Test Area Research Articles

A Split-Face Comparison of Novel Microneedle Patch versus Botulinum Toxin-A and Microneedle Patch for Improvement in Undereye Skin Texture

(1) Background: The emergence of microneedle patch technology and its development as a transdermal drug delivery platform have shown proven results in improving skin texture and appearance. This study was conducted to determine the efficacy of the microneedle patch (MNP)-only cosmesis of undereye skin texture and wrinkles against patch cosmesis with diluted botulinum toxin-A. (2) Methods: A total of 23 Thai females volunteered for this prospective clinical trial. Each participant was treated according to a split-face design, with the application of diluted botulinum toxin-A through MNP technology to the right undereye and a normal saline MNP application to the left undereye. Test areas were recorded at baseline and 2, 4, 8, 12, and 16 weeks after the initial treatment. (3) Results: Botulinum toxin-A was successfully delivered to the skin by MNP technology. After the initial treatment, these novel transdermal drug delivery patches significantly improved infraorbital hollowness at week 8 and wrinkles at week 16. In addition, the skin surface was markedly enhanced, with no adverse effects observed during the trial. (4) Conclusions: Novel MNPs are an effective and safe technology for use in the management of undereye skin aging. Combination treatment with botulinum toxin-A-impregnated devices gave a higher patient satisfaction than MNPs alone.

A Noval Solar Simulator to Explore Envirnoment Impacts On Panel Efficiency

The paper provided a complete hardware design for a solar simulator for versatile environmental conditions. These conditions include shading, humidity, dust, and temperature. In this work, the solar simulator was designed and fabricated to analyze the performance of PV panels with and without air cooling mechanisms in indoor tests. The halogen bulbs with built-in reflector support by the steel structure holder act as natural sunlight. The challenge for a solar simulator is stable uniform solar radiation and illumination. The uniform solar radiation of 7,575 candela was measured in the test area. Several units of PV panels were tested on variable environmental conditions. The air-cooling mechanism with a speed of 200 km/h decreases the surface PV panels with an air-cooling mechanism decreased by 2.3 ˚C. This increases the efficiency of the panel by 6.11 % of the maximum power output based on different fixed solar radiation. They have also compared it by hardware and by simulation method. An overall method and procedure of the measurement by the solar simulator are discussed and proposed

Fracture mechanisms of selective laser sintered parts manufactured in build direction

Selective laser sintering (SLS) is an additive manufacturing process that, in addition to rapid prototyping, is becoming increasingly popular to produce end-use parts. Predictable mechanical properties of the produced parts through this process is a desired primary goal. It has long been known that the mechanical properties especially the elongation at break of SLS components decrease in the build direction. In various test series with tensile specimen fabricated in build direction by SLS, it was found that, on the one hand, these have a very large scatter of the elongation at break, and, on the other hand, it was noticed that these frequently break outside the test range in the upskin radius. The upskin area describes regions that point in a positive build direction relative to the building plate. The fracture occurs at a point where, due to the specimen cross-section, a lower fracture stress occurs than in the test area of the specimen. This fracture leads to a much lower elongation at break than in the case of specimens that fracture in the test area. This study investigates which mechanism triggers this behavior. It turns out that different roughnesses can be determined in the upskin and downskin radius and different defects can be seen in the fracture surfaces, especially in the edge areas. It cannot be predicted based on surface roughness measurements or surface profiling exactly where, or in which layer the fracture occurs. However, the defects lead to a local stress spike, at which the failure of the specimen begins.

U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia.

Accurate and comparable annual mapping is critical to understanding changing vegetation distribution and informing land use planning and management. A U-Net convolutional neural network (CNN) model was used to map natural vegetation and forest types based on annual Landsat geomedian reflectance composite images for a 500 km × 500 km study area in southeastern Australia. The CNN was developed using 2018 imagery. Label data were a ten-class natural vegetation and forest classification (i.e., Acacia, Callitris, Casuarina, Eucalyptus, Grassland, Mangrove, Melaleuca, Plantation, Rainforest and Non-Forest) derived by combining current best-available regional-scale maps of Australian forest types, natural vegetation and land use. The best CNN generated using six Landsat geomedian bands as input produced better results than a pixel-based random forest algorithm, with higher overall accuracy (OA) and weighted mean F1 score for all vegetation classes (93 vs. 87% in both cases) and a higher Kappa score (86 vs. 74%). The trained CNN was used to generate annual vegetation maps for 2000-2019 and evaluated for an independent test area of 100 km × 100 km using statistics describing accuracy regarding the label data and temporal stability. Seventy-six percent of pixels did not change over the 20 years (2000-2019), and year-on-year results were highly correlated (94-97% OA). The accuracy of the CNN model was further verified for the study area using 3456 independent vegetation survey plots where the species of interest had ≥ 50% crown cover. The CNN showed an 81% OA compared with the plot data. The model accuracy was also higher than the label data (76%), which suggests that imperfect training data may not be a major obstacle to CNN-based mapping. Applying the CNN to other regions would help to test the spatial transferability of these techniques and whether they can support the automated production of accurate and comparable annual maps of natural vegetation and forest types required for national reporting.

An Analysis of the Fire Performance of Small-Scale Canadian Heritage Hardwood and Softwood

A common consideration in the rehabilitation of historic timber structures is addressing the concerns for fire safety. Heritage structures can have softwoods but depending on the time they were built they may also have hardwoods present. Currently, there is a lack of knowledge on the char rate of heritage hardwood and softwood. This study presents initial findings into the charring of these historic materials as they would be encountered in practice through samples taken from pre-existing aged timber structures in Canada that are greater than 100 years old. The materials were tested in a cone calorimeter following a modified ASTM 1354 procedure. Hardwood samples typically exhibited a faster charring rate than the softwoods but the charring rates converged at 1.05 mm/min when exposed to higher fluxes of 50 kW/m2. As rehabilitation and readaptation may require performance-based approaches such as structural fire modelling, a provisional framework for a numerical model using LS DYNA for historic timber members is presented. The objective is to identify future research and testing areas to develop a higher certainty model. In the a-priori model presented, results showed conservative charring rate results with charring trends seen in the experiment generally being followed.

Infiltrating Functional English for Technical Students with the Concomitant of Project Transcripts: A Paradigm in Education

A powerful communication strategy plays a key role in professional settings, all the while demonstrating its ability to garner admiration and respect. Over time, Language is an ever-evolving system from a usage standpoint. Despite several existing methods, the quality of knowledge of technical communication remains a persistent challenge for non-native speakers at the instructional level. This paper explores how engineering students can acquire an understanding of and practice functional technical English by preparing micro and macro projects. This study examined 200 student projects, each comprising 20 pages and approximately 300 lines. These projects serve for statistical analysis and are evaluated based on specific five test areas, such as usage of tense, change of voice, concord, vocabulary, and connectors. The two groups (EG & CG) were offered pretest and post-test. The result of the analysis is interpreted with the help of line graphs that assess the comparability of the two groups. Remedial measures with sequence flow charts were suggested to the participants that served the purpose of mending their deficient areas, which, if believed, would enhance their career progression. This method would assist tertiary-level students in breaking language barriers, enabling them to express their ideas in writing and speaking more effectively using technical language, especially in the ordinary usage of technical means to explain complex technical principles. A language is language, when reflected in the correct sense with the ability to use it functionally rather than learning it for years.

Intelligent Light Emitting Diode Flashing Supplementary Lighting Control Design and Its Big Data Illumination Analysis

Considering the inherent advantages of the Light Emitting Diode (LED) in the field of illumination, this work designs an intelligent supplementary lighting system using LED as the light source. Combining microcontroller and electronic circuit theory, the circuit is built with the microcontroller PIC16F873 as the core control chip. The system utilizes an external 220 V AC-20 V DC conversion power supply, hence operating on a 20 V DC power source. The system consists of four hardware parts: the onboard power supply uses TI-produced TPS54331 as the control chip to achieve voltage conversion; the external signals (flashing and burst flashing signals) are isolated from the microcontroller through an optocoupler circuit; the PWM pulses output from the microcontroller’s RC1/CCP2 pins drive the corresponding switching tubes to achieve the flashing function; the flashing synchronization signal is output externally after optocoupler isolation, and its synchronous output with the flashing signal is achieved through an optocoupler after LED conduction; the circuit is established using TI-produced differential bus transceiver SN65LBC184D to convert the external 485 differential signal to the level signal required by the microcontroller. In the experiment, after completing the hardware design, connecting the LED panel, and debugging the test program, it is found that the designed lighting system has a good supplementary lighting effect. According to the PWM output waveform, the flashing effect meets the design expectations. The Hadoop big data computing platform is introduced. Simulation testing reveals that under no backlight conditions, the system achieves an illumination intensity of around 20 klx at a distance of about 10 meters. With backlight conditions, the system maintains an illumination intensity of around 1.5 klx at a distance of about 10 meters. Further calculations are performed to analyze the variation in foot traffic within the test area’s illumination over 24 hours. The total illumination intensity during different time intervals is compiled, confirming that the system can autonomously adjust the illumination intensity of the area based on changes in foot traffic.

Combined algorithms of high-frequency topographical effects for the boundary-value problems based on Helmert's second condensation method

The Helmert’s second condensation method is usually used to condense the topographical masses outside the boundary surface in the determination of the geoid and quasi-geoid based on the boundary-value theory. The condensation of topographical masses produces direct and indirect topographical effects. Nowadays, the Remove-Compute-Restore (RCR) technique has been widely utilized in the boundary-value problems. In view of spectral consistency, high-frequency direct and indirect topographical effects should be used in the Hotine-Helmert/Stokes–Helmert integral when the Earth gravitational model serves as the reference model in determining the (quasi-) geoid. Thus, the algorithms for high-frequency topographical effects are investigated in this manuscript. First, the prism methods for near-zone direct and indirect topographical effects are derived to improve the accuracies of near-zone effects compared with the traditional surface integral methods. Second, the Molodenskii spectral methods truncated to power H4 are put forward for far-zone topographical effects. Next, the "prism + Molodenskii spectral-spherical harmonic" combined algorithms for high-frequency topographical effects are further presented. At last, the effectiveness of the combined algorithms for the high-frequency topographical effects are verified in a mountainous test area.

Distribution and Variation of Soil Water and Salt before and after Autumn Irrigation

Autumn irrigation is a key measure for alleviating soil salinity and promoting sustainable agricultural development in the Hetao Irrigation district; however, only a part of farmland is irrigated in autumn during the non-growth period of crops, which leads to the redistribution of soil water and salt between autumn-irrigated land (AIL) and adjacent non-autumn-irrigated land (NAIL) after autumn irrigation. To explore the distribution and variation of soil water and salt in different positions of AIL and NAIL after local autumn irrigation and reveal the interaction range between AIL and NAIL, field experiments were carried out for two years in typical test areas. The results showed that compared with non-autumn irrigation, autumn irrigation improved the distribution uniformity of soil water and salt profiles in both horizontal and vertical directions; after autumn irrigation, the water content of the soil at the nearest sampling point to the boundary in the AIL increased the least, but the desalination rate was the greatest, while the water and salt contents of the soil within 45 m from the sampling points to the boundary in the NAIL both increased significantly. NAIL received the drainage of AIL and made the groundwater level after the rise in AIL fell quickly back, but unreasonable autumn irrigation caused the groundwater level of AIL to remain at a high level before freezing, exacerbating the risk of groundwater carrying salts to the surface soil during the freezing and thawing period, detrimental to the growth of crops in the next spring. The research results are of great significance to the rational use of farmland water resources and the improvement of soil salinization in cold and dry areas.

Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR

Frequent floods caused by monsoons and rainstorms have significantly affected the resilience of human and natural ecosystems in the Nam Ngum River Basin, Lao PDR. A cost-efficient framework integrating advanced remote sensing and machine learning techniques is proposed to address this issue by enhancing flood susceptibility understanding and informed decision-making. This study utilizes remote sensing geo-datasets and machine learning algorithms (Random Forest, Support Vector Machine, Artificial Neural Networks, and Long Short-Term Memory) to generate comprehensive flood susceptibility maps. The results highlight Random Forest’s superior performance, achieving the highest train and test Area Under the Curve of Receiver Operating Characteristic (AUROC) (1.00 and 0.993), accuracy (0.957), F1-score (0.962), and kappa value (0.914), with the lowest mean squared error (0.207) and Root Mean Squared Error (0.043). Vulnerability is particularly pronounced in low-elevation and low-slope southern downstream areas (Central part of Lao PDR). The results reveal that 36%–53% of the basin’s total area is highly susceptible to flooding, emphasizing the dire need for coordinated floodplain management strategies. This research uses freely accessible remote sensing data, addresses data scarcity in flood studies, and provides valuable insights for disaster risk management and sustainable planning in Lao PDR.

Application of Continuous Stability Control to a Lightweight Solar-Electric Vehicle Using SMC and MPC

This paper investigates the application of contusion stability yaw control of a lightweight solar-electric vehicle. The vehicle’s customized design envelope makes it more sensitive to variations in load due to its low weight and relatively large size. To address this issue, control strategies were developed using differential motor torques to generate direct yaw moments using the vehicle’s rear in-wheel motors. This paper introduces the working conditions of solar vehicles and demonstrates the necessity of stability control. Vehicle parameters such as mass and center of gravity position are obtained to apply control to the real vehicle. The paper then describes two stability control strategies, using (i) sliding-mode control (SMC) and (ii) model predictive control (MPC). To account for the road bank angle of the test area and the impact of additional weight from a driver and passenger, a Kinematic-Based Observer is designed to estimate the vehicle’s side-slip based on measured values. To collect real-time data, a dSPACE MicroAutobox was installed on the solar vehicle. The results show the effect of the observer and controllers under different vehicle speeds and load conditions. Finally, closed-loop simulation results are presented to support the findings from the open-loop testing.

Enhanced Learning and Memory in Patients with CRB1 Retinopathy.

Neuropsychological tests of cognitive function were used to test individuals with CRB1 and non-CRB1 retinopathies and compare results with a standardised normative dataset. CRB1 retinopathy subjects significantly outperformed those with non-CRB1 retinopathy in list learning tasks of immediate (p = 0.001) and delayed memory (p = 0.007), tests of semantic verbal fluency (p = 0.017), verbal IQ digit span subtest (p = 0.037), and estimation test of higher execution function (p = 0.020) but not in the remaining tests of cognitive function (p > 0.05). CRB1 retinopathy subjects scored significantly higher than the normal population in all areas of memory testing (p < 0.05) and overall verbal IQ tests (p = 0.0012). Non-CRB1 retinopathy subjects scored significantly higher than the normal population in story recall, verbal fluency, and overall verbal IQ tests (p = 0.0016). Subjects with CRB1 retinopathy may have enhanced cognitive function in areas of memory and learning. Further work is required to understand the role of CRB1 in cognition.

Machine learning assisted classification between diabetic polyneuropathy and healthy subjects using plantar pressure and temperature data: a feasibility study

Automated and early detection of diabetics with polyneuropathy in an ambulatory health monitoring setup may reduce the major risk factors for diabetic patients. Increased and localized plantar pressure associated with impaired pain and temperature is a combination of developing foot ulcers in subjects with polyneuropathy. Although many interesting research works have been reported in this area, most of them emphasize on signal acquisition process and plantar pressure distribution in the foot region. In this work, a machine learning assisted low complexity technique was developed using plantar pressure and temperature signals which will classify between diabetic polyneuropathy and healthy subjects. Principal component analysis (PCA) and maximum relevance minimum redundancy (mRMR) methods were used for feature extraction and selection respectively followed by k-NN classifier for binary classification. The proposed technique was evaluated with 100 min of publicly available annotated data from 43 subjects and provides blind test accuracy, sensitivity, precision, F1-score, and area under curve (AUC) of 99.58%, 99.50%, 99.44%, 99.47% and 99.56% respectively. A low resource hardware implementation in ARM v6 controller required an average memory usage of 81.2 kB and latency of 1.31 s to process 9 s pressure and temperature data collected from 16 sensor channels for each of the foot region.

Research and Application of High Efficiency Pressure Relief Technology for Ultra-high Pressure Hydraulic Slotted Coal Seam

In order to solve the technical problem of efficient pressure relief of the impact coal seam, the principle of ultra-high pressure hydraulic slit relief and anti-impact technology is expounded, and the ultra-high pressure hydraulic slit device with working pressure up to 100MPa is selected as the pressure relief equipment of coal seam. The field test of high-efficiency pressure relief by ultra-high pressure hydraulic slotting in impact coal seam was carried out. The test showed that the slotting radius of No.3 coal in Tangkou Mine could reach 1.5m under the condition of 100MPa slotting pressure. The stress variation in seam area and large diameter drilling area is compared and analyzed. The stress in seam area decreases significantly by 40%. The stress of bolt (cable) and the deformation of surrounding rock in the slit area are investigated. Compared with the large-diameter pressure relief area, the increase value of bolt is lower and the increase value of cable is significant in the hydraulic slit test area. The technical benefits of hydraulic slotting and large-diameter drilling are summarized and compared. The engineering quantity of drilling with ultra-high pressure hydraulic slotting is reduced by 60%, and the coal output is 2.5 times of that of large-diameter drilling. The large-diameter drilling provides limited pressure relief space for coal seam, but the ultra-high pressure hydraulic slotting technology can effectively increase the deformation space in the coal body and reduce the elastic energy stored in the coal pillar, so as to achieve a good pressure relief effect. The field test shows that compared with large diameter drilling, ultra-high pressure hydraulic slotting technology has remarkable effects of pressure relief, shock absorption and shock prevention.

An adaptive iterative reweighted filtering methodology for urban MLS dataset

ABSTRACT This study presents a novel filtering methodology for Mobile Laser Scanning (MLS) data using robust iterative reweighting. Initially, 3D point clouds are projected onto a 2D grid to create surfaces from the lowest points. Weights are assigned based on the Height Above Ground (HAG) of these points. Ground points are distinguished by applying a surface function to the dataset via iterative reweighting. Among the tested four robust weight functions, the Denmark and Beaton-Tukey functions outperformed others, achieving total error values of 2.30 and 2.32 across three test areas, respectively. This method efficiently filters MLS data, irrespective of ground point proportions.

Decontamination of Actinide-contaminated Injured Skin with Ca-DTPA Products Using an Ex Vivo Rat Skin Model.

Skin contamination by α-emitting actinides such as plutonium and americium is a risk for workers during nuclear fuel production and reactor decommissioning. Decontamination of skin is an important medical countermeasure to limit potential internal contamination, particularly in the case of injured skin. Current recommendations include undressing of the victim followed by skin washing using soap or chelating agents, such as diethylene triamine pentaacetic acid (DTPA). The goal of the present work is to assess the efficacy of a novel Ca-DTPA loaded gel to decontaminate injured skin exposed to plutonium or americium as compared to recommended treatments. For decontaminant testing on injured skin, whole body skin was obtained from euthanized rats and lesions created using a metallic brush. Delimited test areas were contaminated with plutonium or americium solutions of known properties. Various protocols were tested including time before contamination, duration of gel application, washing steps, as well as the concomitant addition or not of dressings. Activity was measured in each decontamination product and in skin. Data indicate that healthy skin was easier to decontaminate than damaged skin. On injured skin, we demonstrated an increased decontamination efficacy of the Ca-DTPA gel formulation as compared to the solution. Importantly, gel application alone was effective, and further gel applications could be used for residual activity.

Advances in Two-Dimensional Ion-Selective Membranes: Bridging Nanoscale Insights to Industrial-Scale Salinity Gradient Energy Harvesting.

Salinity gradient energy, often referred to as the Gibbs free energy difference between saltwater and freshwater, is recognized as "blue energy" due to its inherent cleanliness, renewability, and continuous availability. Reverse electrodialysis (RED), relying on ion-selective membranes, stands as one of the most prevalent and promising methods for harnessing salinity gradient energy to generate electricity. Nevertheless, conventional RED membranes face challenges such as insufficient ion selectivity and transport rates and the difficulty of achieving the minimum commercial energy density threshold of 5 W/m2. In contrast, two-dimensional nanostructured materials, featuring nanoscale channels and abundant functional groups, offer a breakthrough by facilitating rapid ion transport and heightened selectivity. This comprehensive review delves into the mechanisms of osmotic power generation within a single nanopore and nanochannel, exploring optimal nanopore dimensions and nanochannel lengths. We subsequently examine the current landscape of power generation using two-dimensional nanostructured materials in laboratory-scale settings across various test areas. Furthermore, we address the notable decline in power density observed as test areas expand and propose essential criteria for the industrialization of two-dimensional ion-selective membranes. The review concludes with a forward-looking perspective, outlining future research directions, including scalable membrane fabrication, enhanced environmental adaptability, and integration into multiple industries. This review aims to bridge the gap between previous laboratory-scale investigations of two-dimensional ion-selective membranes in salinity gradient energy conversion and their potential large-scale industrial applications.

Study on Construction Status and Development Suggestions of Intelligent Connected Vehicle Test Area in China

Intelligent connected vehicle is the key to the competition in the second half of the automotive industry reform As a key link before technical iteration and commercial application, the test, evaluation, and demonstration application of intelligent connected vehicles have been highly valued by the state and local governments This paper focuses on summarizing the construction of the intelligent connected vehicle test area zone in China, analyzing the construction progress and advanced achievements of the main test zone and pilot zone, and then summarizing the advanced achievements, studying and judging the problems existing in the development of the test area zone, and pushing forward target measures and suggestions to help The high quality development of the intelligent connected vehicle industry in China.

Large‐Area Graphene‐Based Ion‐Selective Membranes with Micro/Meso‐Pores for Osmotic Energy Harvesting

AbstractRenewable osmotic energy between seawater and river water shows great potential in meeting global energy demand. Reverse electrodialysis (RED) technique using ion‐selective membrane is particularly outstanding for its easy operation. Preparing low‐cost and large‐area ion‐selective membranes with excellent ion transport characteristics is particularly important to promote commercial applications. Herein, large‐area ion‐selective membrane is prepared by scraping slurry of flocculated GO (graphene oxide)/PAAS (sodium polyacrylate) solution and then coated with PVA (polyvinyl alcohol)/SA (sodium alginate) gel layer. The PVA/SA molecules can penetrate into the membrane through the unique micro/meso‐pores, which together increase the ion selectivity, membrane permeability, and stability. This ion‐selective membrane can achieve a power density of 8.65 W m−2 under a 50‐fold salinity gradient (NaCl) simulating the sea/river junction environment (with the testing area of 0.0314 mm2). This work significantly promotes the application of GO in large‐area preparation of low‐cost ion‐selective membrane.

Air Leakage Characteristics of Gas Boreholes in Deep Coal Seams and Application of Short-Hole Grouting and Plugging.

Drilling for gas extraction is widely used as the main approach to manage gas in mines. However, gas leakage during borehole extraction reduces the root cause of the effectiveness of gas extraction. Given that forming a normal hole in the prominent coal seam of the Qingdong Coal Mine is impossible and that air leakage leads to difficulties in prepumping gas in the coal seam, we selected coal seam 3# as the object of this study. First, qualitative analysis determined that the air leakage channel restricted effective gas extraction. Second, short-hole grouting and plugging were proposed to increase the concentration and efficiency of gas extraction from the coal wall, forming a barrier by blocking the fissure network in the plastic zone of the surrounding rock of the coal roadway and preventing the air inside the roadway from penetrating into the coal seam and gas extraction drill holes. Finally, evaluation of the gas extraction efficiency between the grouting test and comparison areas indicated that the initial gas extraction concentration of a single hole could reach 89% when the depth of the selected blocking hole was 15 m. Grouting slowly decreased the gas extraction concentration from 72 to 25%, which effectively improved the speed at which the gas content was reduced in the coal body. The study findings provide a field basis for similar mines to improve their gas extraction efficiency and extend their extraction time.