Security Verification of Low-Trust Architectures

Low-trust architectures work on, from the viewpoint of software, always-encrypted data, and significantly reduce the amount of hardware trust to a small software-free enclave component. In this paper, we perform a complete formal verification of a specific low-trust architecture, the Sequestered Encryption (SE) architecture, to show that the design is secure against direct data disclosures and digital side channels for all possible programs. We first define the security requirements of the ISA of SE low-trust architecture. Looking upwards, this ISA serves as an abstraction of the hardware for the software, and is used to show how any program comprising these instructions cannot leak information, including through digital side channels. Looking downwards this ISA is a specification for the hardware, and is used to define the proof obligations for any RTL implementation arising from the ISA-level security requirements. These cover both functional and digital side-channel leakage. Next, we show how these proof obligations can be successfully discharged using commercial formal verification tools. We demonstrate the efficacy of our RTL security verification technique for seven different correct and buggy implementations of the SE architecture.Comment: 19 pages with appendi

Green Purchasing Practices and Environmental Performance

Green purchasing aims to minimize negative environmental impacts in manufacturing process and transportation by using durable, recyclable and reusable materials. This study aims investigate the impact of green purchasing practices including green product, green process and green supplier on environmental and business performance in the context of Malaysian manufacturing companies. A total of 156 questionnaires were distributed to different industry sectors. The findings show that green product, green process and green supplier are significantly and positively related to environmental performance. In addition, green product is the main predictor of the environmental performance. Ultimately, the results could offer useful guidance for green purchasing practices implementation in Malaysian manufacturing companies and provide a springboard for further empirical research in the area

Dynamics of variable-viscosity nanofluid flow with heat transfer in a flexible vertical tube under peristaltic waves

The present investigation addresses nanofluid flow and heat transfer in a vertical tube with temperature-dependent viscosity. A Tiwari-Das type formulation is employed for the nanofluid with a viscosity modification. The transport equations are transformed from a cylindrical coordinate system with appropriate variables and simplified via longwave length and low Reynolds number approximations. The resulting boundary value problem is solved analytically. The influence of heat source/sink parameter (), Grashof number (Gr) and the viscosity parameter () and nanoparticle volume fraction () on velocity, temperature, pressure gradient, pressure rise and wall shear stress distributions is presented graphically. Three different nanofluid suspensions are investigated- Titanium oxide-water, Copper oxide-water and Silver-water. Streamline plots are also computed to illustrate bolus dynamics and trapping phenomena which characterize peristaltic propulsion. The computations show that wall shear stress is maximum for the Silver-water nanofluid case. Furthermore the pressure rise is reduced with increasing Grashof number, heat absorption parameter and viscosity parameter in the augmented pumping region whereas the contrary response is observed in the peristaltic pumping region. Significant modification in the quantity of trapped boluses is found with different nanofluids and the size of the trapped bolus is decreased in the Titanium oxide-water nanofluid case with either greater heat source or sink parameter. The study is relevant to drug delivery systems exploiting nano-particles

Architecture of Pol II(G) and molecular mechanism of transcription regulation by Gdown1.

Tight binding of Gdown1 represses RNA polymerase II (Pol II) function in a manner that is reversed by Mediator, but the structural basis of these processes is unclear. Although Gdown1 is intrinsically disordered, its Pol II interacting domains were localized and shown to occlude transcription factor IIF (TFIIF) and transcription factor IIB (TFIIB) binding by perfect positioning on their Pol II interaction sites. Robust binding of Gdown1 to Pol II is established by cooperative interactions of a strong Pol II binding region and two weaker binding modulatory regions, thus providing a mechanism both for tight Pol II binding and transcription inhibition and for its reversal. In support of a physiological function for Gdown1 in transcription repression, Gdown1 co-localizes with Pol II in transcriptionally silent nuclei of early Drosophila embryos but re-localizes to the cytoplasm during zygotic genome activation. Our study reveals a self-inactivation through Gdown1 binding as a unique mode of repression in Pol II function

Effectiveness of visible and ultraviolet light emitting diodes for inactivation of Staphylococcus aureus, Pseudomonas aeruginosa,and Escherichia coli: a comparative study

The rapid use of ultraviolet light emitting diodes (UV-LEDs) in various disinfection applications is growing tremendously due to their advantages unachievable using UV lamps. In this study, a comparison of standard LED at 460 nm wavelength and UVA LED at 385 nm was conducted to determine their effectiveness in disinfection of frequently isolated pathogens in hospitals (Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli). Determination of disinfection efficiency was carried out by measuring inhibition zone. Effects of varied exposure time on the inactivation of pathogenic microorganisms was studied. The results demonstrated that LED does not have germicidal activities. The highest inactivation for UVA LED was achieved for Pseudomonas aeruginosa. Linear relationship was found between exposure time and log reduction. This study showed that UVA LEDs can effectively inactivate significantly higher number of microorganisms hence can be used in disinfection of various applications

Prioritizing treatment outcomes: How people with acne vulgaris decide if their treatment is working

Objective To collect information about how people with acne make day‐to‐day decisions concerning the effectiveness of their treatment. Methods Between May and August 2013, an optional question was embedded in the James Lind Alliance Acne Priority Setting Partnership's online survey to collect treatment uncertainties. The question asked people with acne to “Tell us in your own words how you decide if your treatment has been effective.” Results A total of 742 respondents specified at least one outcome or means of assessing change (outcome measure). Fewer spots were the most commonly cited outcome, identified by 272 respondents (36.7%). Other frequently mentioned outcomes were in descending order: less redness (19.4%), reduction in spot size (12.1%), and less pain/discomfort (11.4%). Signs were much more commonly used than symptoms and surrogate outcomes such as changes in aspects of life quality were infrequently mentioned. Visual inspection of the skin was the most widely adopted outcome measure (16.3%). Conclusions Although the most frequently used methods map well onto the outcome measures adopted in the majority of acne trials, namely physician‐assessed changes in lesion counts and global acne severity, people with acne often take into account several factors that cannot be assessed by a third party at a single point in time. The minimal use of changes in psychosocial wellbeing and mood may reflect that these are regarded as secondary consequences of improvements in appearance. The robustness of these findings now requires independent evaluation. If confirmed, they could form the basis of a new patient‐reported outcome measure

Self-organized stress patterns drive state transitions in actin cortices

Biological functions rely on ordered structures and intricately controlled collective dynamics. This order in living systems is typically established and sustained by continuous dissipation of energy. The emergence of collective patterns of motion is unique to nonequilibrium systems and is a manifestation of dynamic steady states. Mechanical resilience of animal cells is largely controlled by the actomyosin cortex. The cortex provides stability but is, at the same time, highly adaptable due to rapid turnover of its components. Dynamic functions involve regulated transitions between different steady states of the cortex. We find that model actomyosin cortices, constructed to maintain turnover, self-organize into distinct nonequilibrium steady states when we vary cross-link density. The feedback between actin network structure and organization of stress-generating myosin motors defines the symmetries of the dynamic steady states. A marginally cross-linked state displays divergence-free long-range flow patterns. Higher cross-link density causes structural symmetry breaking, resulting in a stationary converging flow pattern. We track the flow patterns in the model actomyosin cortices using fluorescent single-walled carbon nanotubes as novel probes. The self-organization of stress patterns we have observed in a model system can have direct implications for biological functions

Performance Regression Detection in DevOps

Performance is an important aspect of software quality. The goals of performance are typically defined by setting upper and lower bounds for response time and throughput of a system and physical level measurements such as CPU, memory, and I/O. To meet such performance goals, several performance-related activities are needed in development (Dev) and operations (Ops). Large software system failures are often due to performance issues rather than functional bugs. One of the most important performance issues is performance regression. Although performance regressions are not all bugs, they often have a direct impact on users’ experience of the system. The process of detection of performance regressions in development and operations is faced with challenges. First, the detection of performance regression is conducted after the fact, i.e., after the system is built and deployed in the field or dedicated performance testing environments. Large amounts of resources are required to detect, locate, understand, and fix performance regressions at such a late stage in the development cycle. Second, even we can detect a performance regression, it is extremely hard to fix it because other changes are applied to the system after the introduction of the regression. These challenges call for further in-depth analyses of the performance regression. In this thesis, to avoid performance regression slipping into operation, we first perform an exploratory study on the source code changes that introduce performance regressions in order to understand root-causes of performance regression in the source code level. Second, we propose an approach that automatically predicts whether a test would manifest performance regressions in a code commit. Most of the performance issues are related to configurations. Therefore, third, we propose an approach that predicts whether a configuration option manifests a performance variation issue. To assist practitioners to analyze system performance with operational data, we propose an approach to recovering field-representative workload that can be used to detect performance regression