Label-free analysis of protein biomarkers using pattern-optimized graphene-nanopyramid SERS for rapid diagnosis of Alzheimer’s disease

The quantitative and highly sensitive detection of biomarkers such as Tau proteins and Aβ polypeptides is considered one of the most effective methods for the early diagnosis of Alzheimer’s disease (AD). Surface-enhanced Raman spectroscopy (SERS) detection is a promising method that faces, however, challenges like insufficient sensitivity due to the non-optimized nanostructures for specialized analyte sizes and insufficient control of the location of SERS hot spots. Thus, the SERS detection of AD biomarkers is restricted. We reported here an in-depth study of the analytical Raman enhancement factor (EF) of the wafer-scale graphene-Au nanopyramid hybrid SERS substrates using a combination of both theoretical calculation and experimental measurements. Experimental results show that larger nanopyramids and smaller gap spacing lead to a larger SERS EF, with an optimized analytical EF up to 1.1 × 1010. The hybrid SERS substrate exhibited detection limits of 10–15 M for Tau and phospho-Tau (P-Tau) proteins and 10–14 M for Aβ polypeptides, respectively. Principal component analysis correctly categorized the SERS spectra of different biomarkers at ultralow concentrations (10–13 M) using the optimized substrate. Amide III bands at 1200–1300 cm–1 reflect different structural conformations of proteins or polypeptides. Tau and P-Tau proteins are inherently disordered with a few α-helix residuals. The structure of Aβ42 polypeptides transitioned from the α-helix to the β-sheet as the concentration increased. These results demonstrate that the hybrid SERS method could be a simple and effective way for the label-free detection of protein biomarkers to enable the rapid early diagnosis of AD and other diseases

Vulnerability assessment of ports and industrial clusters against catastrophes

Catastrophes, with the features of high negative impact and low frequency, are causing increasing losses to the human society due to the increasing exposure and vulnerability. Seaports are critical lifeline infrastructures in coastal cities and are at the same time vulnerable to both natural and man-made catastrophes, such as typhoon, earthquake, fire, and explosion. Any disruptions to a seaport will have a direct impact on the supply chain where the port lies and have a second order or even a third order propagation to the industrial clusters in the hinterland. A literature review reveals a research gap on port multi-dimensional vulnerability assessment against catastrophes, which includes assessments of physical, functional, institutional, economic and interdependency aspects of port vulnerability. Therefore, to fill the gap, this study firstly identifies the major port catastrophic hazards by literature review. Based on the framework, port vulnerability is assessed against non-repetitive catastrophes by utilizing the method of vulnerability index which integrates the fuzzy evidential reasoning (ER) and the fuzzy technique for order preference by similarity ideal solution (TOPSIS). By using Tianjin Port Explosion in 2015 as the case study, vulnerability estimates of the four port sub-systems as well as the whole port system in two assessment periods are obtained. It is found that the storage system is the most vulnerable subsystem after the explosion, while the vulnerability condition of the loading and unloading system improves the most after the first round of port recovery. Further, port vulnerability assessment against repetitive catastrophes is conducted by using the developed port operation simulation-based model. The relationship between catastrophe magnitude and port loss is revealed by quantifying decreased port throughput and physical damages. The typhoon hazard and the Port of Shenzhen, China is selected as the case study. It is estimated that a worst-case scenario typhoon attack could cause a total loss of 0.91 USD billion in the studied terminal, which is approximately three times the terminal net profit in 2015. Finally, the research takes a further step in considering the hinterland industrial clusters into the research scope. VIII Propagation of port vulnerability to hinterland industrial clusters is evaluated by an original three-layer port-cargo-industrial cluster model. The key seaports and industrial clusters in Guangdong province, China as well as the typhoon hazard are used as examples. It is identified that the most vulnerable industrial cluster of Guangdong is the petrochemical industrial cluster when facing typhoon-induced port disruptions in the import mode, while the textile and apparel industrial cluster is the most vulnerable one in the export mode. Consequently, the port and industrial clusters vulnerability estimates obtained from this study could be used by decision makers in identifying and prioritizing critical port protection targets, ship route planning, and risk mitigation strategy formulating.Doctor of Philosoph

Simulation-based severe weather-induced container terminal economic loss estimation

Container terminals play a critical role in maritime supply chains. However, they show vulnerabilities to severe weather events due to the sea–land interface locations. Previous severe weather risk analysis focused more on larger assessment units, such as regions and cities. Limited studies assessed severe weather risks on a smaller scale of seaports. This paper aims to propose a severe weather-induced container terminal loss estimation framework. Based on a container terminal operation simulation model, monthly average loss and single event-induced loss are obtained by using historical hazard records and terminal operation records as model inputs. By studying the Port of Shenzhen as the case study, we find that the fog events in March lead to the longest monthly port downtime and the highest monthly severe weather-induced economic losses in the studied port. The monthly average loss is estimated to be 30 million USD, accounting for 20% of the intact income. The worst-case scenario is found to be a red-signal typhoon attack which results in nearly 20% decrease in the month’s income. The results provide useful references for various container terminal stakeholders in severe weather risk management.Accepted versio

Simulation-based catastrophe-induced port loss estimation

Seaports are critical infrastructure systems in the international economy. They are at the same time vulnerable to various types of natural and man-made catastrophes due to their special coastal and low-lying locations. Traditional catastrophe risk analyses focused more on regions, port cities, and port communities. Limited studies assessed catastrophe risks on ports as a specific system. This paper aims to develop a catastrophe-induced port loss estimation framework, based on a port operation simulation model, actual terminal records and historical hazard records. By using the typhoon hazard and the Port of Shenzhen as a case study, we find that (1) the worst-case scenario of a typhoon impact could cause a total loss of US$0.91 billion for a terminal with 16 berths; and (2) the annual predicted typhoon-induced loss for the same terminal for the next 5 years will reach approximately US$64 million, accounting for 19.7% of the terminal net profit in 2015. The results provide useful references for various port stakeholders in catastrophe risk assessment and mitigation.Accepted versio

Catastrophe risk assessment framework of ports and industrial clusters : a case study of the Guangdong province

Seaports, as critical infrastructures, are vulnerable to natural catastrophes such as hurricane/typhoon, earthquake, and tsunami. The inoperability of a port caused by these hazards tends to activate domino effects to the adjacent industrial clusters in the hinterland. Limited works addressed high-impact and low-probability (HILP) catastrophe risks and fewer studied industrial cluster risks resulting from catastrophe-induced port disruptions. This paper aims to assess ports and industrial clusters catastrophe risks, based on a three-layer port-cargo-industrial cluster (PCI) model. By using the Guangdong province in China and the typhoon hazard as a case study, we find that the petrochemical industrial cluster is the most vulnerable in the Guangdong province against typhoon-induced port disruptions in the import mode, while the textile and apparel industrial cluster is the least vulnerable. These two industrial clusters exchange rankings under the export mode. Proactive preparations can thus be made to avoid any possible prolonged production downtimes.Nanyang Technological UniversityWe wish to thank the anonymous reviewers for their valuable comments and suggestions. We also wish to thank the Institute of Catastrophe Risk Management at Nanyang Technological University for providing research scholarship to the first author as a PhD student

Offshore Platform for Containerized Cargo Redistribution: A New Concept and Simulation-based Performance Study

10.1080/03088839.2020.1783464Maritime Policy & Management4871032-105

A Data-driven Business Intelligence System for Large-scale Semi-Automated Logistics Facilities

10.1080/00207543.2020.1727048International Journal of Production Research59082250-226

Three Carriages Driving the Development of Intelligent Digital Twins – Simulation Plus Optimization and Learning

Winter Simulation Conferenc

Classification and literature review on the integration of simulation and optimization in maritime logistics studies

10.1080/24725854.2020.1856981IISE Transactions53101157-117

A Voxel-Based Morphometric MRI Study in Young Adults with Borderline Personality Disorder.

BACKGROUND:Increasing evidence has documented subtle changes in brain morphology and function in patients with borderline personality disorder (BPD). However, results of magnetic resonance imaging volumetry in patients with BPD are inconsistent. In addition, few researchers using voxel-based morphometry (VBM) have focused on attachment and childhood trauma in BPD. This preliminary study was performed to investigate structural brain changes and their relationships to attachment and childhood trauma in a homogenous sample of young adults with BPD. METHOD:We examined 34 young adults with BPD and 34 healthy controls (HCs) to assess regionally specific differences in gray matter volume (GMV) and gray matter concentration (GMC). Multiple regressions between brain volumes measured by VBM and attachment style questionnaire (ASQ) and childhood trauma questionnaire (CTQ) scores were performed. RESULTS:Compared with HCs, subjects with BPD showed significant bilateral increases in GMV in the middle cingulate cortex (MCC)/posterior cingulate cortex (PCC)/precuneus. GMC did not differ significantly between groups. In multiple regression models, ASQ insecure attachment scores were correlated negatively with GMV in the precuneus/MCC and middle occipital gyrus in HCs, HCs with more severe insecure attachment showed smaller volumes in precuneus/MCC and middle occipital gyrus, whereas no negative correlations between insecure attachment and GMV in any region were found in BPD group. In addition, CTQ total scores were not correlated with GMV in any region in the two groups respectively. CONCLUSIONS:Our findings fit with those of previous reports of larger precuneus GMV in patients with BPD, and suggest that GMV in the precuneus/MCC and middle occipital gyrus is associated inversely with insecure attachment style in HCs. Our finding of increased GMV in the MCC and PCC in patients with BPD compared with HCs has not been reported in previous VBM studies