regression using L-shaped data including the three blocks such as sensory attributes, consumers’ liking ratings, and consumer attributes, while approach two was based on one-step simultaneous L-Partial Least Square (L-PLS) Regression model of the same three blocks of data. The different approaches are compared in terms of centering, step procedures, interpretations, flexibility, and outcomes. Methodological implications and recommendations for academia and future research avenues are outlined.

ObjectivesHealth care system of many countries are facing a surging burden of COVID-19. Although Vietnam has successfully controlled the COVID-19 pandemic to date, there is a sign of initial community transmission. An estimate of possible scenarios to prepare health resources in the future is needed. We used modelling methods to estimate impacts of mitigation measures on the COVID-19 pandemic in Vietnam.MethodsSEIR model built in the COVIDSIM1.1 tool was adopted using available data for estimation. The herd immunization scenario was with no intervention implemented. Other scenarios consisted of isolation and social distancing at different levels (25%, 50%, 75% and 10%, 20%, 30%, respectively). Outcomes include epidemic apex, daily new and cumulative cases, deaths, hospitalized patients and ICU beds needed.ResultsBy April 8, 2020, there would be 465 infected cases with COVID-19 in Viet Nam, of those 50% were detected. Cumulatively, there would be 1,400 cases and 30 deaths by end of 2020, if 75% of cases was detected and isolated, and 30% of social distancing could be maintained.The most effective intervention scenario is the detection and isolation of 75% infected cases and reduction of 10% social contacts. This will require an expansion of testing capacity at health facilities and in the community, posing a challenge to identify high-risk groups to prioritized testing.ConclusionsIn a localized epidemic setting, the expansion of testing should be the key measure to control the epidemic. Social distancing plays a significant role to prevent further transmission to the community.

Surveillance and outbreak reporting systems in Vietnam required improvements to function effectively as early warning and response systems. Accordingly, the Ministry of Health of Vietnam, in collaboration with the US Centers for Disease Control and Prevention, launched a pilot project in 2016 focusing on community and hospital event–based surveillance. The pilot was implemented in 4 of Vietnam’s 63 provinces. The pilot demonstrated that event-based surveillance resulted in early detection and reporting of outbreaks, improved collaboration between the healthcare facilities and preventive sectors of the ministry, and increased community participation in surveillance and reporting.

A novel wireless sensor network node (WSNN) is presented in this paper where the solar energy harvester system is used as an autonomous power solution for endless battery lifetime. In this sensor node, the meander-line Inverted-F-Antenna (MIFA) is proposed and integrated in a single-CC2650 chip of Texas Instrument. The simple structure, low cost, compact size, high efficiency and low power consumption are advantages of this single-chip WSNN. The experimental results show that MIFA antenna is promising solution to enhance communication performance in WSN. In addition, the investigated single-chip WSNN with multi-wireless technologies including Bluetooth Low Energy and Zigbee as well as 6LowPAN is an attractive device for internet of thing (IoT) applications.

For describing the evolution of sensory properties during eating, dynamic sensory methods are still being developed and optimised. Temporal Dominance of Sensations (TDS) and Temporal Check All That Apply (TCATA) are currently the most used and discussed. The aim of this study was to compare TDS, TCATA and a variant of TDS, performed by modality (M-TDS) in the outcome of the dynamic sensory description. These methods were applied with the same trained panel (n = 10) for the evaluation of the dynamic properties of yoghurt samples, with identical composition, only varying in textural properties. Based on a design of experiment, the yoghurts varied in viscosity (thin/thick), size of cereal particle added (flour/flakes) and flavour intensity (low dose/optimised dose, by adding artificial sweetener and vanilla). The TDS curves revealed that the variation in viscosity and particle size led to differences in perception mainly at the beginning of the eating process (Thin/Thick and Gritty/Sandy). Additionally, all samples were also perceived as Bitter at the end of the eating process. TCATA and TDS by modality results were, generally, in agreement with TDS, but they unveiled more details of the samples’ dynamic profiles in all stages of the eating process, showing the effect of Vanilla and Sweet for the samples with optimised flavour, and the masked perception of Bitter. The duration of the eating process was standardized and split into three time intervals (T0-T40, T41-T80, T81-T100). Panelists’ responses were summarized as frequency values in each time interval. Principal Component Analysis was used to visualize sample trajectories over time in the sensory space, with the need to study up to the third dimension to better understand the trajectories. ANOVA models were used to find the attributes which were significantly differences among products. Panel performance was assessed based on MANOVA models for the three methods. The results indicated that TCATA was more discriminative and panelists were more in agreement. TCATA also described samples in more detail in terms of number of discriminating attributes as compared with TDS. The discussion also centers in the different aspects of perception that could respond to different research questions for the three compared methods.