Nonhydrolyzable Heptose Bis- and Monophosphate Analogues Modulate Pro-inflammatory TIFA-NF-κB Signaling

d -Glycero-d -manno-heptose-1β,7-bisphosphate (HBP) and d -glycero-d -manno-heptose-1β-phosphate (H1P) are bacterial metabolites that were recently shown to stimulate inflammatory responses in host cells through the activation of the TIFA-dependent NF-κB pathway. To better understand structure-based activity in relation to this process, a family of nonhydrolyzable phosphonate analogues of HBP and H1P was synthesized. The inflammation modulation by which these molecules induce the TIFA-NF-κB signal axis was evaluated in vivo at a low-nanomolar concentration (6 nM) and compared to that of the natural metabolites. Our data showed that three phosphonate analogues had similar stimulatory activity to HBP, whereas two phosphonates antagonized HBP-induced TIFA-NF-κB signaling. These results open new horizons for the design of pro-inflammatory and innate immune modulators that could be used as vaccine adjuvant.     

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.     

Design rules for an integratable low-power amplifier/filter combination

In this paper design rules for a circuit topology in which there is an inseparable combination of an amplifier and a filter characteristic, are presented. By intentionally using the capacitance of an already present input sensor for the filtering, the total required integrated capacitance is much less than that in circuits, which have a separately designed amplifier and filter function. Consequently, it is possible to have the advantage of a better integratability. Moreover, less complexity in the design is achieved. The presented circuit shows a current-to-voltage conversion and an inherently controllable second-order low-pass filter characteristic. A discrete realization has been designed to test the circuit. This circuit operates down to a 1 V supply voltage and the transfer shows a 1.8 M currentto-voltage conversion with a bandwidth of 6 kHz. Measurement results of this circuit show that a 63 dB dynamic range can be achieved with a total required integrated capacitance of only 31 pF.     

Filter-resistant code injection on ARM

Code injection attacks are one of the most powerful and important classes of attacks on software. In these attacks, the attacker sends malicious input to a software application, where it is stored in memory. The malicious input is chosen in such a way that its representation in memory is also a valid representation of a machine code program that performs actions chosen by the attacker. The attacker then triggers a bug in the application to divert the control flow to this injected machine code. A typical action of the injected code is to launch a command interpreter shell, and hence the malicious input is often called shellcode. Attacks are usually performed against network facing applications, and such applications often perform validations or encodings on input. Hence, a typical hurdle for attackers, is that the shellcode has to pass one or more filtering methods before it is stored in the vulnerable application??s memory space. Clearly, for a code injection attack to succeed, the malicious input must survive such validations and transformations. Alphanumeric input (consisting only of letters and digits) is typically very robust for this purpose: it passes most filters and is untouched by most transformations. This paper studies the power of alphanumeric shellcode on the ARM architecture. It shows that the subset of ARM machine code programs that (when interpreted as data) consist only of alphanumerical characters is a Turing complete subset. This is a non-trivial result, as the number of instructions that consist only of alphanumeric characters is very limited. To craft useful exploit code (and to achieve Turing completeness), several tricks are needed, including the use of self-modifying code.     

Effects of face-to-face versus chat communication on performance in a collaborative inquiry modeling task

In many contemporary collaborative inquiry learning environments, chat is being used as a means for communication. Still, it remains an open issue whether chat communication is an appropriate means to support the deep reasoning process students need to perform in such environments. Purpose of the present study was to compare the impact of chat versus face-to-face communication on performance within a collaborative computer-supported modeling task. 44 Students from 11th-grade pre-university education, working in dyads, were observed during modeling. Dyads communicated either face-to-face or through a chat tool. Students’ reasoning during modeling was assessed by analyzing verbal protocols. In addition, we assessed the quality of student-built models. Results show that while model quality scores did not differ across both conditions, students communicating through chat compressed their interactions resulting in less time spent on surface reasoning, whereas students who communicated face-to-face spent significantly more time on surface reasoning.     

Toric forms of elliptic curves and their arithmetic

We scan a large class of one-parameter families of elliptic curves for efficient arithmetic. The construction of the class is inspired by toric geometry, which provides a natural framework for the study of various forms of elliptic curves. The class both encompasses many prominent known forms and includes thousands of new forms. A powerful algorithm is described that automatically computes the most compact group operation formulas for any parameterized family of elliptic curves. The generality of this algorithm is further illustrated by computing uniform addition formulas and formulas for generalized Montgomery arithmetic.     

Grounded design: Design patterns as the link between theory and practice

The process of designing a networked learning environment can be characterized by a high degree of uncertainty. This is especially true when the design includes innovative technologies. It is difficult to design a networked learning environment that closely fits the requirements of the educational practice. Often the technology seems leading in the design process because it is the most tangible aspect of the e-learning environment. This brings along the risk that the technology becomes detached from its context of use.Design patterns are a means to overcome this problem of detachment between design and practice. Design patterns make the tight relationship between the two more explicit. In this paper we further elaborate on the relationship between design and practice. We will stress the importance of theory in the development of design patterns. Theory development is an essential aspect of our approach to the development of design patterns. The approach is oriented towards a systematic analysis of problems and the development of conceptual models that guide the definition and evaluation of design patterns. In this paper we present a case study of how the approach was used to develop design patterns for networked learning in the classroom.     

Guarding against online threats: why entrepreneurs take protective measures

Information technology is becoming increasingly important for entrepreneurs. Protecting their technical infrastructure and stored data is, therefore, also becoming more vital. Nevertheless, research into the safety and security of entrepreneurs in general, and online threats targeted at entrepreneurs in particular, is still limited. This study investigates to what extent self-employed entrepreneurs protect themselves against online threats, and what motivates them to do so. Based on secondary analyses on data collected from 1622 Dutch entrepreneurs, we observe that the majority implement technical and personal coping measures. By adopting protection motivation theory as a theoretical basis for our study, we found that coping appraisal explains the adoption of protective measures. Entrepreneurs are likely to implement protective measures when they believe a measure is effective, when they are capable of using internet technology, when their attitude towards online protection is positive and when they believe they are responsible for their own online security. Although the secondary analysis provides some limitations, this study offers new insights into the usage of protective measures and the motivation for taking them. These insights can help to improve information security campaigns.