Wet and Dry Anaerobic Digestion of Biowaste and of Co-substrates

Treatment of municipal solid waste by anaerobic digestion can solve the environmental problems caused by this organic solid waste and also supply biogas as renewable energy for a sustainable development. In this study the improvement of wet anaerobic digestion by addition of co-substrates and the effect of moisture on dry anaerobic digestion were investigated

MicroRNA and Epigenetic Controls of CD4+ T cells' Activation, Differentiation and Maintenance

<p>As a major component of the adaptive immune system, CD4+ T cells play a vital role in host defense and immune tolerance. The potency and accuracy of CD4+ T cell-mediated protection lie in their ability to differentiate into distinct subsets that could carry out unique duties. In this dissertation, we dissected the roles and interplays between two emerging mechanisms, miRNAs and epigenetic processes, in regulating CD4+ T cell-mediated responses. Using both gain- and loss-of-function genetic tools, we demonstrated that a miRNA cluster, miR-17-92, is critical to promote Th1 responses and suppress inducible Treg differentiation. Mechanistically, we found that through targeting Pten, miR-17-92 promotes PI3K activation. Strong TCR-PI3K activation leads to the accumulation of DNMT1, elevated CpG methylation in the foxp3 promoter, and suppression of foxp3 transcription. Furthermore, we demonstrated that an epigenetic regulator, methyl CpG binding protein 2 (MeCP2), is critical to sustain Foxp3 expression in Tregs, and to support Th1 and Th17 differentiation in conventional CD4+ T cells (Tcons). In Tregs, MeCP2 directly binds to the CNS2 region of foxp3 locus to promote its local histone H3 acetylation; while in Tcons, MeCP2 enhances the locus accessibility and transcription of miR-124, which negatively controls SOCS5 translation to support STAT1, STAT3 activation and Th1, Th17 differentiation. Overall, miRNAs and epigenetic processes may crosstalk to control CD4+ T cell differentiation and function.</p>Dissertatio

Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection

Machine learning based solutions have been successfully employed for automatic detection of malware in Android applications. However, machine learning models are known to lack robustness against inputs crafted by an adversary. So far, the adversarial examples can only deceive Android malware detectors that rely on syntactic features, and the perturbations can only be implemented by simply modifying Android manifest. While recent Android malware detectors rely more on semantic features from Dalvik bytecode rather than manifest, existing attacking/defending methods are no longer effective. In this paper, we introduce a new highly-effective attack that generates adversarial examples of Android malware and evades being detected by the current models. To this end, we propose a method of applying optimal perturbations onto Android APK using a substitute model. Based on the transferability concept, the perturbations that successfully deceive the substitute model are likely to deceive the original models as well. We develop an automated tool to generate the adversarial examples without human intervention to apply the attacks. In contrast to existing works, the adversarial examples crafted by our method can also deceive recent machine learning based detectors that rely on semantic features such as control-flow-graph. The perturbations can also be implemented directly onto APK's Dalvik bytecode rather than Android manifest to evade from recent detectors. We evaluated the proposed manipulation methods for adversarial examples by using the same datasets that Drebin and MaMadroid (5879 malware samples) used. Our results show that, the malware detection rates decreased from 96% to 1% in MaMaDroid, and from 97% to 1% in Drebin, with just a small distortion generated by our adversarial examples manipulation method.Comment: 15 pages, 11 figure

Photodegradation of free estrogens driven by the UV light: Effects of operation mode and water matrix

Estrogens are endocrine disrupting chemicals that have been frequently detected in diverse water matrices (e.g. surface water, wastewater and drinking water) and caused a series of health risks. This study was aimed at investigating the photochemical degradation of free estrogens estrone (E1), 17β-estradiol (E2), estriol (E3), and 17α-ethyl estradiol (EE2) upon the monochromatic irradiation (253.7 nm). Concerning the practical installation of photolysis treatment, exposing the impacts of photoreactor operation mode (stationary or up-flow) and the water matrix (ultrapure water or natural surface water) on the photolytic behaviour of estrogens was of high importance. The pseudo-first-order rate constants showed that E1 was the most susceptible to UV radiation among chosen estrogens due to its high molar absorption coefficient of 402.4 M^{−1] cm^{−1} and quantum yield of 0.065 mol E^{−1} at λ = 253.7 nm. Moreover, the up-flow mode and the surface water matrix collected from a lake in Regent's Park (London) were found to favour the photodegradation of estrogens due to the introduction of more dissolved oxygens and promotion of reactive oxygen species (ROS) formation. These findings may shed light on the photochemical behaviour of estrogens in some specific scenarios

Improvement of Printing Quality for Laser-induced Forward Transfer based Laser-Assisted Bioprinting Process using a CFD-based numerical model

As one of the three-dimensional (3D) bioprinting techniques with great application potential, laser-induced-forward-transfer (LIFT) based laser assisted bioprinting (LAB) transfers the bioink through a developed jet flow, and the printing quality highly depends on the stability of jet flow regime. To understand the connection between the jet flow and printing outcomes, a Computational Fluid Dynamic (CFD) model was developed for the first time to accurately describe the jet flow regime and provide a guidance for optimal printing process planning. By adopting the printing parameters recommended by the CFD model, the printing quality was greatly improved by forming stable jet regime and organized printing patterns on the substrate, and the size of printed droplet can also be accurately predicted through a static equilibrium model. The ultimate goal of this research is to direct the LIFT-based LAB process and eventually improve the quality of bioprinting

An Empathy-Based Sandbox Approach to Bridge Attitudes, Goals, Knowledge, and Behaviors in the Privacy Paradox

The "privacy paradox" describes the discrepancy between users' privacy attitudes and their actual behaviors. Mitigating this discrepancy requires solutions that account for both system opaqueness and users' hesitations in testing different privacy settings due to fears of unintended data exposure. We introduce an empathy-based approach that allows users to experience how privacy behaviors may alter system outcomes in a risk-free sandbox environment from the perspective of artificially generated personas. To generate realistic personas, we introduce a novel pipeline that augments the outputs of large language models using few-shot learning, contextualization, and chain of thoughts. Our empirical studies demonstrated the adequate quality of generated personas and highlighted the changes in privacy-related applications (e.g., online advertising) caused by different personas. Furthermore, users demonstrated cognitive and emotional empathy towards the personas when interacting with our sandbox. We offered design implications for downstream applications in improving user privacy literacy and promoting behavior changes

A State-of-the-Art Review of Laser-Assisted Bioprinting and its Future Research Trends

Bioprinting is an additive manufacturing technology with great potential in medical applications. Among available bioprinting techniques, laser-assisted bioprinting (LAB) is a promising technique due to its high resolution, high cell viability, and the capability to deposit high-viscousity bioink. These characteristics allow the LAB technology to control cells precisely to reconstruct living organs. Recent developments of LAB technologies are reviewed in this paper, covering various designs of LAB printers, research progresses in energy-absorbing layer (EAL), the physical phenomenon that triggers the printing process in terms of bubble formation and jet development, printing process parameters, and major factors related to the post-printing cell viability. The latest studies on LAB technologies are highlighted, expounding their advantages and disadvantages, and some potential applications are presented. The potential technical challenges and future research trends for LAB technologies are also discussed