Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework

Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety.Small or incipient irregularities may lead to severe degradation in complex chemical processes,and the conventional process monitoring techniques cannot detect these irregularities.In this study to improve the performance of monitoring,an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis(MSPCA) with cumulative sum(CUSUM) and exponentially weighted moving average(EWMA) control charts.The new Hotelling's T~2 and square prediction error(SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data.The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods.The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults.Moreover,a comparative study shows that the SPEEWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.

Convolutional Neural Network for Histopathological Osteosarcoma Image Classification

Osteosarcoma is one of the most widespread causes of bone cancer globally and has a high mortality rate.Early diagnosis may increase the chances of treatment and survival however the process is time-consuming(reliability and complexity involved to extract the hand-crafted features)and largely depends on pathologists’experience.Convolutional Neural Network(CNN—an end-to-end model)is known to be an alternative to overcome the aforesaid problems.Therefore,this work proposes a compact CNN architecture that has been rigorously explored on a Small Osteosarcoma histology Image Dataaseet(a high-class imbalanced dataset).Though,during training,class-imbalanced data can negatively affect the performance of CNN.Therefore,an oversampling technique has been proposed to overcome the aforesaid issue and improve generalization performance.In this process,a hierarchical CNN model is designed,in which the former model is non-regularized(due to dense architecture)and the later one is regularized,specifically designed for small histopathology images.Moreover,the regularized model is integrated with CNN’s basic architecture to reduce overfitting.Experimental results demonstrate that oversampling might be an effective way to address the imbalanced class problem during training.The training and testing accuracies of the non-regularized CNN model are 98%&78%with an imbalanced dataset and 96%&81%with a balanced dataset,respectively.The regularized CNN model training and testing accuracies are 84%&75%for an imbalanced dataset and 87%&86%for a balanced dataset.

Total Particulate Matter and Wound Healing: An in vivo Study with Histological Insights

Objectives Wound healing in the skin is a multifarious orchestration of cellular processes and cigarette smoking may be a cause for delayed wound healing. The aim of this study was to investigate the plausible association between exposures of cigarette total particulate matter （TPM） and wound healing. Methods An in vivo wound healing model of mice was established for determination of assorted events of wound healing, dermal matrix regeneration, re-epithelialization, and neovascularization. A total of 72 adult mice, separated in eight groups, were exposed to TPM for 12 days. Results A highly considerable diminution in wound closure （P〈0.001） was pragmatic among all TPM-treated mice from day 6 to day 8 post-wounding. Histological investigations unveiled a noteworthy impede in the outcome of re-epithelialization, dermal matrix regeneration and maturation of collagen bundles among all TPM-exposed wounds. Delayed commencement of neovascularization was pragmatic among all TPM-treated mice, on day 12 post wounding. Abbot curve, angular spectrum, and other different parameters of 3D surface behavior of wounds revealed a very highly significant reduction （P〈0.001） in angiogenesis on days 6 and 8 post-wounding, which points that application of TPM instigates extensive delay in trigging the progression of angiogenesis, resulting in delayed onset of wound healing. Conclusion Our annotations validate the damaging effects of TPM on wound healing and excessive use of TPM may lead to the production of chronic wounds and oral ulcers.

A Longitudinal Survey for Genome-based Identification of SARS-CoV-2 in Sewage Water in Selected Lockdown Areas of Lahore City, Pakistan: A Potential Approach for Future Smart Lockdown Strategy

In 2019,the newly emerged SARS-CoV-2 virus caused pneumonia-like illness.The disease rapidly spread globally,leading to a worldwide outbreak referred to as the COVID-19 pandemic.

GIS Based Management System for Photovoltaic Panels

This paper provides a proposal of implementation of latest technologies in photovoltaic installation and management system. Punjab Government Cooperative Housing Society was selected to find out suitability for photovoltaic installation and its management after that. Google Earth imagery and scanned maps were selected for the preparation of spatial and attribute data of buildings in the study area by using ArcGIS software. In first stage data were digitized and suitability and potential for each building were estimated. In second stage all the tabular data which consisted of owner information, panel information, its potential and location were linked to each other for management purpose. Selected area for solar panels installation was linked to building information for query and visualization.

Simultaneous Determination of Amlodipine with H₁-Receptor Antagonists by Reversed Phase High Performance Liquid Chromatography and Application to Interaction Studies

A rapid, fast and precise method has been developed and validated for the simultaneous determination of amlodipine with H1-receptor antagonists (cetirizine, fexofenadine, and buclizine) from dosage forms. The chromatography was performed on a Purospher? Star, C18 (5 mm, 250 × 4.6 mm) column using acetonitrile: buffer (0.01 mM) (40:60, v/v, pH adjusted to 3.0), as a mobile phase. The mobile phase was pumped at a flow rate of 1.0 mL·min-1 and UV detection was performed at 240 nm. The method was validated for linearity, accuracy, precision and specificity. The method was applied to study the interaction between amlodipine and H1-receptor antagonists. These interactions were carried out in simulated gastric juice (pH 1), simulated full stomach (pH 4), blood pH (pH 7.4) and simulating GI (pH 9). The interacting drugs were heated at 37℃ with intermit-tent shaking and the samples were withdrawn every thirty minutes for three hours and drug contents were analyzed by RP-HPLC techniques. In most cases the in vitro availability of amlodipine was decreased. It was observed that the change in in vitro availability was pH dependent.

A Study of Decadal December Temperature Variability in Pakistan

The spatial distribution of December temperature in Pakistan has been assessed by statistical method based on mean monthly data from 51 ground stations. The analysis is performed at decadal scale over the period of 1950-2000. December is one of the representative months of winter season in Pakistan, the country with subtropical location and complex rugged terrains, plateaus and plains. The results support a slight rising temperature trend in December. However, this change in temperature varies from region to region as well as from decade to decade and reflects a complicated spatial-temporal structure of temperature anomalies. The assessment shows that the temperature anomalies in different national territories at local scale do not follow the assumption that winter months are warming in northern hemisphere. Both the isothermal shift and temperature anomalies confirm that the mountainous areas of Pakistan face more temperature variability than plains.

Microvesicles in Gliomas and Medulloblastomas: An Overview

Microvesicles (MVs) or shedding membrane vesicles have recently been described as a novel model of intercellular communication. Previously, MVs were considered as unnecessary or secreted cellular debris, but MVs have lately been described as having roles in a variety of biological functions, such as cell homeostasis and the cellular processes involved in the oncogenesis of many types of tumors. Carrying several key molecules that contribute to tumor development and progression, similar to mRNAs, microRNAs and other non-coding RNAs, DNA and even small proteins, MVs can be considered as a ubiquitous form of novel cell communication that is present in most somatic cells. Although tumor-derived MVs have been demonstrated in different types of cancers, the literature data on MVs in primary central nervous system (CNS) tumors are relatively scarce. In this review, we address the involvement of MVs in diffuse astrocytomas, particularly glioblastomas, as well as oligodendrogliomas and medulloblastomas. We placed particular focus on the cellular crosstalk between tumor and “normal” cells, the putative mechanisms how the tumor microenvironment is modulated and the spread of aggressive phenotypes. Additionally, a better understanding of the participation of tumor-derived MVs in the regulation of key cancer pathways will offer new insights into tumor pathogenesis and the mechanisms of multidrug resistance, and may help to develop new strategies for novel therapies against these infiltrative CNS tumors.

Investigating Factors of Slope Failure for Different Landsliding Sites in Murree Area, Using Geomatics Techniques

Throughout the mountainous part of Pakistan, Murree is considered to host the worst slide affected areas. Landslide risk assessment, mapping and analysis is a labour intensive and time consuming work by using conventional field based methods. In this study Geomatics techniques have been applied on digital data such as satellite image and DEM, to investigate some possible causes of slope failure in selected landslide risk zones. The Remote sensing technology and GIS capabilities have been implemented using Landsat TM (30 m) multispectral data and Aster DEM (30 m). Satellite image and digital elevation model have been used to generate rock type map, aspect map, streams order map and slope map. The possible factors of slope failure for different zones of land sliding have been predicted by integrating information from all maps. It has been found that major causes of slope failure have been addressed, also it has been noted that water is the most dominant factor to cause land sliding in Murree area. Results are available for supporting hazard studies, disaster management and future development plans.

Regional Characteristics of Temperature Anomalies in Pakistan with Emphasis on Spatial Distribution at Decadal Scale: A Case Study of August (1950s-2000s)

In this paper the month of August was assessed from 1950s-2000s based on the temperature data from 53 stations that covers almost all Pakistan. The temperature coefficient has been calculated by making use of linear regression. The results have been mapped that show considerable variability of temperature at decadal scale in different areas of Pakistan. The rugged terrains especially and rest of Pakistan generally reflect significant temperature variability in the decades of 1950s, 1960s, 1970s, 1980s, 1990s and 2000s as well. This change in temperature varies from region to region and decade to decade in Pakistan. The temperature anomalies achieved in the country are complicated at local level and did not follow the simple perception that winter months are warming and summer months are cooling. In this study, a geographical approach has been adopted to explain the spatial-temporal dynamics of temperature variation over the study period in Pakistan with emphasis on regional detail.

An indicator model for assessing community resilience to the COVID-19 pandemic and its validation: A case study in Hong Kong

The COVID-19 outbreak had a significant negative impact on the world,and the fifth wave of COVID-19 in Hong Kong brought a considerable shock to Chinese society.There is a growing call for more resilient cities.However,empirical evidence and validation of modeling studies of resilience indicators for urban community responses to the COVID-19 pandemic still need to be provided.In this study,a resilience assessment indicator model comprising 4 subsystems,7 indicators,and 12 variables was developed to assess the resilience of Hong Kong communities in response to COVID-19(i.e.,Resilience Index).Furthermore,this study utilized regression models such as geographically weighted regression(GWR)and multiscale GWR(MGWR)to validate the resilience model proposed in this study at the model and variable levels.In the regression model,the Resilience Index and the individual variables in the resilience model are explanatory variables,and the outcomes of the COVID-19 pandemic(confirmed cases,confirmation rate,discharged cases,discharge rate)are dependent variables.The results showed that:(i)the resilience of Hong Kong communities to the COvID-19 pandemic was not strong in general and showed some clustered spatial distribution characteristics;(i)the validation results at the model level showed that the Resilience Index did not explain the consequences of the COvID-19 pandemic to a high degree;(ii)the validation results at the variable level showed that the MGWR model was the best at identifying the relationships between explanatory variables and the dependent variable;and(iv)compared with the model-level assessment results,the variable-level assessment explained the consequences of the COvID-19 pandemic better than the model level assessment results.The above analysis and the spatial distribution maps of the resilience variables can provide empirically based and targeted insights for policymakers.

盐岩渗透特性的试验研究及其在深部储气库中的应用

为给深部盐岩地层（≥1500m）中所建天然气储库的稳定性和密闭性评价提供科学指导,针对取自江苏金坛的不同杂质含量盐岩试样,在荷兰乌德勒支大学HPT实验室开展了在三轴压缩条件下的瞬态法渗透率测试研究,揭示盐岩的变形特征与渗透率演化规律。试验研究表明：在围压20 MPa的常温测试条件下,随着偏应力从0~40MPa递增,损伤后的低含泥盐岩的渗透率从10-16m2逐渐下降至10-21m2以下,而损伤后的高含泥盐岩的渗透率则平均高出前者1~2个量级,推测表明损伤后的盐岩在加载下裂纹闭合、孔隙减小、逐渐压缩密实,进而渗透率快速降低,同时也表明外载压密作用对纯盐岩的裂纹压缩闭合、甚至损伤修复作用更显著。根据试验成果,并利用H.Alkan等[11]建立的盐岩压缩–扩容边界线对位于1500~2000 m深部的盐岩地层中的球形腔体的围岩应力状态分析显示,围岩几乎都位于扩容边界以下的安全区域,由此推知：即使在储气库低压运行条件下,围岩中较难发生扩容而导致密闭性失效事件发生,腔体的密闭性能极好。该研究为深部盐穴储气库的可行性和密闭性评价提供有利支撑。

Preparation of cerium and yttrium doped ZnO nanoparticles and tracking their structural,optical,and photocatalytic performances

Yttrium(Y)and cerium(Ce)co-doped ZnO nanoparticles(NPs)were synthesized via the simple sol-gel auto-combustion route.The effect of Ce and Y doping on the structure,morphology,optical,Zeta potential,and photocatalytic activities of ZnO NPs was examined by Fourier transform infrared(FTIR)spectrometer,X-ray diffraction(XRD),transmission electron microscope(TEM),UV-vis spectrophotometer,and Zetasizer instrument.XRD data show that the fabricated samples crystallize into a hexagonal wurtzite structure.The dopants Y and Ce affect the crystal structure of ZnO NPs.The crystallite size is reduced with the co-doping effect.TEM results confirm the nano-sized particles of the prepared samples.An increase in optical bandgap values from 3.19 eV for x=0.0 to 3.22,3.24,and 3.25 eV for x=0.01,0.03,and 0.05 samples was confirmed by UV-Vis spectroscopy analysis.Y and Ce co-doped ZnO nanoparticles show significant alteration of zeta potential and photocatalytic properties compared to undoped ZnO NPs.Comparatively,undoped ZnO shows better stability in deionized water as compared to Ce-Y doped ZnO NPs and exhibits high photocatalytic activity(degradation rate,97.92%)for methyl orange(MO)degradation.

Influence of absorber doping in a-SiC:H/a-Si:H/a-SiGe:H solar cells

This work deals with the design evaluation and influence of absorber doping for aSi：H/aSiC：H/a SiGe：H based thinfilm solar cells using a twodimensional computer aided design （TCAD） tool. Various physical parameters of the layered structure, such as doping and thickness of the absorber layer, have been studied. For reliable device simulation with realistic predictability, the device performance is evaluated by implementing nec essary models （e.g., surface recombinations, thermionic field emission tunneling model for carrier transport at the heterojunction, SchokleyRead Hall recombination model, Auger recombination model, bandgap narrowing ef fects, doping and temperature dependent mobility model and using FermiDirac statistics）. A single absorber with a graded design gives an efficiency of 10.1% for 800 nm thick multiband absorption. Similarly, a tandem design shows an efficiency of 10.4% with a total absorber of thickness of 800 nm at a bandgap of 1.75 eV and 1.0 eV for the top aSi and bottom aSiGe component cells. A moderate ndoping in the absorber helps to improve the efficiency while p doping in the absorber degrades efficiency due to a decrease in the Voc （and fill factor） of the device.

Enhanced catalytic complete oxidation of 1,2-dichloroethane over mesoporous transition metal-doped γ-Al_2O_3

High-surface-area mesoprous powders of γ-Al2O3 doped with Cu^2＋, Cr^3＋, and V^3＋ ions were prepared uia a modified sol-gel method and were investigated as catalysts for the oxidation of chlorinated organic compounds. The composites retained high surface areas and pore volumes comparable with those of undoped γ-Al2O3 and the presence of the transition metal ions enhanced their surface acidic properties. The catalytic activity of the prepared catalysts in the oxidation of 1,2-dichloroethane （DCE） was studied in the temperature range of 250-400℃. The catalytic activity and product selectivity were strongly dependent on the presence and the type of dopant ion. While Cu^2＋- and Cr^3＋-containing catalysts showed 100% conversion at 300℃ and 350℃, V3＋-containing catalyst showed considerably lower conversion. Furthermore, while the major products of the reactions over γ-alumina were vinyl chloride （C2H3Cl） and hydrogen chloride （HCl） at all temperatures, Cu- and Cr-doped catalysts showed siguiticantly stronger capability for deep oxidation to CO2.