Intrauterine deaths — an unsolved problem in Polish perinatology

Objectives: The Polish criteria for “intrauterine death” include fetal demise after 22 weeks of gestation, weighing > 500 g and body length at least 25 cm, when the gestational age is unknown. The rate of fetal death in Poland in 2015 is 3:10,000. In 2020, 1,231 stillbirths were registered. Material and methods: An analysis using 142,662 births in the period between 2015–2020 in 11 living in Poland. The first subgroup was admitted as patients > 22 to the beginning of the 30th week of pregnancy (n = 229), and the second from the 30th week of pregnancy inclusively (n = 179). In the case of women from both subgroups, there was a risk of preterm delivery close to hospitalization. Results: It was found that stillbirth in 41% of women in the first pregnancy. For the patient, stillbirth was also the first in his life. The average stillbirth weight was 1487 g, the average body length was 40 cm. Among fetuses up to 30 weeks, male fetuses are born more often, in subgroup II, the sex of the child was usually female. Most fetal deaths occur in mothers < 15 and > 45 years of age. Conclusions: According to the Polish results of the origin of full-term fetuses > 30 weeks of gestation for death in the concomitant antenatal, such as placental-umbilical and fetal hypoxia, acute intrapartum effects rarely, and moreover < 30 Hbd fetal growth restriction (FGR), occurring placental-umbilical, acute intrapartum often

Design challenges of privacy controls for IoT systems

The Internet of Things (IoT), based on single-purpose internet-connected devices, becomes more and more pervasive. It is increasingly adopted by private households and hospitality industry, providing services such as security, monitoring or voice assistance via the "cloud". In order to develop effective privacy controls for this technology, users should be kept in the loop of managing the flows of the data they generate. That\u27s why user’s privacy preferences and respective contextual factors need to be understood and incorporated in the design of corresponding controls, which is the topic of this work.Although the users of IoT environments had relatively accurate mental models about the data practices employed by IoT vendors, they did not steer the users towards taking protective actions. IoT users still expect vendors and regulators or policymakers to protect them from the privacy and security threats entailed by the adoption of in-house IoT devices. Other findings revealed that users underestimate these threats and are uncertain and/or unaware of privacy and security controls offered by IoT vendors. These findings suggest the demand for tools such as indicators of data collection and data flows, to address the issues of user awareness. Next, usable control interfaces are needed to empower IoT users in making informed decisions about the privacy of their household-generated data.Following up on the prevalence of voice assistants as the main control interface for in-house IoT devices, the second work investigated users’ expectations of the next generation of this technology based on constant listening. It examined contextual factors such as the sensitivity of a conversation to be shared with the assistant in exchange for service provision, perceived service usefulness or perceived comfort of service provision. The most desired but at the same time the most controversial types of services this technology can offer turned out to be carrying out actions on users’ behalf. Main concerns respondents expressed pertained to privacy and conveniences such an assistant can offer. Further, study participants pointed to the importance of robustness of the system in respecting their preferences of how relevant or timely the offered assistance is. These concerns pointed to the need of providing ways of enforcing a set of user preferences in the end user product. The identified concerns were found to influence users’ privacy decision making when considering trade-offs between privacy and convenience offered by the next generation of voice assistants.The thesis also offers a reflection on how to improve the usability of existing and which factors to consider when designing new privacy controls for IoT by investigating the data flows generated by IoT devices and by designing privacy indicators, controls and certification mechanism

Privacy expectations and challenges of smart home ecosystems

Technology has long facilitated our lives. Nowadays, we increasingly embrace living in digital spaces. Sometimes we cannot avoid enrolling into them, if only because staying outside makes our lives more complicated.One technology that has become almost universally accepted as unavoidable to fully participate as a person is the smartphone, but in their use we balance trading our privacy for convenience. To mitigate this, the evolution of smartphone privacy controls is an example of how researchers work to shield users from privacy risks. Another technology that enters our lives and homes is the Internet of Things (IoT). Unlike smartphones, the IoT has not converged in a few common platforms (like Android and iOS), but is spread out over numerous, separate ecosystems of individual vendors. In addition, IoT ecosystems are closed by design; both data collection and processing is realized by black-box devices and vendor backends. This makes it challenging to devise a unified privacy protection measure for the IoT that, for instance, smartphone users enjoy – a permission system.Addressing this challenge, my thesis aims at providing an early foundation for designing an IoT permission system. It sets out to understand associated design challenges in several dimensions, from the perspectives of users and the technology.The user side was studied with qualitative and mixed Human-Computer Interaction (HCI) methods, such as interviews and surveys. The exploration of the technology side involved mobile IoT companion apps and IoT devices themselves. The former was conducted through a combination of static and dynamic analysis. The latter was approached from the perspective of emulating the externally observable network behavior of the devices and the ecosystem.The contributions of this work begin with providing empirical evidence on the understanding that IoT users have of the data processing practices of this technology as well as user expectations of such practices; both from a privacy perspective. Secondly, a thorough study of mobile IoT companion apps has shed light on how the effectively mandatory use of the apps factors into the information exposure of IoT users and how the users react to that. Finally, a system intended to facilitate the prototyping of IoT privacy tools, e.g. a permission system, is proposed.The multi-faceted approach applied in this work to study design challenges of an IoT permission system intends to serve as a stepping stone for research aimed at supporting IoT users in making informed choices about their privacy

Towards interactive visualization of public discourse in time and space

We report on a proof-of-concept study where we (1) apply NLP tools for extracting political-discourse topics from a large Swedish Twitter dataset; and (2) design an interactive spatiotemporal visualization application allowing humanities and social-science scholars to explore how the tweet topics vary over space and time

"I don\u27t own the data": End User Perceptions of Smart Home Device Data Practices and Risks

Smart homes are more connected than ever before, with a variety of commercial devices available. The use of these devices introduces new security and privacy risks in the home, and needs for helping users to understand and mitigate those risks. However, we still know little about how everyday users understand the data practices of smart home devices, and their concerns and behaviors regarding those practices. To bridge this gap, we conducted a semi-structured interview study with 23 smart home users to explore what people think about smart home device data collection, sharing, and usage practices; how that knowledge affects their perceived risks of security and privacy; and the actions they take to resolve those risks. Our results reveal that while people are uncertain about manufacturers\u27 data practices, users\u27 knowledge of their smart home does not strongly influence their threat models and protection behaviors. Instead, users\u27 perceptions and concerns are largely shaped by their experiences in other computing contexts and with organizations. Based on our findings, we provide several recommendations for policymakers, researchers and designers to contribute to users\u27 risk awareness and security and privacy practices in the smart home

Genetic Diversity of Type A Influenza Viruses Found in Swine Herds in Northwestern Poland from 2017 to 2019: The One Health Perspective

Influenza A viruses (IAV) are still a cause of concern for public health and veterinary services worldwide. With (−) RNA-segmented genome architecture, influenza viruses are prone to reassortment and can generate a great variety of strains, some capable of crossing interspecies barriers. Seasonal IAV strains continuously spread from humans to pigs, leading to multiple reassortation events with strains endemic to swine. Due to its high adaptability to humans, a reassortant strain based on “human-like” genes could potentially be a carrier of avian origin segments responsible for high virulence, and hence become the next pandemic strain with unseen pathogenicity. The rapid evolution of sequencing methods has provided a fast and cost-efficient way to assess the genetic diversity of IAV. In this study, we investigated the genetic diversity of swine influenza viruses (swIAVs) collected from Polish farms. A total of 376 samples were collected from 11 farms. The infection was confirmed in 112 cases. The isolates were subjected to next-generation sequencing (NGS), resulting in 93 full genome sequences. Phylogenetic analysis classified 59 isolates as genotype T (H1avN2g) and 34 isolates as genotype P (H1pdmN1pdm), all of which had an internal gene cassette (IGC) derived from the H1N1pdm09-like strain. These data are consistent with evolutionary trends in European swIAVs. The applied methodology proved to be useful in monitoring the genetic diversity of IAV at the human–animal interface

A fuzzy data-based model for Human-Robot Proxemics

This work aims at bringing empirical knowledgeon Human-Robot Interaction obtained from user studies closerto being integrated into the capabilities of robots currentlyavailable on the market. The Takagi-Sugeno-Kang method andresults of a user study conducted with thirty two participantswere used to build a fuzzy data-based model for Human-RobotProxemics. The experiment investigated the effect of robotapproach distance and angle on perceived human comfort. Theproposed model, consisting of a set of rules, fuzzy sets and theirparameters, can be used by the robotics community thanksto their formal form. It can also be directly translated intonatural language statements. Results of model cross-validationare reported

Ubitile: A Finger-Worn I/O Device for Tabletop Vibrotactile Pattern Authoring

While most mobile platforms offer motion sensing as input for creating tactile feedback, it is still hard to design such feedback patterns while the screen becomes larger, e.g. tabletop surfaces. This demonstration presents Ubitile, a finger-worn concept offering both motion sensing and vibration feedback for authoring of vibrotactile feedback on tabletops. We suggest the mid-air motion input space made accessible using Ubitile outperforms current GUI-based visual input techniques for designing tactile feedback. Additionally Ubitile offers a hands-free input space for the tactile output. Ubitile integrates both input and output spaces within a single wearable interface, jointly affording spatial authoring/editing and active tactile feedback on- and above- tabletops