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Blockchain is a newly emerging technology in the past decade that has significantly impacted various aspects. "Scientific popularization" among IT practitioners on this technology and its use cases become a pressing need. However, constructing an effective blockchain teaching approach for this purpose is a challenging task. A training framework consisting of constructivist and pragmatic approaches is proposed, aiming to provide IT practitioners with an effective Teaching and Learning (T &L) process about blockchain on both theory and application aspects. The outcomes of this study are to 1) propose an effective teaching methodology, 2) assess the effectiveness of constructivist and pragmatic approaches and 3) extract the elements facilitating blockchain T &L. Mixed quantitative and qualitative research methods were adopted, including questionnaires and knowledge quizzes. 1267 participants were involved in the training that implemented the proposed framework. Their performance and responses indicated that the framework is effective and flexible. The findings from this empirical research can serve as a reference for educators in blockchain to implement a systemic approach that facilitates the T &L process and improves the field of blockchain and education in the future.

Introduction Central glucocorticoid receptor (GR) has been found to play an important role in the interpretation of cognitive abnormalities of posttraumatic stress disorder (PTSD), particularly focused on the extinction failure of fear memory. Potential of using GR antagonist as a pharmacological agent to prevent PTSD-related fear memory disruption is worth investigating. Objectives We aimed to examine whether GR antagonist Mifepristone (RU486) administered before single prolonged stress (SPS) can prevent rats from fear memory extinction impairment. Methods In the present study, SPS was employed in rats to induce a rodent model of PTSD. 60 minutes before SPS, RU486 (20 mg/kg) was administered by intraperitoneal injection. Seven days after SPS, rats received a protocol of behavioral testing to measure their abilities of specific fear memory (by a cue-dependent fear conditioning paradigm) and nonspecific spatial memory (by T-maze). Neurochemically, we measured plasma corticosterone with or without dexamethasone suppression, activation ratio of GR and levels of norepinephrine, dopamine, and serotonin in amygdala, paraventricular nucleus, dorsal and ventral hippocampus. Results Our results found that RU486 exerted protective effects on SPS-induced fear extinction impairment. Corticosterone of SPS-RU486 rats was less suppressed by dexamethasone. GR became less activated in dorsal hippocampus of SPS-RU486 rats. Conclusions The findings supported the utility of GR antagonism in preventing the development of PTSD. Disclosure No significant relationships.

Here, the authors report photon-energy-dependent terahertz emission and ultrafast photocurrents from the Weyl semimetal, TaAs. The polarization control of the emission is achieved by excitation of the photocurrents whose direction and magnitude depend on the polarization of the femtosecond optical pulses.

The growing coverage of impervious surfaces within cities has resulted in a decrease in vegetation areas, which in turn has caused the temperature increase in urban region. It has proved that vegetation plays an important role in mitigating urban heat island (UHI) effects such that the city managers and planners have paid more attention on how to plan green lands in city planning related projects. This paper focuses on the detection of the mean land surface temperature (LST) change in residential blocks in Changchun where citizens are have common daily lives. Then, according to the interactive extraction of high spatial resolution images, the regions with great changes in Changchun city during 2016 and 2019 are analyzed and compared with the average surface temperature of each block. According to statistical methods, the mitigation effect of the green space on the plot was obtained. It is helpful for city managers or planners to create a livable environment for citizens.

The geographical information, temporal and spatial distribution of pollution sources cannot be accurately described by the traditional aerosol lidar inversion data. In order to accurately locate the pollution sources and monitor the spatial and temporal distribution of pollutants, an aerosol lidar data visualization method based on ArcGIS is proposed in this paper. A natural neighborhood method is used to perform group interpolation on ArcGIS software, and the range range-extinction coefficient relationship diagram is plotted using the aerosol optical data obtained from Klett inversion algorithm. The geographic information is added to the lidar inversion data in this diagram. The aerosol spatial and temporal distribution range and the direction of aerosol diffusion are accurately displayed directly. The change of aerosol concentration is plotted in different colors, the visually displaying the concentration of pollutants in the detection area is realized. The aerosol detection data in the sunny and haze days in Yinchuan are visualized in this paper. The result shows that this method can quickly determine the geographical location of pollution sources and visualize the spatial and temporal distribution of aerosols. This method can be used to display aerosol data with geographic information for meteorological and environmental protection departments. This method can provide data support for meteorological and environmental protection departments to quickly determine the location and concentration of pollution sources.

For a long time, the research of the optical properties of atmospheric aerosols has aroused a wide concern in the field of atmospheric and environmental. Many scholars commonly use the Klett method to invert the lidar return signal of Mie scattering. However, there are always some negative values in the detection data of lidar, which have no actual meaning，and which are jump points. The jump points are also called wild value points and abnormal points. The jump points are refered to the detecting points that are significantly different from the surrounding detection points, and which are not consistent with the actual situation. As a result, when the far end point is selected as the boundary value, the inversion error is too large to successfully invert the extinction coefficient profile. These negative points are jump points, which must be removed in the inversion process. In order to solve the problem, a method of processing jump points of detection data of lidar and the inversion method of aerosol extinction coefficient is proposed in this paper. In this method, when there are few jump points, the linear interpolation method is used to process the jump points. When the number of continuous jump points is large, the function fitting method is used to process the jump points. The feasibility and reliability of this method are verified by using actual lidar data. The results show that the extinction coefficient profile can be successfully inverted when different remote boundary values are chosen. The extinction coefficient profile inverted by this method is more continuous and smoother. The effective detection range of lidar is greatly increased using this method. The extinction coefficient profile is more realistic. The extinction coefficient profile inverted by this method is more favorable to further analysis of the properties of atmospheric aerosol. Therefore, this method has great practical application and popularization value.

Lidar is an advanced atmospheric and meteorological monitoring instrument. The atmospheric aerosol physical parameters can be acquired through inversion of lidar signals. However, traditional methods of solving lidar equations require many assumptions and cannot get accurate analytical solutions. In order to solve this problem, a method of inverting lidar equation using artificial neural network is proposed. This method is based on BP (Back Propagation) artificial neural network, the weights and thresholds of BP artificial neural network is optimized by Genetic Algorithm. The lidar equation inversion prediction model is established. The actual lidar detection signals are inversed using this method, and the results are compared with the traditional method. The result shows that the extinction coefficient and backscattering coefficient inverted by the GA-based BP neural network model are accurate than that inverted by traditional method, the relative error is below 4%. This method can solve the problem of complicated calculation process, as while as providing a new method for the inversion of lidar equations.

In order to study the environment or climate of an area, it is necessary to understand the composition of atmospheric aerosol particles, as well as microphysical properties, such as extinction cross section, scattering cross section, polarization degree, etc. For a long time, when calculating the microphysical properties of atmospheric aerosol particles, the aerosol particles are always be considered as spheres. Mie theory has been used to calculate the scattering properties of spherical particles with high accuracy. However, in reality, aerosol particles are not only spherical, they have complex composition and different shapes. The influence of non-spherical aerosol particles on atmospheric radiation, scattering and absorption cannot be ignored. Therefore, it is necessary to fully understand the micro-physical characteristics of non-spherical aerosol particles for fully understand the real atmospheric environment. Until now, T-Matrix method is one of the most effective and extensive methods to study the light scattering characteristics of non-sphericalrotationally symmetric aerosol particles. In this paper, the non-spherical aerosol particles extinction section, scattering cross section,the absorption cross section are calculated using T-Matrix method. The extinction, scattering, and the absorption properties arecalculated with variety of different types aerosol particles, and compared with the properties calculated by Mie scattering theory. Itlays a foundation for more accurate simulation of the microphysical properties of aerosol particles in real atmosphere.

A cannular combustor with a 100-KW thermal power was designed with a swirler, primary holes, dilution holes, and cooling holes based on an original gas turbine of a practical application. Further, the combustion process in this combustor was numerically simulated by using Computational Fluid Dynamics (CFD). A methane-reduced chemical mechanism was applied to CFD to simulate the combustion process. The combustion performance, product concentrations, and flow field were analyzed. Experimental data of airflow distribution obtained in previous study were applied in the design process. The present work was reported to verify that the experimental data can be regarded as a guide and optimization basis in the aerodynamic design process. Additionally, the consistency of numerical results and design data indicates that the design in this paper could satisfy the design requirements.

Early identification and management of precancerous lesions at high risk of developing cancers is the most effective and economical way to reduce the incidence, mortality, and morbidity of cancers as well as minimizing treatment-related complications, including pain, impaired functions, and disfiguration. Reliable cancer-risk-predictive markers play an important role in enabling evidence-based decision making as well as providing mechanistic insight into the malignant conversion of precancerous lesions. The focus of this article is to review updates on markers that may predict the risk of oral premalignant lesions (OPLs) in developing into oral squamous cell carcinomas (OSCCs), which can logically be discovered only by prospective or retrospective longitudinal studies that analyze pre-progression OPL samples with long-term follow-up outcomes. These risk-predictive markers are different from those that prognosticate the survival outcome of cancers after they have been diagnosed and treated, or those that differentiate between different lesion types and stages. Up-to-date knowledge on cancer-risk-predictive markers discovered by longitudinally followed studies will be reviewed. The goal of this endeavor is to use this information as a starting point to address some key challenges limiting our progress in this area in the hope of achieving effective translation of research discoveries into new clinical interventions.

A Lean Premixed Prevaporized (LPP) low-emission combustor which is applied with the combustion technology of staged lean fuel is developed. To study the cold flow dynamics and the combustion performance of the LPP combustor, both experimental tests using the Particle Image Velocimetry (PIV) to quantify the flow dynamics and numerical simulation using the Fluent software are conducted respectively. To investigate the emissions of the LPP combustor, four kinds of inlet conditions (viz. 7%, 30%, 85% and 100% F∞ (Thrust Force)) were conducted using numerical simulation. Numerical results are in good agreement with the experimental data. Results show that:1) a Primary recirculation zone (PRZ), a Corner recirculation zone (CRZ) and a Lip recirculation zone (LRZ) exist in the LPP combustor, and the velocity gradients between pilot swirling flow and primary swirling flow have contributed to the exchanges of mass, momentum and energy. 2) With the decrease of thrust force, NO mass fraction, CO2 mass fraction and total pressure losses at the exit of LPP combustor fall gradually. 3) Thermal NO formation rate closely relate to the zone area where gas temperature overruns 1900K and the maximum temperature in LPP combustor. 4) The combustion performance of the LPP combustor proposed in this paper is very well, and through comparative analysis with four kins of typical gas tubine combustor, the NO emission is very low and is equivalent to the CAEP6 43.87%.

Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

Rock sheds have been widely used to protect against rockfall. Traditionally, a cushion layer is placed on the top of a rock shed to reduce the impact force and dissipate energy. However, heavy cushion layers lead to high dead loads and increased construction costs. This paper discusses the concept of an impact-resilient flexible buffer structure. On the basis of that concept, it also proposes a buffer structure mainly composed of springs, ring nets, spring rods, and support ropes, which can be used to replace the traditional cushion layer on a shed for rockfall protection. Full-scale impact tests were conducted to study the impact-resilient characteristic of the structure combined with numerical simulation. The dynamic responses of the buffer structure, including force, deformation, and energy dissipation, were analysed in depth. Finally, parametric numerical simulations of 33 models were conducted; the spring stiffness of these models ranged from 300 kN/m to 1500 kN/m; the impact energy ranged from 100 kJ to 2000 kJ. Moreover, simple approaches for estimating the impact force and braking distance of the buffer structure were proposed and verified using measured data obtained from the impact test.

Cellular retinol-binding protein II (CRBP II) belongs to the family of cellular retinol-binding proteins and plays a major role in absorption, transport, and metabolism of vitamin A. In addition, because vitamin A is correlated with reproductive performance, we measured CRBP II mRNA abundance in erlang mountainous chickens by real-time PCR using the relative quantification method. The expression of CRBP II showed a tissue-specific pattern and egg production rate-dependent changes. The expression was very high (p

The appearance of cystic Brunner’s gland hamartomas (BGHs) on computed tomography (CT) or magnetic resonance imaging (MRI) has only been reported in a very small number of cases. Imaging diagnosis of cystic BGHs is usually difficult. We present a case of cystic BGH and characterize it in conjunction with previously reported cases. We found that the cysts of BGHs are smaller than those of other cystic duodenal lesions. The presence of cysts in BGHs can limit the differential diagnosis to cystic duodenal lesions, and our observations may assist others in the discrimination of cystic BGHs from other cystic duodenal lesions.

Pentaherb formula (PHF) has been proven to improve the quality of life of children with atopic dermatitis without side effects. The aim of this study was to elucidate the potential anti-inflammatory and anti-allergic activities of PHF, Moutan Cortex (Danpi/DP) and gallic acid (GA) using human basophils (KU812 cells), which are crucial effector cells in allergic inflammation. PHF, DP and GA could significantly suppress the expression of allergic inflammatory cytokine IL-33-upregulated intercellular adhesion molecule (ICAM)-1, and the release of chemokines CCL2, CCL5, CXCL8 and inflammatory cytokine IL-6 from KU812 cells (all p < 0.05). With the combined use of dexamethasone (0.01 μg/mL) and GA (10 μg/mL), the suppression of ICAM-1 expression and CCL5 and IL-6 release of IL-33-activated KU812 cells were significantly greater than the use of GA alone (all p < 0.05). The suppression of the IL-33-induced activation of intracellular signalling molecules p38 mitogen activated protein kinase, nuclear factor-kB and c-Jun amino-terminal kinase in GA-treated KU812 cells could be the underlying mechanism for the suppression on ICAM-1, chemokines and cytokines. The combined use of dexamethasone with the natural products PHF or DP or GA might therefore enhance the development of a novel therapeutic modality for allergic inflammatory diseases with high potency and fewer side effects.

The ability of droplet digital PCR (ddPCR) to accurately determine the concentrations of amplifiable targets makes it a promising platform for measuring copy number alterations (CNAs) in genomic biomarkers. However, its application to clinical samples, particularly formalin-fixed paraffin-embedded specimens, will require strategies to reliably determine CNAs in DNA of limited quantity and quality. When applied to cancerous tissue, those methods must also account for global genetic instability and the associated probability that the abundance(s) of one or more chosen reference loci do not represent the average ploidy of cells comprising the specimen. Here we present an experimental design strategy and associated data analysis tool that enables accurate determination of CNAs in a panel of biomarkers using multiplexed ddPCR. The method includes strategies to optimize primer and probes design to cleanly segregate droplets in the data output from reaction wells amplifying multiple independent templates, and to correct for bias from artifacts such as DNA fragmentation. We demonstrate how a panel of reference loci can be used to determine a stable CNA-neutral benchmark. These innovations, when taken together, provide a comprehensive strategy that can be used to reliably detect biomarker CNAs in DNA extracted from either frozen or FFPE tissue biopsies.

Objective: We assessed association of retinal micro-vessel diameter with central and peripheral BP. Methods: We post-processed retinal photographs taken in 514 subjects randomly selected from a Flemish population (mean age, 50.6 years; 50.8% women), using IVAN software to generate retinal arteriolar (CRAE) and venular (CRVE) equivalents. We measured peripheral and central BP by mercury sphygmomanometry and tonometry at the carotid artery (SphygmoCor software), respectively. We applied stepwise regression, considering as covariables in addition to BP sex, age, body mass index, smoking, drinking, antihypertensive drug treatment, and serum cholesterol. Results: CRAE and CRVE averaged 153μm and 219μm. Effect sizes (ìm) for CRAE for 1–SD increase in peripheral vs. central BP were –3.77 vs. –3.52 systolic, –3.16 vs. –3.13 diastolic, –3.84 vs. –3.64 for mean BP, and –2.07 vs. –1.83 for pulse pressure (P≤0.006). Models that included two BP components demonstrated that CRAE decreased (P≤0.035) with systolic (peripheral vs. central, –2.87 vs. –2.40) and diastolic (–1.58 vs. –1.80) BP. CRAE decreased with mean BP (–3.53 vs. –3.53; P