Impacts of Compaction Load and Procedure on Stress-Deformation Behaviors of a Soil Geosynthetic Composite (SGC) Mass—A Case Study

Fill compaction in the construction of Geosynthetic Reinforced Soil (GRS) mass is typically performed by operating a vibratory or roller compactor, which in turns imposed a compaction load in direction perpendicular to the wall face. The compaction process resulted in the development of the so-called compaction-induced stress (CIS), which may subsequently increase the stiffness and strength of the fill material. Compaction process is normally simulated using one of the following compaction procedures—(i) a uniformly distributed load acting on the top surface of each soil lift, (ii) a uniformly distributed load acting on the top and bottom surface of each soil lift, and (iii) a moving strip load with different width. Uncertainties such as compaction procedures, compaction and surcharge loads led to the disparity in studying the mechanism of GRS mass. This paper aimed to study the impact of compaction load, compaction procedure, surcharge load and CIS on the stress-deformation behavior of GRS mass via the simulation of a 2 m high Soil Geosynthetic Composite (SGC) mass and a 6 m high GRS mass. The results were examined in terms of reinforcement strains, wall lateral displacements, and net CIS. Results from the analysis show the important impacts of compaction conditions on the stress-deformation behavior of SGC mass and the CIS

Mechanical Responses of Soil-Geosynthetic Composite (SGC) Mass under Failure Load

There is an increasing awareness on the major benefits of using soil-geosynthetic composite (SGC) to achieve and maintain the stability of earth-filled embankment. Unlike the mechanically stabilized earth wall, the mechanism of the composite mass is still not fully understood. For examples, current analyses have been limited to an SGC mass with a reinforcement spacing Sv of 0.2 m only; the combined effect of reinforcement and backfill properties is rarely studied; the equation for the estimation of the load-carrying capacity of the SGC mass has only been validated for backfill with maximum particle size dmax between 10 mm and 33 mm and an Sv/dmax ratio between 6 and 20. The consequences of backfill compaction on an SGC mass with different reinforcement spacings are yet to be validated and whether the load-carrying capacity equation would still be applicable for materials with properties falling outside the above ranges. Through the simulation and validation of a field scale SGC mass, this study aims to assess the influence of various reinforcement and backfill parameters on the mechanical responses of a large-scale experimental SGC mass under its working load and failure conditions; the results are presented in terms of the wrapped face lateral displacement, reinforcement axial strain, and load-carrying capacity

Chafe’s Semantic Structure Processes Versus Halliday’s Systemic Functional Grammar Processes

Processes are seen as a language phenomenon involving the participant of various language elements realized by verbals, nominal groups or adverbials. How these elements occur in the processes depends on linguists’ concepts of processes. The paper aims to consider Chafe’s processes and Halliday’s Systemic Functional Grammar processes to see what similarities and differences are. The study was conducted with qualitative methods in order to analyse materials and analyse the data collected. The data include samples extracted from four literary works in English which are The Man of Property, The Old Man and the Sea, the Call of the Wild and the Moon and Sixpence. The findings can point out some differences and similarities of processes by Chafe and Halliday. At the same time, the results will help those who pay much attention to this language phenomenon have a deeper understanding in order to equip themselves with background knowledge of language learning and research

A DENSITY FUNCTIONAL THEORY STUDY OF ANTIOXIDANT ACTIVITY OF ISOTHIOCYANATES IN BROCCOLI SPROUTS (BRASSICA OLERACEA L.)

Antioxidant activity of 9 isothiocyanate derivatives (−N=C=S) extracted from Broccolisprouts (Brassica oleracea L.) has been investigated using density functional theory (DFT) –based computational methods. Through the hydrogen atom transfer (HAT) and single electrontransfer (SET) mechanisms, three thermodynamic parameters including bond dissociationenthalpy (BDE), vertical ionization energy (IE), and vertical electron affinity (EA) werecalculated in the gas phase using B3LYP/6-311++G(3df,3p)//B3LYP/6-311G(d,p) modelchemistry. As a result, the isothiocyanate (ITC) shows potential antioxidant activity via HATmechanism. The most potential antioxidant is 3-isothiocyanato pro-1-en (3ITCP) withBDE(C−H) of 72.9 kcal/mol. The SET mechanism is not dominant in case of the studied ITCs.Moreover, the radicals formed H• removal had more reactive and less stable than the intialneutral compounds with lower IE, higher EA and ω

XRand: Differentially Private Defense against Explanation-Guided Attacks

Recent development in the field of explainable artificial intelligence (XAI) has helped improve trust in Machine-Learning-as-a-Service (MLaaS) systems, in which an explanation is provided together with the model prediction in response to each query. However, XAI also opens a door for adversaries to gain insights into the black-box models in MLaaS, thereby making the models more vulnerable to several attacks. For example, feature-based explanations (e.g., SHAP) could expose the top important features that a black-box model focuses on. Such disclosure has been exploited to craft effective backdoor triggers against malware classifiers. To address this trade-off, we introduce a new concept of achieving local differential privacy (LDP) in the explanations, and from that we establish a defense, called XRand, against such attacks. We show that our mechanism restricts the information that the adversary can learn about the top important features, while maintaining the faithfulness of the explanations.Comment: To be published at AAAI 202

Impact of electronic word of mouth to the purchase intention - the case of Instagram

This research aims to discover and confirm the factors of e-WOM that influence users' shopping intentions on Instagram. The data was collected from 700 customers who belong to Gen Y and Gen Z from 18 to 39 years old who live and work in Vietnam. The research model and the scales were built from the empirical research of e-WOM from Lim (2016); Park et al. (2007); Prendergast et al. (2010). Quantitative methods were performed by Cronbach's Alpha reliability testing, EFA discovery factor analysis, regression, and ANOVA test. The research results showed that the fourth factor of e-WOM positively impacts users' purchase intent on Instagram with decreasing levels as Information Provider's Expertise, the quantity of e-WOM, and the Source credibility of e-WOM, and the quality of e-WOM, respectively. Also, users' purchase intention on Instagram under the impact of e-WOM varies by gender, but there is no difference by age and income

Active Membership Inference Attack under Local Differential Privacy in Federated Learning

Federated learning (FL) was originally regarded as a framework for collaborative learning among clients with data privacy protection through a coordinating server. In this paper, we propose a new active membership inference (AMI) attack carried out by a dishonest server in FL. In AMI attacks, the server crafts and embeds malicious parameters into global models to effectively infer whether a target data sample is included in a client's private training data or not. By exploiting the correlation among data features through a non-linear decision boundary, AMI attacks with a certified guarantee of success can achieve severely high success rates under rigorous local differential privacy (LDP) protection; thereby exposing clients' training data to significant privacy risk. Theoretical and experimental results on several benchmark datasets show that adding sufficient privacy-preserving noise to prevent our attack would significantly damage FL's model utility.Comment: Published at AISTATS 202

NOVEL HPLC-UV METHOD USING VOLATILE BUFFER FOR SIMULTANEOUS DETERMINATION OF AMLODIPINE BESYLATE AND ATORVASTATIN CALCIUM

Objective: The purpose of this work was to develop and validate a novel HPLC-UV method using triethylamine (TEA) as a volatile buffer for simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV).Methods: System suitability, linearity, limit of detection (LOD), limit of quantification (LOQ), selectivity, accuracy, and precision was validated using Hitachi L-2000 system with detector: DAD L-2455 at a detected wavelength of 245 nm. Stationary phase: Phenomenex Luna RP-C18 (250 mm x 4.6 mm, 5 µm) and mobile phase: acetonitrile-methanol-TEA pH 4.0 (ratio 52:18:30 v/v/v) were used. Samples' volume of 20 µl was run at room temperature with the flow rate at 1 ml/min.Results: The linearity demonstrated good correlation in the concentration range at 2-40 ppm and 4-80 ppm for AML and ATV, respectively. The method was repeatable with relative standard deviation (RSD) of the intermediate precision test less than 1%. The recovery rate was 100.03% and 99.58% for AML and ATV, respectively. The method was also validated for dissolution studies with excellent compatibility.Conclusion: A new, simple and easy HPLC-UV method was successfully developed and validated for the determination of AML and ATV in both quantification test and dissolution test.Keywords: Amlodipine, Atorvastatin, Simultaneous, Dissolution, HPLC, Quantification, Volatile buffe

Analytical Method for Predicting Lateral Facing Deflection of Geosynthetic-Reinforced Soil Abutment Walls

Geosynthetic-reinforced soil (GRS) walls have been recently used as bridge abutments to directly support spread footings on the reinforced soil mass. This application reduces the requirement for using traditional deep foundations, such as piles or drilled shafts, to support bridge beams. GRS abutment walls are generally subjected to high footing loads that are close to the wall facing. Although GRS abutment walls with modular block facing have been the subject of a number of studies, there are limited methods to predict the profile of the lateral facing deflections along the height of the GRS abutment walls. Lateral deflections along the facing of GRS walls are of significant importance and are difficult to predict. In practice, design engineers need numerical modeling or software to predict the deflection profile. The objectives of this study were to develop an analytical approach to estimate lateral deflections of the wall facing along the height of the GRS abutment walls. Two sets of equations were developed, and experimental test results were used for verification of the proposed analytical approach. There is agreement between the results from proposed approach and the measured data. The maximum lateral deflections predicted from the proposed equations are almost identical to the measured data. The facing lateral deflection profiles with depth are within close range of measured data. The proposed analytical equations for determining lateral deflections provide an effective and simple tool in design of the GRS abutment walls