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Major legal, philosophical, and scientific discussions regard control over personal information as a cornerstone of users’ fundamental right to privacy. Even though user perceptions of control determine whether and how people exercise their control, little is known about how these perceptions develop. We identify a property of the personal information the online service providers process, naming it the “Order of Control”. In an online experiment ( $N=329$ ) with a pre-study ( $N=110$ ), we investigate how this property and personal information relevance affect users’ perceived control across three contexts of disclosure through mobile devices: meet ups, mobile payments, and food delivery. We find that perceived control differs depending on a person’s assumptions regarding the required levels of information processing. This effect was moderated by information relevance, albeit not systematically, and differed across the three contexts. The results also reveal that users tend to assume that any personal information may be recoverable from any other disclosed personal data, limiting their control over such information. Privacy practitioners and system designers should consider informing the users regarding outcomes of their disclosure and sharing decisions, while researchers should further investigate how user perceptions of control form and manifest themselves.

Introduction: This study was carried out to investigate the impact of duration of different renal replacement therapies such as hemodialysis and continuous ambulatory peritoneal dialysis on potential overproduction of endothelin-1 (ET-1) and pulmonary function tests in these patients.Materials and methods: The study included 26 patients (14 males, mean age 54.9±16.2 years) with end stage renal diseases (ESRD) receiving regular hemodialysis (HD) and 23 patients (10 males, mean age 55.8±15.8 years) with ESRD treated with continuous ambulatory peritoneal dialysis (CAPD). The spirometry values were recorded before the onset of HD and prior to emptying the peritoneal cavity in CAPD patients and ET-1 was measured using the enzyme immunoassay (EIA) methodology. Two groups of patients (groups 1 and 2) were further divided into subgroups (group A and group B). Groups A (1-A and 2-A) included patients treated with any type of renal replacement therapy (RRT) (HD or CAPD) less than 5 years, and groups B (1-B and 2-B) included patients treated with any type of RRT (HD or CAPD) longer than 5 years.Results: Patients treated with HD or CAPD for more than five years were found to have significantly higher serum levels of ET-1 (HD = 41.49±21.28 vs. 185.13±73.67, p

Time series mapping of snow volume in the mountains at global scales and at resolutions needed for water resource management is an unsolved challenge to date. Snow depth mapping by differencing surface elevations from airborne lidar is a mature measurement approach filling the observation gap operationally in a few regions, primarily in mountain headwaters in the Western United States. The same concept for snow depth retrieval from stereo- or multi-view photogrammetry has been demonstrated, but these previous studies had limited ability to determine the uncertainties of photogrammetric snow depth at the basin scale. For example, assessments used non-coincident or discrete points for reference, masked out vegetation, or compared a subset of the fully snow-covered study domain. Here, using a unique data set with simultaneously collected airborne data, we compare snow depth mapped from multi-view Structure from Motion photogrammetry to that mapped by lidar at multiple resolutions over an entire mountain basin (300 km2). After excluding reconstruction errors (negative depths), SfM had lower snow-covered area (∼27%) and snow volume (∼16%) compared to lidar. The reconstruction errors were primarily in areas with vegetation, shallow snow (< 1 m), and steep slopes (> 60°C). Across the overlapping snow extent, snow depths compared well to lidar with similar mean values (< 0.03 m difference) and snow volume (± 5%) for output resolutions of 3 m and 50 m, and with a normalized median absolute deviation of 0.19 m. Our results indicate that photogrammetry from aerial images can be applied in the mountains but would perform best for deeper snowpacks above tree line.

High Mountain Asia (HMA) has the largest expanse of snow outside of the polar regions and it plays a critical role in climate and hydrology. In situ monitoring is rare due to terrain complexity and inaccessibility, making remote sensing the most practical way to understand snow patterns in HMA despite relatively short periods of record. Here, trends in snow cover duration were assessed using MODIS between 2002 and 2017 across the headwaters of the region’s primary river basins (Amu Darya, Brahmaputra, Ganges, Indus, and Syr Darya). Data limitations, associated with traditional binary mapping and data gaps due to clouds, were addressed with a daily, spatially and temporally complete, snow cover product that maps the fraction of snow in each pixel using spectral mixture analysis. Trends in fractional snow cover duration (fSCD) were calculated at the annual and monthly scale, and across 1,000 m elevation bands, and compared to trends in binary snow cover duration (SCD). Snow cover is present, on average, for 102 days across all basin headwaters, with the longest duration in western basins and shortest in eastern basins. Broadly, snow cover is in decline, which is most pronounced in elevation bands where snow is most likely to be present and most needed to sustain glaciers. Some of the strongest negative trends in fSCD were in the Syr Darya, which has 13 fewer days between 4,000–5,000 m, and Brahmaputra, which has 31 fewer days between 5,000–6,000 m. The only increasing tendency was found in the Indus between 2,000 and 5,000 m. There were differences between fSCD and SCD trends, due to SCD overestimating snow cover area relative to fSCD.

Next-generation multi-specific antibody therapeutics (MSATs) are engineered to combine several functional activities into one molecule to provide higher efficacy compared to conventional, mono-specific antibody therapeutics. However, highly engineered MSATs frequently display poor yields and less favorable drug-like properties (DLPs), which can adversely affect their development. Systematic screening of a large panel of MSAT variants in very high throughput (HT) is thus critical to identify potent molecule candidates with good yield and DLPs early in the discovery process. Here we report on the establishment of a novel, format-agnostic platform process for the fast generation and multiparametric screening of tens of thousands of MSAT variants. To this end, we have introduced full automation across the entire value chain for MSAT engineering. Specifically, we have automated the in-silico design of very large MSAT panels such that it reflects precisely the wet-lab processes for MSAT DNA library generation. This includes mass saturation mutagenesis or bulk modular cloning technologies while, concomitantly, enabling library deconvolution approaches using HT Sanger DNA sequencing. These DNA workflows are tightly linked to fully automated downstream processes for compartmentalized mammalian cell transfection expression, and screening of multiple parameters. All sub-processes are seamlessly integrated with tailored workflow supporting bioinformatics. As described here, we used this platform to perform multifactor optimization of a next-generation bispecific, cross-over dual variable domain-Ig (CODV-Ig). Screening of more than 25,000 individual protein variants in mono- and bispecific format led to the identification of CODV-Ig variants with over 1,000-fold increased potency and significantly optimized production titers, demonstrating the power and versatility of the platform.

In this viewpoint we make specific recommendations that can assist and make the return to sport/exercise as safe as possible for all those impacted – from the recreational athlete to the elite athlete. We acknowledge that there are varying rules and regulations around the world, not to mention the varying philosophies and numerous schools of thought as it relates to return to sport/exercise and we have been cognisant of this in our recommendations. Despite the varying rules and circumstances around the world, we believe it is essential to provide some helpful and consistent guidance for return to training and sport for sport and exercise physicians around the world at this most difficult time. The present viewpoint provides practical and medical recommendations on the resumption to sport process.

Abstract Societal unrest and similar events are important for societies, but it is often difficult to quantify their effects on individuals, hindering a timely and effective policy-making in emergencies and in particular localized social shocks such as protests. Traditionally, effects are assessed through economic indicators or surveys with relatively low temporal and spatial resolutions. In this work, we compute two behavioral indexes, based on the use of credit card transaction data, for measuring the economic effects of a series of protests on consumer actions and personal consumption. Using data from a metropolitan area in an OECD country, we show that protests affect consumers’ shopping frequency and spending, but in noticeably different ways. The effects show strong temporal and spatial patterns, vary between neighborhoods and customers of different socio-demographical characteristics as well as between merchants of different categories, and suggest interesting subtleties in purchase behavior such as displaced or delayed shopping activities. Our method can generally serve for the real-time monitoring of the effects of major social shocks or events on urban economy and consumer sentiment, providing high-resolution and cost-effective measurement tools to complement traditional economic indicators.

Operators often fail to rely sufficiently on alarm systems. This results in a joint human-machine (JHM) sensitivity below the one of the alarm system. The ‘confidence vs. trust hypothesis’ assumes the use of the system depends on the weighting of both values. In case of higher confidence, the task is performed manually, if trust is higher, the user relies on the system. Thus, insufficient reliance may be due to operators’ overconfidence in their own abilities and/or insufficient trust in the decision automation, but could be mitigated by providing feedback. That was investigated within a signal detection task, supported by a system with either higher sensitivity (HSS) or lower sensitivity (LSS) than the human, while being provided with feedback or not. We expected disuse of the LSS and insufficiently reliance on the HSS, in the condition without feedback. The feedback was expected to increase reliance on the HSS through an increase in trust and/or decreases in confidence, and thus, improve performance. Hypotheses were partly supported. Confidence in manual performance was similar to trust in the HSS even though humans’ sensitivity was significantly lower than systems’ sensitivity. While confidence had not effect on reliance or JHM sensitivity, trust was found to be positively related with both. We found disuse of the HSS, that could be improved through feedback, increasing also trust and JHM sensitivity. However, contrary to ‘confidence vs. trust’ expectations, participants were also found to make use of the LSS. This misuse could not be reduced by feedback. Results indicate the use of feedback being beneficial for the overall performance (with HSS only). Findings do not support the idea that misuse or disuse of the system may result from comparison of confidence and trust. We suppose it may rather be the product of users’ wrong strategy of function allocation, based on the underlying idea of team work in combination with missing assignment of responsibility. We discuss this alternative explanation.

Novel embedded applications are characterized by increasing requirements on processing performance as well as the demand for communication between several or many devices. Networked Multiprocessor System-on-Chips (MPSoCs) are a possible solution to cope with this increasing complexity. Such systems require a detailed exploration on both architectures and system design. An approach that allows investigating interdependencies between system and network domain is the cooperative execution of system design tools with a network simulator. Within previous work, synchronization mechanisms have been developed for parallel system simulation and system/network co-simulation using the high level architecture (HLA). Within this contribution, a methodology is presented that extends previous work with further building blocks towards a construction kit for system/network co-simulation. The methodology facilitates flexible assembly of components and adaptation to the specific needs of use cases in terms of performance and accuracy. Underlying concepts and made extensions are discussed in detail. Benefits are substantiated by means of various benchmarks.

When graphene is placed on a crystalline surface, the periodic structures within the layers superimpose and moiré superlattices form. Small lattice rotations between the two materials in contact strongly modify the moiré lattice parameter, upon which many electronic, vibrational, and chemical properties depend. While precise adjustment of the relative orientation in the degree- and sub-degree-range can be achieved via careful deterministic transfer of graphene, we report on the spontaneous reorientation of graphene on a metallic substrate, Ir(111). We find that selecting a substrate temperature between 1530 and 1000 K during the growth of graphene leads to distinct relative rotational angles of 0°, ± 0.6°, ±1.1°, and ±1.7°. When modeling the moiré superlattices as two-dimensional coincidence networks, we can ascribe the observed rotations to favorable low-strain graphene structures. The dissimilar thermal expansion of the substrate and graphene is regarded as an effective compressive biaxial pressure that is more easily accommodated in graphene by small rotations rather than by compression.