Collective institutional work: the case of Airbnb in Amsterdam,London and New York

ABSTRACT

Given that online platforms disrupt established industries and challenge existing institutions, they can only be successful if their innovation becomes both legal and legitimate. This requires ‘institutional work’ that changes perceptions and regulations within society. Rather than only focussing on the online platform as the sole agent engaging in institutional work, our study analyses institutional work as a collective process. We investigate the case of home-sharing platform Airbnb and the process of institutional change its introduction prompted regarding short-term rental in Amsterdam, London and New York. We find, contrary to the popular view of online platforms as disruptive entrepreneurs, that the platform mainly focusses on creating new institutions rather than disrupting existing ones, and that users and non-users undertake most of the institutional work activities. We also show that different types of actors carry out different types of institutional work suggesting that the process of institutional work is highly distributed.     

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.     

Understanding TES microcalorimeter noise and energy resolution

We have performed numerical calculations of the noise in voltage-biased superconducting transition edge-based X-ray microcalorimeters, using a finite-element model. Details of the model are discussed, as well as results for different absorber geometries. The results are in agreement with an analytical model and show that the amount of internal thermal fluctuation noise can be reduced by using a segmented absorber. The simulation also agrees well with experimental data, which, for our detectors, contain no major unidentified noise sources. Furthermore, the discrepancy between the (small-signal) theoretical and the measured energy resolutions for 5.9 keV X-rays, for our sensors typically a factor of 2, is explained by a more accurate modelling of the sensor responsivity, taking into account the large signal behaviour.     

Identification of valence shifts in Au during the water-gas shift reaction

In situ X-ray absorption spectroscopy (XAS) has been performed to investigate the active site on Au-based catalysts in the water-gas shift (WGS) reaction. The surface area and hence the WGS activity is higher for AuTiO₂ catalysts supported on carbon nanofibres (CNF) than TiO₂. The WGS reaction rate depends on the Au coordination number with an apparent maximum close to eight which corresponds to a particle size of approximately 2.5–3.0 nm. A likely cause for the changes in the electronic structure of Au is the adsorption of CO on the surface, which also creates a small positive charge in the Au atoms. The catalytic activity significantly improves when titania is present compared to Au deposited directly on CNF.     

Microblog language identification: overcoming the limitations of short, unedited and idiomatic text

Multilingual posts can potentially affect the outcomes of content analysis on microblog platforms. To this end, language identification can provide a monolingual set of content for analysis. We find the unedited and idiomatic language of microblogs to be challenging for state-of-the-art language identification methods. To account for this, we identify five microblog characteristics that can help in language identification: the language profile of the blogger (blogger), the content of an attached hyperlink (link), the language profile of other users mentioned (mention) in the post, the language profile of a tag (tag), and the language of the original post (conversation), if the post we examine is a reply. Further, we present methods that combine these priors in a post-dependent and post-independent way. We present test results on 1,000 posts from five languages (Dutch, English, French, German, and Spanish), which show that our priors improve accuracy by 5 % over a domain specific baseline, and show that post-dependent combination of the priors achieves the best performance. When suitable training data does not exist, our methods still outperform a domain unspecific baseline. We conclude with an examination of the language distribution of a million tweets, along with temporal analysis, the usage of twitter features across languages, and a correlation study between classifications made and geo-location and language metadata fields.     

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.