Thermodynamic and experimental evaluation of a cloud chamber for ultrafine particle detection

Particle sensing based on condensational growth has long been the basis for robust nanoparticle measurement. Increasingly cloud chamber devices offer the potential for low-cost and portable measurement when operated semi-continuously with relatively small system volumes. Models based on isentropic and isenthalpic expansion are derived to predict the time evolution of temperature, saturation ratio, particle growth, and resultant light extinction in cloud chambers. A laboratory cloud chamber is fabricated and experiments using NaCl aerosol particles as the condensation nucleus are conducted to verify the models. The isentropic model, suggests that the temperature drops 0.6 ℃ within 40 ms, and accordingly, the saturation ratio reaches 1.04. For an aerosol with lognormal distribution, the predicted geometric mean diameter grows more than 5 times while the distribution narrows due to ∝1/p growth in the continuum regime. The performance of the cloud chamber agrees with the system physics and reference instruments, with relative error in measured extinction coefficient and signal intensities of ±5%. Detailed error propagation shows that the measured number concentrations agree well with reference instruments and the underlying theory. The lower limit of detection (~4×10^6 cm^-3) for the device is suitable for fire detection and emissions characterization

Using Context-Based Password Strength Meter to Nudge Users' Password Generating Behavior: A Randomized Experiment

Encouraging users to create stronger passwords is one of the key issues in password-based authentication. It is particularly important as prior works have highlighted that most passwords are weak. Yet, passwords are still the most commonly used authentication method. This paper seeks to mitigate the issue of weak passwords by proposing a context-based password strength meter. We conduct a randomized experiment on Amazon MTurk and observe the change in users’ behavior. The results show that our proposed method is significantly effective. Users exposed to our password strength meter are more likely to change their passwords after seeing the warning message, and those new passwords are stronger. Furthermore, users are willing to invest their time to learn about creating a stronger password, even in a traditional password strength meter setting. Our findings suggest that simply incorporating contextual information to password strength meters could be an effective method in promoting more secure behaviors among end users

Centrifuge Modelling of the Collapse of Shaft Linings

The collapse of abandoned and often hidden mine shafts is a serious problem in the UK and many parts of Europe. The collapse of these shafts is often related to the failure of the shaft lining. Understanding the mechanisms of ground movements around deforming/collapsing mine shafts is, therefore, important in the assessment of mine shaft location as well as lining condition. This paper presents an experimental study of the mechanisms of soil failure around a deforming shaft lining. Geotechnical centrifuge modelling of reduced-scale buried mine shafts was tested to determine the magnitude and pattern of ground deformations that occurred during loss of internal support pressure. An axis-symmetric centrifuge container was used along with half-cylindrical model shafts. These allowed for the acquisition of digital images of the sub-surface soil and mine shafts which enabled the measurement of soil and shaft deformation using image analysis techniques. The results from two model shaft tests are presented. The first test involved the loss of internal support along the entire shaft length, whereas the second test studied the effect of a discrete weakened zone within the lining

An Experimental Evaluation of the Weathering Effects on Mine Shaft Lining Materials

Many shaft collapses are related to the deterioration and failure of the masonry shaft lining materials. In modern mine shaft, concrete is widely used to provide support. To analyse shafts stability, the properties of the lining need to be well defined. The behaviour of masonry and concrete can be considerably affected by long-term exposure to harsh mine water. This paper presents a study which focuses on the weathering effects of mine water on lining materials (brick, mortar, and concrete). To reproduce the weathering process, samples were placed into solutions of potable water, artificial mine water, and a more aggressive mine-water solution for just less than one year. Four phases of laboratory tests were conducted throughout the time period to assess the degradation of mechanical properties of the lining materials. Particular attention is given to the degradation of material strength and stiffness. Results indicate that the harsh acidic mine water has pronounced detrimental effects on the strength and stiffness of mortar. The weathering process is shown to have the most significant effect on the stiffness of concrete and mortar. It is also shown that the use of mass loss as an index for evaluation of mechanical properties may not be appropriate

Using Context-Based Password Strength Meter to Nudge Users\u27 Password Generating Behavior: A Randomized Experiment

Encouraging users to create stronger passwords is one of the key issues in password-based authentication. It is particularly important as prior works have highlighted that most passwords are weak. Yet, passwords are still the most commonly used authentication method. This paper seeks to mitigate the issue of weak passwords by proposing a context-based password strength meter. We conduct a randomized experiment on Amazon MTurk and observe the change in users’ behavior. The results show that our proposed method is significantly effective. Users exposed to our password strength meter are more likely to change their passwords after seeing the warning message, and those new passwords are stronger. Furthermore, users are willing to invest their time to learn about creating a stronger password, even in a traditional password strength meter setting. Our findings suggest that simply incorporating contextual information to password strength meters could be an effective method in promoting more secure behaviors among end users

The Meaning of Memory Safety

We give a rigorous characterization of what it means for a programming language to be memory safe, capturing the intuition that memory safety supports local reasoning about state. We formalize this principle in two ways. First, we show how a small memory-safe language validates a noninterference property: a program can neither affect nor be affected by unreachable parts of the state. Second, we extend separation logic, a proof system for heap-manipulating programs, with a memory-safe variant of its frame rule. The new rule is stronger because it applies even when parts of the program are buggy or malicious, but also weaker because it demands a stricter form of separation between parts of the program state. We also consider a number of pragmatically motivated variations on memory safety and the reasoning principles they support. As an application of our characterization, we evaluate the security of a previously proposed dynamic monitor for memory safety of heap-allocated data.Comment: POST'18 final versio

Stereo Computation for a Single Mixture Image

This paper proposes an original problem of \emph{stereo computation from a single mixture image}-- a challenging problem that had not been researched before. The goal is to separate (\ie, unmix) a single mixture image into two constitute image layers, such that the two layers form a left-right stereo image pair, from which a valid disparity map can be recovered. This is a severely illposed problem, from one input image one effectively aims to recover three (\ie, left image, right image and a disparity map). In this work we give a novel deep-learning based solution, by jointly solving the two subtasks of image layer separation as well as stereo matching. Training our deep net is a simple task, as it does not need to have disparity maps. Extensive experiments demonstrate the efficacy of our method.Comment: Accepted by European Conference on Computer Vision (ECCV) 201

Hepatic fibrogenesis requires sympathetic neurotransmitters

Background and aims: Hepatic stellate cells (HSC) are activated by liver injury to become proliferative fibrogenic myofibroblasts. This process may be regulated by the sympathetic nervous system (SNS) but the mechanisms involved are unclear. Methods: We studied cultured HSC and intact mice with liver injury to test the hypothesis that HSC respond to and produce SNS neurotransmitters to promote fibrogenesis. Results: HSC expressed adrenoceptors, catecholamine biosynthetic enzymes, released norepinephrine (NE), and were growth inhibited by α- and β-adrenoceptor antagonists. HSC from dopamine β-hydroxylase deficient (Dbh(−/−)) mice, which cannot make NE, grew poorly in culture and were rescued by NE. Inhibitor studies demonstrated that this effect was mediated via G protein coupled adrenoceptors, mitogen activated kinases, and phosphatidylinositol 3-kinase. Injury related fibrogenic responses were inhibited in Dbh(−/−) mice, as evidenced by reduced hepatic accumulation of α-smooth muscle actin(+ve) HSC and decreased induction of transforming growth factor β1 (TGF-β1) and collagen. Treatment with isoprenaline rescued HSC activation. HSC were also reduced in leptin deficient ob/ob mice which have reduced NE levels and are resistant to hepatic fibrosis. Treating ob/ob mice with NE induced HSC proliferation, upregulated hepatic TGF-β1 and collagen, and increased liver fibrosis. Conclusions: HSC are hepatic neuroglia that produce and respond to SNS neurotransmitters to promote hepatic fibrosis

Th gme 10: A numerical model to capture the geotechnical response to coal combustion at an underground coal gasification site

A detailed numerical modelling study was carried out to represent geotechnical aspects of the Wieczorek underground coal gasification (UCG) site in Poland. A coupled thermos-mechanical numerical model was created to represent a single coal burning panel. The coal burning proceb was simulated by modifying the energy balance equation with an additional term related to the calorific value of coal as a source. Temperature dependent material properties were abigned to the coupled thermal-mechanical model according to published data. In the model, the burning zone spread about 7.5m laterally after 20 days of burning. Results from the coupled model were used to gauge a worst-case scenario in terms of the potential size of a formed cavity. This data was used within a leb computationally expensive mechanicalonly numerical model in order to evaluate the ground subsidence caused by the worst-case scenario for single and multiple UCG burning panels. The single panel burning resulted in 23mm of ground subsidence at the top of the model after long term coal burning. The ground subsidence measured at the top of the model, at the center point of the gasification arrangement, was approximately 72mm when five panels were burnt with an edge to edge panel distance of 5m; this was increased to 85mm for seven panels. The numerical modelling results have implications to the industrial application of UCG