Photoacoustic computed tomography guided microrobots for targeted navigation in intestines in vivo

Tremendous progress in synthetic micro/nanomotors has been made for potential biomedical applications. However, existing micro/nanomotor platforms are inefficient for deep tissue imaging and motion control in vivo. Here, we present a photoacoustic computed tomography (PACT) guided investigation of micromotors in intestines in vivo. The micromotors enveloped in microcapsules exhibit efficient propulsion in various biofluids once released. PACT has visualized the migration of micromotor capsules toward the targeted regions in real time in vivo. The integration of the developed microrobotic system and PACT enables deep imaging and precise control of the micromotors in vivo

A novel Automatic Reflective Indexing (ARI) method to create a world peace index

The negative peace and positive peace are the core concepts of the peace research. The Global Peace Index (GPI) and Positive Peace Index (PPI) try to measure the levels of negative and positive peace respectively and support the relevant empirical researches. However, the influences of GPI and PPI are very limited in empirical peace research. The literatures ascribed the unpopularity of the GPI to its low credibility caused by its embedded “inappropriate subjectiveness”, which is an ambiguous statement since no concrete limitations of GPI and PPI were revealed. The aim of this research is to identify the concrete limitations of the GPI and PPI methods which reduce their credibility, and then develop a new peace indexing method to solve these limitations. We dig into the methods of GPI and PPI and conclude four concrete limitations in terms of the target aggregation, the indicator validation, the indicator weighting (PPI), and the missing value estimation which can reduce the credibility of GPI and PPI. Then, we design a new peace indexing method called the automatic reflective indexing (ARI) and demonstrate its theoretically advantages by solving the concrete limitations of the methods of GPI and PPI. To evaluate the practical performance of the ARI, we use the ARI to establish specific peace indexes, the Internal Peace Index (IPI) and the External Negative Peace Index (ENPI), and then demonstrate that these indexes indeed no longer suffer from the limitations of GPI and PPI. We also illustrate that the ARI can be useful to study the causes of peace due to its SEM-based characteristics. At the end of this thesis, we summarise the contributions and limitations of the ARI and give an outlook on the future works after this research

Quantifying structural connectivity in brain tumor patients

Brain tumors are characterised by infiltration along the white matter tracts, posing significant challenges to precise treatment. Mounting evidence shows that an infiltrative tumor can interfere with the brain network diffusely. Therefore, quantifying structural connectivity has potential to identify tumor invasion and stratify patients more accurately. The tract-based statistics (TBSS) is widely used to measure the white matter integrity. This voxel-wise method, however, cannot directly quantify the connectivity of brain regions. Tractography is a fiber tracking approach, which has been widely used to quantify brain connectivity. However, the performance of tractography on the brain with tumors is biased by the tumor mass effect. A robust method of quantifying the structural connectivity in brain tumor patients is still lacking. Here we propose a method which could provide robust estimation of tract strength for brain tumor patients. Specifically, we firstly construct an unbiased tract template in healthy subjects using tractography. The voxel projection procedure of TBSS is employed to quantify the tract connectivity in patients, based on the location of each tract fiber from the template. To further improve the standard TBSS, we propose an approach of iterative projection of tract voxels, under the guidance of tract orientation measured by voxel-wise eigenvectors. Compared to the conventional tractography methods, our approach is more sensitive in reflecting functional relevance. Further, the different extent of network disruption revealed by our approach correspond to the clinical prior knowledge of tumor histology. The proposed method could provide a robust estimation of the structural connectivity for brain tumor patients

Securing Cyber-Physical Social Interactions on Wrist-worn Devices

Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this article, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel key generation system, which harvests motion data during user handshaking from the wrist-worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn’t involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed key generation system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to different types of attacks including impersonate mimicking attacks, impersonate passive attacks, or eavesdropping attacks. Specifically, for real-time impersonate mimicking attacks, in our experiments, the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed key generation system can be extremely lightweight and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption