Experimental structure determination of the chemisorbed overlayers of chlorine and iodine on Au{111}

We have performed an experimental structure determination of the ordered p(sqrt[3] x sqrt[3])R30 degrees structures of chlorine and iodine on Au{111} using low-energy electron diffraction (LEED). Despite great similarities in the structure of the underlying substrate, which shows only minor deviations from the bulk positions in both cases, chlorine and iodine are found to adsorb in different adsorption sites, fcc and hcp hollow sites, respectively. The experimental Au-Cl and Au-I bond lengths of 2.56 and 2.84 A are close to the sums of the covalent radii, supporting the view that the bond is essentially covalent in nature; however, they are significantly shorter than predicted theoretically

Prediction, evolution and privacy in social and affiliation networks

In the last few years, there has been a growing interest in studying online social and affiliation networks, leading to a new category of inference problems that consider the actor characteristics and their social environments. These problems have a variety of applications, from creating more effective marketing campaigns to designing better personalized services. Predictive statistical models allow learning hidden information automatically in these networks but also bring many privacy concerns. Three of the main challenges that I address in my thesis are understanding 1) how the complex observed and unobserved relationships among actors can help in building better behavior models, and in designing more accurate predictive algorithms, 2) what are the processes that drive the network growth and link formation, and 3) what are the implications of predictive algorithms to the privacy of users who share content online. The majority of previous work in prediction, evolution and privacy in online social networks has concentrated on the single-mode networks which form around user-user links, such as friendship and email communication. However, single-mode networks often co-exist with two-mode affiliation networks in which users are linked to other entities, such as social groups, online content and events. We study the interplay between these two types of networks and show that analyzing these higher-order interactions can reveal dependencies that are difficult to extract from the pair-wise interactions alone. In particular, we present our contributions to the challenging problems of collective classification, link prediction, network evolution, anonymization and preserving privacy in social and affiliation networks. We evaluate our models on real-world data sets from well-known online social networks, such as Flickr, Facebook, Dogster and LiveJournal

The dark side of light. Light pollution kills leatherback turtle hatchlings

The leatherback turtle is the largest and most migratory of all sea turtles and deepest diving air-breathing animal. It has unique physiology which allows it to adapt to various habitats ranging from sub-polar to equatorial during its migrations. The leatherback turtle is also the only sea turtle where no cases of tumours have been diagnosed. These unique features add to the arguments for preservation of this endangered species. Here we discuss the effect of light pollution on leatherback turtle hatchlings in Tobago and the measures for their protection

Methodology of the training in health care system for preparation of the future medical professionals to work with children and adults with special needs

Dzieci i dorośli ze specjalnymi potrzebami są pełnoprawnymi członkami naszego społeczeństwa. Rozwijają się i żyją między nami. Dzielą swoje życie z przyjaciółmi, sąsiadami i bliskimi. Artykuł ma na celu przedstawianie zarysu systemu kształcenia przygotowującego przyszły personel medyczny do pracy z osobami ze specjalnymi potrzebami. Prezentowany "Indywidualny plan opieki zdrowotnej" zawiera cenne informacje dla dzieci i dorosłych ze specjalnymi potrzebamiChildren and adults with special needs are members of our society and take their place in it. They develop themselves and live among us. Share their lives with friends, neighbors and relatives. The methodology of training in health care aims to reveal and outline the system of training of future medical specialists to work with children and adults with special needs in the high school. The study presents the process and the conditions under which the methodology is a factor in the system of training of the specialists to work with these individuals. Presented "Individual healthcare plan" contains valuable information for needy children and adults with special needs car

SAFETY AND HEALTH OF STUDENTS DURING THEIR TRAINING AT THE HIGHER MEDICAL

The scientific communication presents the essence of the concepts "safety" and "health". The risks of the modern educational environment for the health condition of the students-specialists in health care are considered. The measures and actions that must be taken to prevent and overcome the negative effects of modern training on the health of future health care professionals, as well as ensuring safe conditions for their practical training in a real hospital environment are presented. The main concepts related to the assessment of the risks for health and safety in the process of education in the higher medical school are considered. Leading are the conditions of promotion and prevention for student health

The Methodology of Training in Health Care - a Condition and Factor for Successful Implementation of Patient Safety in the Application of Medical Care

INTRODUCTION: Higher education in school is a purposeful process of interaction between teachers and students. There are trained specialists suited to carry out professional activities and provide quality and safe health care for people. The methodology of training in health care offers safe, effective, individual, efficient, timely and equitable care.AIM: The aim of the scientific report is to reveal and outline the organizational pedagogical conditions and the effectiveness of the methodology for the successful implementation of patient safety efforts in medical care. Patient safety is focused on the acquisition of knowledge, skills and competencies students need to work efficiently in the field of health care.MATERIALS AND METHODS: The aim of the study is to reveal the role of methodology in the application of safe patient care; to investigate the effectiveness and its importance in patient safety; to establish the level of satisfaction with the application of safe patient care. The methods used during the research were: programmed interview with a survey and a pedagogical experiment. The subject of the research were students from the Nurse program, educators in health care, medical professionals, and patients. The object of the research were the process and the conditions under which the methodology was provided, a factor for successful implementation of patient safety when caring for patients.RESULTS: The analysis of the results allowed to conclude that the teaching methodology in health care:• is an important condition and factor in the successful implementation of patient safety (100%);• maintains, improves and enhances the acquisition of knowledge, skills and competencies of health professionals(98%);• is a key to addressing the needs of patients (89%);• satisfies the requirements of medical professionals to provide safe care for patients and their personal training (100%).CONCLUSION: The methodology of training in health care is a condition and factor for success in providing safe and high quality care for patients

Minimizing Interference and Selection Bias in Network Experiment Design

Current approaches to A/B testing in networks focus on limiting interference, the concern that treatment effects can "spill over" from treatment nodes to control nodes and lead to biased causal effect estimation. Prominent methods for network experiment design rely on two-stage randomization, in which sparsely-connected clusters are identified and cluster randomization dictates the node assignment to treatment and control. Here, we show that cluster randomization does not ensure sufficient node randomization and it can lead to selection bias in which treatment and control nodes represent different populations of users. To address this problem, we propose a principled framework for network experiment design which jointly minimizes interference and selection bias. We introduce the concepts of edge spillover probability and cluster matching and demonstrate their importance for designing network A/B testing. Our experiments on a number of real-world datasets show that our proposed framework leads to significantly lower error in causal effect estimation than existing solutions.Comment: This paper has been accepted at the International AAAI Conference on Web and Social Media (ICWSM 2020

Inferring Causal Effects Under Heterogeneous Peer Influence

Causal inference in networks should account for interference, which occurs when a unit's outcome is influenced by treatments or outcomes of peers. There can be heterogeneous peer influence between units when a unit's outcome is subjected to variable influence from different peers based on their attributes and relationships, or when each unit has a different susceptibility to peer influence. Existing solutions to causal inference under interference consider either homogeneous influence from peers or specific heterogeneous influence mechanisms (e.g., based on local neighborhood structure). This paper presents a methodology for estimating individual causal effects in the presence of heterogeneous peer influence due to arbitrary mechanisms. We propose a structural causal model for networks that can capture arbitrary assumptions about network structure, interference conditions, and causal dependence. We identify potential heterogeneous contexts using the causal model and propose a novel graph neural network-based estimator to estimate individual causal effects. We show that existing state-of-the-art methods for individual causal effect estimation produce biased results in the presence of heterogeneous peer influence, and that our proposed estimator is robust