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Interfacial roughness in heterostructures critically degrade the optical and electrical properties of the devices fabricated with III‐V semiconductor compounds. Experimental work on the surface roughening processes during MBE growth by monitoring the reflection high energy electron diffraction (RHEED) intensity concluded that the surface roughening is a result of competition between surface roughening processes such as adsorption and evaporation and the surface smoothening process such as surface migration to stable sites. In this work, the stochastic model of MBE growth is employed to study the surface roughening kinetics in GaAs (100). The growth condition was chosen similar to that of experiments: temperature range of study: 773 – 873°K; cation to anion flux ratio in the range: 1 : 10 to 1 : 20. Diatomic arsenic molecular specie is employed for the study was As2. The time averaged RHEED intensity was obtained from the growth data and with the experimental results. The agreement between the results was excellent. A transition temperature at which the time averaged RHEED intensity is a maximum was observed for flux ratios 1 : 10 and 1 : 20. The RHEED intensity increases with temperature till the transition temperature due to surface smoothening resulting from the surface migration of Ga and As to energetically favorable sites. The RHEED intensity decreases beyond the transition temperature due to the evaporation of As from the surface. The transition temperature is observed to be a function of the flux ratio and can be explained by the difference in time for the formation of energetically stable surface adatom clusters resulting from the difference in the effective surface migration rates for various flux ratios.

This study aims, a systematic review and meta-analysis, to evaluate the effects of folic acid (folate) on patients with depression.

Related articles were found by searching PubMed, SCOPUS, Web of science and Cochrane’s Library, from inception to January 2022. Weighted mean differences (WMD) were pooled using a random-effects model. Heterogeneity, sensitivity analysis and publication bias were reported using standard methods.

Pooled analysis of six randomized controlled trials revealed that folic acid supplementation decreased the depression score in the Beck Depression Inventory (WMD: −3.9; 95% CI: −5.3 to −2.4, p < 0.001) compared with control group, without heterogeneity (I2 = 0.0%, p = 1.000). It also lowered the depression score in the Hamilton (HAM) Depression Inventory (WMD: −3.5 mg/dL; 95% CI: −4.6 to −2.4, p < 0.001) compared with control group, with moderate heterogeneity (I2 = 71.8%, p = 0.007). Moreover, subgroup analysis showed that the folic acid supplementation reduced HAM in all subgroups. Meta-regression analysis demonstrated that there is no evidence of a significant linear relationship between dose and duration of folic acid supplementation and changes in HAM. Also, based on the non-linear dose response, no evidence of a relationship between dose and duration of folic acid supplementation and changes in HAM was found.

Folic acid supplementation could possibly have an effect on lowering depression in patients. However, the clinical trials thus far are insufficient for clinical guidelines and practice.

This paper aims to investigate the failure modes present in the dangerous operations and modify processes. After the identification of potential failures, prioritization will be made to rank them for quick attention and immediate correction in the operation/modification.

The methodology utilizes the strength of hazard and operability (HAZOP) study and failure mode and effect analysis (FMEA) to identify and prioritize the hidden potential failures present in the system. Fuzzy linguistics approach has been applied to enhance the performance of the study. This study correlates HAZOP study, FMEA and fuzzy system.

This proposed technique is used to find the better ranking of the failure modes. Risk priority number and fuzzy weighted geometric mean of the risk factors are used to improve the performance of the risk evaluation. This makes the assessment easier to be carried out effectively for critically operated systems.

This proposed approach could be very useful for the systematic and rational risk assessment of passive systems.

A new decision‐making approach is used to prioritize the failure modes present in the process industry with use of a case study.

Condition‐based maintenance is the diagnosis of component failure or a prognosis of a component's time to failure. The aim of this paper is twofold: a summary of the main assumptions regarding condition‐based maintenance found in the literature into eight postulates, and a comparison of the postulates against industrial practice. The postulates were formulated regarding the technical system, the managerial system and workforce knowledge.

The postulates were examined in a multiple case study of five large firms in the process industry.

The results indicate that some postulates were supported with empirical findings. Limited or no support was found for postulates concerning the application of prognostic activities, use of dedicated software, use of procedures, use of training, and the active management of domain‐related knowledge availability.

Practitioners can use the eight postulates as key elements in the management of condition‐based maintenance technology, and for the comparison of their current condition‐based maintenance practices with what literature generally proposes.

Other researchers have reported on condition‐based maintenance, but most publications focus on applied mathematics and new monitoring and simulation models. Only limited attention was paid to industrial practice so far. The study is one of the first in‐depth empirical studies into actual condition‐based maintenance practice.

The purpose of this paper is the development of an empirically based typology of condition based maintenance (CBM) approaches, including the relevant characteristics and requirements.

An exploratory case study was conducted in a major gas production facility. The CBM typology that resulted from this case study was subsequently tested against a large set of CBM literature.

In the literature, CBM is usually presented as a single theory or practice. The paper finds that CBM in fact includes several different approaches and that each of the approaches is only suitable in situations where the specific characteristics of the approach match the situational characteristics. Aided by these findings, a new typology for CBM was developed. The typology is based on the method for obtaining the expected value, or trend (through statistical vs analytical modeling) and the type of data used (process vs failure data). A subsequent literature survey reveals that the proposed typology is applicable for the categorization of a large number of CBM cases found in the literature.

One of the most important requirements in selecting and using a CBM approach is the availability and integration of various types of knowledge, in particular process engineering and maintenance engineering knowledge. Practitioners can use these insights to assess current CBM cases, and identify the key characteristics of current and future use of various CBM types.

This paper presents a novel and empirically based framework for the classification of the different CBM types. Such frameworks were lacking in the current literature. The paper adds to maintenance engineering literature by identifying the key dimensions of the various types along with their key requirements.

This paper aims to investigate the photocatalytic activity of zinc doped MAO-TiO₂ films under the optimum MAO treatment condition.

The coating was prepared by micro arc oxidation, and the influence of doping on the properties of the coating was also investigated.

The results show that the BET surface area is 78.25±0.03m²/g, total pore area is 76.32 ± 0.04m²/g, and the total pore volume is 0.2135 ± 0.0004cm³/g. The degradation ratio of the film electrode with Zn-doped in methyl orange solution is up to 94%. When the react circles is 10 times, the degradation ratio is up to more than 85% and remains steady. With the different reaction conditions, these kinetics of the reactions show some different formulas.

A kinetic equation for photocatalytic activity is established.

This paper proposes a novel method of fault detection, which is based on H_/H∞ Runge–Kutta observer and an adaptive threshold for a class of closed-loop non-linear systems. The purpose of this paper is to improve the rapidity and accuracy of fault detection.

First, the authors design the H_/H∞ Runge–Kutta fault detection observer, which is used as a residual generator to decouple the residual from the input. The H_ performance index metric in the specified frequency domain is used to describe how sensitive the residual to the fault. The H∞ norm is used to describe the residual robustness to the external disturbance of the systems. The residual generator is designed to achieve the best tradeoff between robustness against unknown disturbances but sensitivity to faults, thus realizing the accurate detection of the fault by suppressing the influence of noise and disturbance on the residual. Next, the design of the H_/H∞ fault detection observer is transformed into a convex optimization problem and solved by linear matrix inequality. Then, a new adaptive threshold is designed to improve the accuracy of fault detection.

The effectiveness and correctness of the method are tested in simulation experiments.

This paper presents a novel approach to improve the accuracy and rapidity of fault detection for closed-loop non-linear system with disturbances and noise.

The purpose of this paper is to design an out-of-plane micro electro-thermal-compliant actuator based logic gates which work analogously to complementary metal oxide semiconductor (CMOS) based logic gates. The proposed logic gates used a single-bit mechanical micro ETC actuator per logic instead of using 6-14 individual transistors as in CMOS.

A complete analytical modelling is performed on a single ETC vertical actuator, and a relation between the applied voltage and the out-of-plane deflection is derived. Its coupled electro-thermo-mechanical analysis is carried out using micro electro mechanical system (MEMS) CAD tool CoventorWare to illustrate its performance.

This paper reports analytical and numerical simulation of basic MEMS ETC actuator-based logic gates. The proposed logic gate operates on 5 V, which suits well with conventional CMOS logic, which in turn reduces the power consumption of the device.

The proposed logic gates uses a single-bit MEMS ETC actuator per logic instead of using more transistors as in CMOS. The unique feature of this proposed logic gates is that the basic mechanical ETC actuator is customized in its structure to function as specific logic gates depending upon the given inputs.

There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.

A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.

The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.

A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.