Miracle-dz/UniFAR-FTUs huggingface dataset:
Never ever or no matter what: Investigating Adoption Intentions and Misconceptions about the Corona-Warn-App in Germany

To help tackle the COVID-19 pandemic, the tech community has put forward proximity detection apps to help warn people who might have been exposed to the coronavirus. The privacy implications of such apps have been discussed both in academic circles and the general population. The discussion in Germany focused on the trade-off between a centralized or decentralized approach for data collection and processing and their implications. Specifically, privacy dominated the public debate about the proposed “Corona-Warn-App. ” This paper presents a study with a quota sample of the German population (n = 744) to assess what the population knew about the soon-to-be-released app and their willingness to use it. We also presented participants potential properties the app could have and asked them how these would affect their usage intention. Based on our findings, we discuss our participants' views on privacy and functionality, including their perception of selected centralized and decentralized features. We also examine a wide range of false beliefs and information that was not communicated successfully. Especially technical details, such as that the app would use Bluetooth, as opposed to location services, were unknown to many participants. Our results give insights on the complicated relationship of trust in the government and public communication on the population's willingness to adopt the app. © is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee.
Towards Designing Cost-Optimal Policies to Utilize IaaS Clouds under Online Learning

Many businesses possess a small infrastructure that they can use for their computing tasks, but also often buy extra computing resources from clouds. Cloud vendors such as Amazon EC2 offer two types of purchase options: on-demand and spot instances. As tenants have limited budgets to satisfy their computing needs, it is crucial for them to determine how to purchase different options and utilize them (in addition to possible self-owned instances) in a cost-effective manner while respecting their response-time targets. In this paper, we propose a framework to design policies to allocate self-owned, on-demand and spot instances to arriving jobs. In particular, we propose a near-optimal policy to determine the number of self-owned instance and an optimal policy to determine the number of on-demand instances to buy and the number of spot instances to bid for at each time unit. Our policies rely on a small number of parameters and we use an online learning technique to infer their optimal values. Through numerical simulations, we show the effectiveness of our proposed policies, in particular that they achieve a cost reduction of up to 64.51% when spot and on-demand instances are considered and of up to 43.74% when self-owned instances are considered, compared to previously proposed or intuitive policies.
JOURNAL FOR INNOVATIVE DEVELOPMENT IN PHARMACeutical AND technical SCIENCE

Mobile Discovery program provides a low-cost approach to explore chemical diversity of local ecosystems and discover its potential to improve human health. Its combination with a carrier hemp oil that contains a near optimal ratio of linoleic and linolenic acids working together to promote healthy metabolism and migration of skin cells in to the scratch wound area, created a novel botanical intervention that can be tested in preclinical and clinical models to improve wound care and management of immune skin disorders. Preclinical testing in skin and macrophage cell cultures showed high regenerative potential of spotted wintergreen preparations. When combined with hemp oil (Cannabis sativa L., Cannabaceae) as a carrier botanical oil and a distinctive source of essential polyunsaturated fatty acids critical to support skin function and β-oxidation, spotted wintergreen lipid fraction promoted migration and scratch wound closure in cell culture. Based on this data, we proposed botanical-infused hemp oils as a novel group of topical skin care formulations potentially effective at alleviating cutaneous infections and disorders associated with abnormal skin regeneration.
Shared Memory on Standard Workstations and Operating Systems

TreadMarks is a distributed shared memory (DSM) system for standard Unix systems such as SunOS and Ultrix. This paper presents a performance evaluation of TreadMarks running on Ultrix using DECstation-5000/240's that are connected by a 100-Mbps switch-based ATM LAN and a 10-Mbps Ethernet. Our objective is to determine the e ciency of a user-level DSM implementation on commercially available workstations and operating systems. We achieved good speedups on the 8-processor ATM network for Jacobi (7.4), TSP (7.2), Quicksort (6.3), and ILINK (5.7). For a slightlymodi ed version of Water from the SPLASH benchmark suite, we achieved only moderate speedups (4.0) due to the high communication and synchronization rate. Speedups decline on the 10-Mbps Ethernet (5.5 for Jacobi, 6.5 for TSP, 4.2 for Quicksort, 5.1 for ILINK, and 2.1 for Water), re ecting the bandwidth limitations of the Ethernet. These results support the contention that, with suitable networking technology, DSM is a viable technique for parallel computation on clusters of workstations. To achieve these speedups, TreadMarks goes to great lengths to reduce the amount of communication performed to maintain memory consistency. It uses a lazy implementation of release consistency, and it allows multiple concurrent writers to modify a page, reducing the impact of false sharing. Great care was taken to minimize communication overhead. In particular, on the ATM network, we used a standard low-level protocol, AAL3/4, bypassing the TCP/IP protocol stack. Unix communication overhead, however, remains the main obstacle in the way of better performance for programs like Water. Compared to the Unix communication overhead, memory management cost (both kernel and user level) is small and wire time is negligible.
Loyola eCommons Loyola eCommons

The use of strong passwords is viewed as a recommended cybersecurity practice, as the hacking of weak pass-words led to major cybersecurity breaches. The present research investigated whether nudging with messages based on participants ’ self-schemas could lead them to create stronger passwords. We modeled our study on prior health-related research demonstrating positive results using messages based on self-schema categories (i.e., True Colors categories -compassionate, loyal, intellectual, and adventurous). We carried out an online study, one with 256 (185 women, 66 men, 5 other) undergraduates and one with 424 (240 men, 179 women, 5 other) Amazon Mechanical Turk (MTurk) workers, in which we randomly assigned participants to receive messages that matched or mismatched their self-schema. We also investigated whether differences across the Big Five personality traits, secure password knowledge, attitudes and behavior, need for cognition, and general risk-taking predicted the strength of passwords that participants created during the study. Multiple individual difference variables predicted password strength (i.e., conscientiousness, emotional stability, need for cognition, self-reported secure password knowledge, attitude, and behavior, and general risk-taking). MTurk workers had higher levels of cybersecurity knowledge and created stronger passwords than college students. The nudging messages did not lead to stronger passwords. Implications for strategies to increase the use of secure passwords are discussed.
Spectral Matting

We present spectral matting: a new approach to natural image matting that automatically computes a basis set of fuzzy matting components from the smallest eigenvectors of a suitably defined Laplacian matrix. Thus, our approach extends spectral segmentation techniques, whose goal is to extract hard segments, to the extraction of soft matting components. These components may then be used as building blocks to easily construct semantically meaningful foreground mattes, either in an unsupervised fashion, or based on a small amount of user input.
Can macroeconomic volatility affect stock market volatility ? The case of 5 central and eastern European countries

This paper examines whether macroeconomic instability can influence stock market volatility in a sample of 5 emerging European countries. To account for the effects of fundamentals, modified ARCH/GARCH models are employed. The results are discordant from one country to another, but when a dynamic panel GMM is estimated, exchange rate volatility is found to be the sole significant explanatory variable.
The relative age effect in soccer: a case study of the São Paulo Football Club

The aim of this study was to compare the birth-date distribution of youth athletes of a high-level Brazilian soccer club with the general population of the same age group. In a cross-sectional study, the birth date of 341 youth athletes (under 10-20) was compared with a reference population (live births that occurred in Sao Paulo state in the same age group; n = 5,480,868). The subjects were divided into quarters of birth: 1st = January-March; 2nd = April-June; 3rd = July-September; 4th = October-December. The chi-square test (χ2) was used to compare the expected (reference population) and observed (athletes) distributions. It was detected a significant difference between the expected distribution and observed distribution (χ2= 29.53; p<0.0001), with a higher percentage of athletes born in the 1st quarter (47.5%) and a lower percentage in the 4th quarter (8.8%). The present results confirm the occurrence of the relative age effect (RAE) during the player selection process in a top-level Brazilian soccer club. The occurrence of this phenomenon during the selection and development of young athletes needs to be taken into account and should be analyzed carefully in order to minimize the loss of potential youth soccer talent. Further studies are required to identify the determinants of RAE and to establish preventive strategies that ensure a more efficient selection process of young soccer players.
Optimal Heart Failure Medical Therapy and Mortality in Survivors of Cardiogenic Shock: Insights From the FRENSHOCK Registry

Background The effects of pharmacological therapy on cardiogenic shock (CS) survivors have not been extensively studied. Thus, this study investigated the association between guideline‐directed heart failure (HF) medical therapy (GDMT) and one‐year survival rate in patients who are post‐CS. Methods and Results FRENSHOCK (French Observatory on the Management of Cardiogenic Shock in 2016) registry was a prospective multicenter observational survey, conducted in metropolitan French intensive care units and intensive cardiac care units. Of 772 patients, 535 patients were enrolled in the present analysis following the exclusion of 217 in‐hospital deaths and 20 patients with missing medical records. Patients with triple GDMT (beta‐blockers, renin‐angiotensin system inhibitors, and mineralocorticoid receptor antagonists) at discharge (n=112) were likely to have lower left ventricular ejection fraction on admission and at discharge compared with those without triple GDMT (n=423) (22% versus 28%, P<0.001 and 29% versus 37%, P<0.001, respectively). In the overall cohort, the one‐year mortality rate was 23%. Triple GDMT prescription was significantly associated with a lower one‐year all‐cause mortality compared with non‐triple GDMT (adjusted hazard ratio 0.44 [95% CI, 0.19–0.80]; P=0.007). Similarly, 2:1 propensity score matching and inverse probability treatment weighting based on the propensity score demonstrated a lower incidence of one‐year mortality in the triple GDMT group. As the number of HF drugs increased, a stepwise decrease in mortality was observed (log rank; P<0.001). Conclusions In survivors of CS, the one‐year mortality rate was significantly lower in those with triple GDMT. Therefore, this study suggests that intensive HF therapy should be considered in patients following CS.
Risk Factors for Early Implant Failure and Selection of Bone Grafting Materials for Various Bone Augmentation Procedures: A Narrative Review

Implant therapy is now an established treatment with high long-term success and survival rates. However, early implant failure, which occurs within one year of superstructure placement, occurs at a higher rate than late failure, which is represented by peri-implantitis caused by bacterial infection. Furthermore, various risk factors for early failure have been reported, including patient-related factors, such as systemic diseases, smoking, and bone quality and quantity, as well as surgery-related factors, such as surgeons’ skill, osteogenesis technique, and selection of graft material, and implant-related factors, such as initial implant fixation and implant length diameter. Due to the wide variety of relevant factors reported, it is difficult to identify the cause of the problem. The purpose of this review is to discuss the risk factors associated with various types of bone augmentation which have a close causal relationship with early implant failure, and to determine the optimal bone grafting material for bone augmentation procedures to avoid early implant failure.
Proceedings of the 21st Annual Conference of the European Association for Machine Translation

Automatic machine translation evaluation was crucial for the rapid development of machine translation systems over the last two decades. So far, most attention has been paid to the evaluation metrics that work with text on the sentence level and so did the translation systems. Acrosssentence translation quality depends on discourse phenomena that may not manifest at all when staying within sentence boundaries (e.g. coreference, discourse connectives, verb tense sequence etc.). To tackle this, we propose several documentlevel MT evaluation metrics: generalizations of sentence-level metrics, language(pair)-independent versions of lexical cohesion scores and coreference and morphology preservation in the target texts. We measure their agreement with human judgment on a newly created dataset of pairwise paragraph comparisons for four language pairs.
The role of remittances in the stability of money demand in Pakistan: A cointegration analysis

The paper examines the dynamic relationship between the series of monetary aggregates M1 and M2 for the period 1972–2014. M1 and M2 are the dependent variables, while the explanatory variables are real income, discount rate, inflation rate, real exchange rate, and remittances. The ARDL bounds testing approach to cointegration is used to investigate the existence of long-run and short-run effects of remittances on monetary aggregates. The results show that remittances exert only positive effects on real narrow money demand in the end, suggesting that in Pakistan remittances are used for the purpose of consumption. Both money demand functions are stable in Pakistan, but the longrun effect of M1 remittances is a faster speed of adjustment to equilibrium (26.2%) than M2 remittances (21.3%). It is recommended that M1 be used as a monetary tool in Pakistan.
0 A ug 2 01 3 Discrepancy and numerical integration in Sobolev spaces on metric measure spaces

Abstract. We study the error for quasi Monte Carlo quadrature rules on metric measure spaces adapted to a decomposition of the space into disjoint subsets. We consider both the error for a single given function, and the worst case error for all functions in a given class of potentials. The main tools are the classical Kintchine-Marcinkiewicz-Zygmund inequality and more recent suitable definitions of Sobolev classes on metric measure spaces.
Supporting Polyrepresentation in a Quantum-inspired Geometrical Retrieval Framework

The relevance of a document has many facets, going beyond the usual topical one, which have to be considered to satisfy a user’s information need. Multiple representations of documents, like user-given reviews or the actual document content, can give evidence towards certain facets of relevance. In this respect polyrepresentation of documents, where such evidence is combined, is a crucial concept to estimate the relevance of a document. In this paper, we discuss how a geometrical retrieval framework inspired by quantum mechanics can be extended to support polyrepresentation. We show by example how different representations of a document can be modelled in a Hilbert space, similar to physical systems known from quantum mechanics. We further illustrate how these representations are combined by means of the tensor product to support polyrepresentation, and discuss the case that representations of documents are not independent from a user point of view. Besides giving a principled framework for polyrepresentation, the potential of this approach is to capture and formalise the complex interdependent relationships that the different representations can have between each other.
The Role of Gaming During Dificult Life Experiences

HCI has become increasingly interested in the use of technology during diicult life experiences. Yet despite considerable popularity, little is known about how and why people engage with games in times of personal diiculty. Based on a qualitative analysis of an online survey (N=95), our ind-ings indicate that games ofered players much needed respite from stress, supported them in dealing with their feelings, facilitated social connections, stimulated personal change and growth, and provided a lifeline in times of existential doubt. However, despite an emphasis on gaming as being able to support coping in ways other activities did not, participants also referred to games as unproductive and as an obstacle to living well. We discuss these indings in relation to both coping process and outcome, while considering tensions around the potential beneits and perceived value of gaming.
Using X-Ray Form Factor , Attenuation and Scattering ( FFAST ) Database to Calculate the Linear and Mass Attenuation Coefficients

The aim of this study was to evaluate the physical proprieties of epoxy resin to be used as a phantom material to mimic the liver of human body in computed tomography (CT) protocols. The epoxy resin type of E110I/H-9 was mixed uniformly with a ratio 2:1 of resin and hardener. The mass density, effective atomic number, linear and mass attenuation coefficients of the epoxy were calculated. The linear and mass attenuation coefficients were measured theoretically at relevant CT photon energy 40-65keV using the FFAST database (NIST, USA). Then, the calculated measurements of fabricated epoxy were compared with the standard values of human liver. The results indicated that the mass density and effective atomic number had achieved good agreement with the liver values. The theoretical values of linear and mass attenuation coefficients were in strong agreement with the values reported in International Commission on Radiation Units and Measurements (ICRU, Report 44). Therefore, the results physically verify the suitability of epoxy resin E-110I/H-9 as a CT phantom material to mimic the human liver.
Analysis of Emerging Barriers for e-Learning Models: An Empirical Study

The diffusion of the e-learning model during the last decade has contributed to solve many problems concerned with education at the workplace. Technological progress has significantly contributed to eliminating most limitations of the traditional education model, through improved access, diffusion of information, and the adaptation to individual needs. However, e-learning is an instrument, which does not ensure the automatic achievement of intended goals. Some studies have demonstrated that the mere conversion of course materials into an e-learning course may reduce motivation and thus, the level of effective learning. In addition, appropriate design of course materials for e-learning programs might not be sufficient to achieve optimal results. In order to maximize the benefits of implementing an e-learning program, it is if fact necessary to take into account organizational issues, such as the existence of incentives, the distribution of time for learning at the workplace, or the management system being used, for example. This paper analyzes some organizational features, which are linked to learning in organizations and might help to better explain success of an e-learning program. In particular, we attempt to assess the impact of both incentives and the assignment of a specific period of time for education to personal satisfaction and the level of learning. To this end, we proposed a specific survey to users of e-learning courses at a consulting company, which includes questions about satisfaction, self-assessed learning and monetary or long-term (career) incentives, among others. The impact of different organizational characteristics on satisfaction and learning has been then estimated by a bivariate ordered probit model, which allows for considering both the nature of dependent variables and the possible correlation between equations. The analysis sheds light on key practical organizational features, which should be taken into account in order to improving results of e-learning programs The main goal of this analysis has been to provide evidences to support policies aimed to increase effectiveness of e-learning models. We have based on the e-learning experience of a consulting company, evaluating the effectiveness of this new model in terms of two variables: learning perceived and level of satisfaction of participants. In order to analyze the determinants of both learning and satisfaction, we collected data from participants of e-learning programs. We found out that self-assessed satisfaction and perceived learning are likely to be affected by the same set of variables. On considering these relationships, and the nature of available data, both a simultaneous bivariate ordered probit model and a simultaneous bivariate probit model have been used in order to assess the impact of different factors on both satisfaction and perceived learning.
Adinkra Graphs 2 . 1 Graph-theoretic Notation

Adinkras are a graphical tool for studying off-shell representations of supersymmetry. In this paper we efficiently classify the automorphism groups of Adinkras relative to a set of local parameters. Using this, we classify Adinkras according to their equivalence and isomorphism classes. We extend previous results dealing with characterization of Adinkra degeneracy via matrix products, and present algorithms for calculating the automorphism groups of Adinkras and partitioning Adinkras into their isomorphism classes. brendan@physics.uwa. edu.au gatess@wam.umd. edu wang@physics.uwa. edu.au ar X iv :1 00 9. 14 49 v1 [ he pth ] 8 S ep 2 01 0