Investing in Montenegro: Limits and Opportunties

Over the past few decades international flow of capital has contributed to the “globalisation” phenomena. Some countries took advantage of this, managing to develop their economies and to improve the standard of living of their citizens by attracting foreign investments. Others were not so successful. Countries of the South-Eastern Europe, hit by Balkan wars and economic sanctions, were late to be included in the first wave of international capital flow. But now, when the whole region tries to join the accession process to the European Union, foreign investments are more important then ever. This paper examines one such country – Montenegro, which suffered for almost two decades, isolated by economic sanctions and hit by the consequences of the Balkan wars. Montenegro is a part of the State Union of Serbia and Montenegro and it undertook extensive economic and social changes in order to fulfil the conditions for accession into the European Union. This paper presents general information for foreign investors interested in this part of Europe and describes specific benefits and risks that they may face during the process. There are many possibilities that can be exploited by educated investors not afraid to invest their capital in MontenegroInternational flow of capital, foreign investments, Montenegro, accession, foreign investors

Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints

We study a problem of optimal information gathering from multiple data providers that need to be incentivized to provide accurate information. This problem arises in many real world applications that rely on crowdsourced data sets, but where the process of obtaining data is costly. A notable example of such a scenario is crowd sensing. To this end, we formulate the problem of optimal information gathering as maximization of a submodular function under a budget constraint, where the budget represents the total expected payment to data providers. Contrary to the existing approaches, we base our payments on incentives for accuracy and truthfulness, in particular, {\em peer-prediction} methods that score each of the selected data providers against its best peer, while ensuring that the minimum expected payment is above a given threshold. We first show that the problem at hand is hard to approximate within a constant factor that is not dependent on the properties of the payment function. However, for given topological and analytical properties of the instance, we construct two greedy algorithms, respectively called PPCGreedy and PPCGreedyIter, and establish theoretical bounds on their performance w.r.t. the optimal solution. Finally, we evaluate our methods using a realistic crowd sensing testbed.Comment: Longer version of AAAI'18 pape

Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge

We study minimal single-task peer prediction mechanisms that have limited knowledge about agents' beliefs. Without knowing what agents' beliefs are or eliciting additional information, it is not possible to design a truthful mechanism in a Bayesian-Nash sense. We go beyond truthfulness and explore equilibrium strategy profiles that are only partially truthful. Using the results from the multi-armed bandit literature, we give a characterization of how inefficient these equilibria are comparing to truthful reporting. We measure the inefficiency of such strategies by counting the number of dishonest reports that any minimal knowledge-bounded mechanism must have. We show that the order of this number is $\Theta(\log n)$, where $n$ is the number of agents, and we provide a peer prediction mechanism that achieves this bound in expectation

Utfordringer ved prima vista tolking i asylintervjuer

Every year the Norwegian Directorate of Immigration (UDI) conducts approximately 10,000 interpreter-mediated asylum interviews in Norway. Each asylum interview ends with the interpreter providing a sight translation of the draft interview report (an oral translation of the text) to the asylum seeker. The UDI wished to find out why some interpreters took so much more time than others for sight translation. In response, Oslo and Akershus University College of Applied Sciences initiated a pilot project. The project’s working hypothesis was that slow sight translation was due mainly to a combination of three factors: interpreters’ poor reading skills; interpreters’ poor interpreting techniques; and/or interpreters’ unfamiliarity with the appropriate genre/style. A more complex picture emerged, however, from an analysis of 13 asylum interviews; group work involving 108 UDI interpreters; and discussions with UDI specialists. An asylum report is the joint product of all the participants in an asylum interview, who are typically the asylum seeker, the interviewer and the interpreter. The pilot study showed that each participant could contribute in various ways to slowing the speed of sight translation. Contributing factors identified that were unrelated to the interpreter included the interviewer’s competence in interview techniques; the interviewer’s competence in creating a written record of speech; the asylum seeker’s narrative ability; and the asylum seeker’s ability to correct mistakes in the draft report. All these factors may have just as much impact on the speed of sight translation as the interpreter’s competence. In addition, the physical strain caused by the length of asylum interviews (six hours plus) and the emotional stress potentially caused by such institutional interviews may affect the communicative abilities of all participants. As sight translation in the public sector is an under-researched area, the article starts with a discussion of terminology and an explanation of the UDI context. It then presents a possible explanation for slowness of sight translation and concludes that there is a need for more research into the various factors relevant to sight translation in the public sector and that there is a need to provide systematic training for both interpreters and interpreter users

Bayesian fairness

We consider the problem of how decision making can be fair when the underlying probabilistic model of the world is not known with certainty. We argue that recent notions of fairness in machine learning need to explicitly incorporate parameter uncertainty, hence we introduce the notion of {\em Bayesian fairness} as a suitable candidate for fair decision rules. Using balance, a definition of fairness introduced by Kleinberg et al (2016), we show how a Bayesian perspective can lead to well-performing, fair decision rules even under high uncertainty.Comment: 13 pages, 8 figures, to appear at AAAI 201

Expression of the Na/Pi-cotransporter Type IIb in Sf9 Cells: Functional Characterization and Purification

In mammals the type IIb Na/Pi-cotransporter is expressed in various tissues such as intestine, brain, lung and testis. The type IIb cotransporter shows 51% homology with the renal type IIa Na/Pi-cotransporter, for which a detailed model of the secondary structure has emerged based on recent structure/function studies. To make the type IIb Na/Pi-cotransporter available for future structural studies, we have expressed this cotransporter in Sf9 cells. Sf9 cells were infected with recombinant baculovirus containing 6His NaPi-IIb. Infected cells expressed a polypeptide of ~90 kDa, corresponding to a partially glycosylated form of the type IIb cotransporter. Transport studies demonstrated that the type IIb protein expressed in Sf9 cells mediates transport of phosphate in a Na-dependent manner with similar kinetic characteristics (apparent K ms for sodium and phosphate and pH dependence) as previously described. Solubilization experiments demonstrated that, in contrast to the type IIa cotransporter, the type IIb can be solubilized by nonionic detergents and that solubilized type IIb Na/Pi-cotransporter can be purified by Ni-NTA chromatograph

Calibrated Fairness in Bandits

We study fairness within the stochastic, \emph{multi-armed bandit} (MAB) decision making framework. We adapt the fairness framework of "treating similar individuals similarly" to this setting. Here, an `individual' corresponds to an arm and two arms are `similar' if they have a similar quality distribution. First, we adopt a {\em smoothness constraint} that if two arms have a similar quality distribution then the probability of selecting each arm should be similar. In addition, we define the {\em fairness regret}, which corresponds to the degree to which an algorithm is not calibrated, where perfect calibration requires that the probability of selecting an arm is equal to the probability with which the arm has the best quality realization. We show that a variation on Thompson sampling satisfies smooth fairness for total variation distance, and give an $\tilde{O}((kT)^{2/3})$ bound on fairness regret. This complements prior work, which protects an on-average better arm from being less favored. We also explain how to extend our algorithm to the dueling bandit setting.Comment: To be presented at the FAT-ML'17 worksho

How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness

What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people's perceptions of three of these fairness definitions. Across two online experiments, we test which definitions people perceive to be the fairest in the context of loan decisions, and whether fairness perceptions change with the addition of sensitive information (i.e., race of the loan applicants). Overall, one definition (calibrated fairness) tends to be more preferred than the others, and the results also provide support for the principle of affirmative action.Comment: To appear at AI Ethics and Society (AIES) 201

Avaliação do equilíbrio na doença de Alzheimer leve e moderada: implicações na capacidade funcional e na ocorrência de quedas

OBJECTIVE: To analyze the correlation between balance, falls and loss of functional capacity in mild and moderate Alzheimer's disease(AD). METHOD: 40 subjects without cognitive impairment (control group) and 48 AD patients (25 mild, 23 moderate) were evaluated with the Berg Balance Scale (BBS) and the Disability Assessment for Dementia (DAD). Subjects answered a questionnaire about falls occurrence in the last twelve months. RESULTS: Moderate AD patients showed poorer balance (p=0.001) and functional capacity (p <0.0001) and it was observed a correlation between falls and balance (r= -0.613; p=0.045). CONCLUSION: There is a decline of balance related to AD which is a factor associated to the occurrence of falls, albeit not the most relevant one. The loss of functional capacity is associated with the disease's progress but not to a higher occurrence of falls. The balance impairment did not correlate with functional decline in AD patients.OBJETIVO: Analisar a correlação entre déficit de equilíbrio, ocorrência de quedas e prejuízo funcional na doença de Alzheimer (DA). MÉTODO: 40 idosos sem comprometimento cognitivo (grupo controle) e 48 idosos com DA (25 leves e 23 moderados), avaliados através da Escala de Equilíbrio de Berg (EEB) e Escala de Avaliação de Incapacidade (EAI), e questionados quanto à ocorrência de quedas nos últimos doze meses. RESULTADOS: O equilíbrio no grupo DA moderada foi pior do que no grupo leve (p=0,001), bem como a capacidade funcional (p<0,0001), sem diferença na ocorrência de quedas entre os grupos. Na DA moderada, houve correlação entre ocorrência de quedas e EEB (r= -0,613; p=0,045). CONCLUSÃO: Há um declínio do equilíbrio associado à progressão da DA. O declínio da capacidade funcional não foi associado à maior ocorrência de quedas. O déficit de equilíbrio não se correlacionou ao declínio funcional na DA