Miracle-dz/UniFAR-FTUs huggingface dataset:
Arx: An Encrypted Database using Semantically Secure Encryption

In recent years, encrypted databases have emerged as a promising direction that provides data confidentiality without sacrificing functionality: queries are executed on encrypted data. However, many practical proposals rely on a set of weak encryption schemes that have been shown to leak sensitive data. In this paper, we propose Arx, a practical and functionally rich database system that encrypts the data only with semantically secure encryption schemes. We show that Arx supports real applications such as ShareLaTeX with a modest performance overhead.
CENTRAL BANK STRATEGY, CREDIBILITY, AND INDEPENDANCE: THEORY AND EVIDENCE

Alex Cukierman is well known for his work on central bank behavior. This book brings together a large body of Cukierman's research and integrates it with recent developments in the political economy of monetary policy. Filled with applications and carefully worked out technical detail, it provides a valuable comprehensive analysis of central bank decisions, of the various effects of policy on inflation, and of the feedback from inflationary expectations to policy choices. Cukierman uncovers and analyzes the reasons for positive inflation and rates of monetary expansion. He shows that the money supply, and therefore inflation, are not exogenous. They are influenced by interactions involving distributional considerations, private information, personal motives, and the political environment. This point of view makes it possible to identify the institutional, political, and other features of a country that may be conducive to inflationary environments. Cukierman presents new multidimensional evidence on both legal and actual central bank independence for a sample of up to 70 countries and uses it to investigate the interconnections between the distributions of inflation and of central bank independence. He takes up such issues as why some countries have more independent central banks than others and identifies reasons for the substantial cross country variation in seigniorage. He provides positive explanations for the tendency of central banks, like the US Federal Reserve, to smooth interest rates and to be secretive. Observing that it is likely that the European Economic Community will have a monetary union before the turn of the century, Cukierman applies the techniques of modern political economy to discuss the effect of this change on the commitment to price stability. The book includes simple and advanced materials as well as informal summaries of the major technical results. The introduction contains a modular guide for reading and teaching the material.
SystemER: A Human-in-the-loop System for Explainable Entity Resolution

Entity Resolution (ER) is the task of identifying diﬀerent representations of the same real-world object. To achieve scalability and the desired level of quality, the typical ER pipeline includes multiple steps that may involve low-level coding and extensive human labor. We present SystemER , a tool for learning explainable ER models that reduces the human labor all throughout the stages of the ER pipeline. SystemER achieves explainability by learning rules that not only perform a given ER task but are human-comprehensible; this provides transparency into the learning process, and further enables veriﬁcation and customization of the learned model by the domain experts. By leveraging a human in the loop and active learning, SystemER also ensures that a small number of labeled examples is suﬃcient to learn high-quality ER models. SystemER is a full-ﬂedged tool that includes an easy to use interface, support for both ﬂat ﬁles and semi-structured data, and scale-out capabilities by distributing computation via Apache Spark
Relationships between Oculo-Motor Mesures as Task-evoked Mental Workloads During an Manipulation Task

The frequency of microsaccades is often used as a measurement of eye movement in order to estimate the level of a cognitive mental workload during an experimental task. When the experiment includes several levels of manipulation tasks, ocular information including microsaccades, saccades and pupil diameters can be measured and compared. The results show that the microsaccade rate reflects a participant’s subjective impressions. In addition to measurements of oculomotors, microsaccade rates also reflect the level of effort required by a mental workload, and the mutual relationships between these rates are analyzed using causal analysis.
Gaussian process modelling of granulation and oscillations in red giant stars

The analysis of photometric time series in the context of transiting planet surveys suffers from the presence of stellar signals, often dubbed ‘stellar noise’. These signals, caused by stellar oscillations and granulation, can usually be disregarded for main-sequence stars, as the stellar contributions average out when phase-folding the light curve. For evolved stars, however, the amplitudes of such signals are larger and the timescales similar to the transit duration of short-period planets, requiring that they be modelled alongside the transit. With the promise of TESS delivering of the order of ∼105 light curves for stars along the red giant branch, there is a need for a method capable of describing the ‘stellar noise’ while simultaneously modelling an exoplanet’s transit. In this work, a Gaussian process regression framework is used to model stellar light curves and the method validated by applying it to TESS-like artificial data. Furthermore, the method is used to characterize the stellar oscillations and granulation of a sample of well-studied Kepler low-luminosity red giant branch stars. The parameters determined are compared to equivalent ones obtained by modelling the power spectrum of the light curve. Results show that the method presented is capable of describing the stellar signals in the time domain and can also return an accurate and precise measurement of νmax, i.e. the frequency of maximum oscillation amplitude. Preliminary results show that using the method in transit modelling improves the precision and accuracy of the ratio between the planetary and stellar radius, Rp/R⋆. The method’s implementation is publicly available.1
Neutrino halo effect on collective neutrino oscillation in iron core-collapse supernova model of a 9.6 M⊙ star

We extend the multi-angle computational framework and investigate the time evolution of the neutrino halo on collective neutrino oscillation in the core collapse of an iron core progenitor. We find that in the case of the 9.6 M⊙ progenitor adopted in this work, there are windows of time {when} the effects of neutrino halo and collective neutrino oscillation {are not simultaneously large}. Inside the shock, the impact of {the} inward-scattered {halo neutrino} cannot in general be neglected compared to the outward-propagating neutrino flux. However, during early epochs, collective neutrino oscillation is effectively shut down by multi-angle matter suppression. During the intermediate epoch, collective neutrino oscillation is {not} suppressed, but {its} onset radius is beyond the still relatively small explosion shock front where the halo is prominent. We also find {in the case of the 9.6 M⊙ progenitor} the halo neutrinos induce a delay {in} the onset of collective neutrino oscillations. This causes novel flavor conversions which sharpen collective neutrino oscillation spectral features. We predict that the inclusion of neutrino halo effects makes neutrino signals that are more clearly distinct from thermal emission that when halo neutrinos are omitted.
Comparison of Visualization Tools for Matches Analysis of a MOBA Game

The phenomenon of eSports has been increasing over the years, including the interest in online video games, by players, coaches and analysts. One of the most popular genres of these games is the Multiplayer Online Battle Arena (MOBA) and games like League of Legend (LoL) have increased its player base and event viewership. Similarly to other sports, players and coaches analyze the games and all the games events, such as players’ movements and spatial, temporal events in which they participate, to understand how they play and to define new strategies to help them progress. This paper presents the VisuaLeague II tool that helps players and coaches to analyze LoL game data using animated maps and other visualizations; and presents a comparative study between VisuaLeague II and other two tools (LoL replay system and OP.GG) to understand if the proposed visualization techniques are adequate for analyzing player’s performance. The results suggest that players are capable of visualizing game-related data through the use of animated maps, to solve common analytic tasks and the comparison suggests that participants prefer to visualize spatio-temporal data dynamically, i.e., using animated maps or the replay system.
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual

Statistical natural language inference (NLI) models are susceptible to learning dataset bias: superficial cues that happen to associate with the label on a particular dataset, but are not useful in general, e.g., negation words indicate contradiction. As exposed by several recent challenge datasets, these models perform poorly when such association is absent, e.g., predicting that “I love dogs. ” contradicts “I don’t love cats. ”. Our goal is to design learning algorithms that guard against known dataset bias. We formalize the concept of dataset bias under the framework of distribution shift and present a simple debiasing algorithm based on residual fitting, which we call DRiFt. We first learn a biased model that only uses features that are known to relate to dataset bias. Then, we train a debiased model that fits to the residual of the biased model, focusing on examples that cannot be predicted well by biased features only. We use DRiFt to train three high-performing NLI models on two benchmark datasets, SNLI and MNLI. Our debiased models achieve significant gains over baseline models on two challenge test sets, while maintaining reasonable performance on the original test sets.
Sampling strategies for species with high breeding-site fidelity: A case study in burrow-nesting seabirds

Sampling approaches used to census and monitor populations of flora and fauna are diverse, ranging from simple random sampling to complex hierarchal stratified designs. Usually the approach taken is determined by the spatial and temporal distribution of the study population, along with other characteristics of the focal species. Long-term monitoring programs used to assess seabird population trends are facilitated by their high site fidelity, but are often hampered by large and difficult to access colonies, with highly variable densities that require intensive survey. We aimed to determine the sampling effort required to (a) estimate population size with a high degree of confidence, and (b) detect different scenarios of population change in a regionally important species in the Atlantic, the Manx shearwater (Puffinus puffinus). Analyses were carried out using data collected from tape-playback surveys on four islands in the North Atlantic. To explore how sampling effort influenced confidence around abundance estimates, we used the heuristic approach of imagining the areas sampled represented the total population, and bootstrapped varying proportions of subsamples. This revealed that abundance estimates vary dramatically when less than half of all plots (n dependent on the size of the site) is randomly subsampled, leading to an unacceptable lack of confidence in population estimates. Confidence is substantially improved using a multi-stage stratified approach based on previous information on distribution in the colonies. In reality, this could lead to reducing the number of plots required by up to 80%. Furthermore, power analyses suggested that random selection of monitoring plots using a matched pairs approach generates little power to detect overall population changes of 10%, and density-dependent changes as large as 50%, because variation in density between plots is so high. Current monitoring programs have a high probability of failing to detect population-level changes due to inappropriate sampling efforts. Focusing sampling in areas of high density with low plot to plot variance dramatically increases the power to detect year to year population change, albeit at the risk of not detecting increases in low density areas, which may be an unavoidable strategy when resources are limited. We discuss how challenging populations with similar features to seabirds might be censused and monitored most effectively.
GRIEF EXPERIENCE PATTERNS AMONG OLDER ADULTS IN RURAL CHINA: A LATENT PROFILE ANALYSIS

The present work sought to explore grief patterns among Chinese older people in rural areas as well as the factors influencing the diverse bereavement results. Participants were 352 older residents who lived in rural areas in China. Latent profile analysis was used to identify subtypes of class membership in combing complicated grief, depression, anxiety, and meaning in life. One-way analysis of variance, chi-square analysis, and multinomial regression analysis were performed together to examine the predictor best distinguishing between classes. The latent profile analysis model best fitting the data was a three-class solution comprised of adaptive (n = 235; 66.8%), moderate maladaptive (n = 83; 23.6%), and severe maladaptive groups (n = 34; 9.7%). Compared to the severe maladaptive and moderate maladaptive groups, participants in the adaptive group had better physical functioning. Participants in the moderate maladaptive group had longer bereavement duration than those in the severe maladaptive group. Future replication is desirable for validating these subgroups.
Low triiodothyronine syndrome is associated with hemorrhagic transformation in patients with acute ischaemic stroke

Hemorrhagic transformation (HT) is a severe complication occurring in acute ischemic stroke (AIS) patients. We explored the association between low triiodothyronine (T3) syndrome and HT in AIS patients. A total of 208 consecutive participants with HT and 208 age- and sex-matched stroke patients without HT were enrolled in this study. HT was diagnosed by follow-up imaging assessment, and was radiologically classified as hemorrhagic infarction (HI) type 1 or 2 or parenchymal hematoma (PH) type 1 or 2. HT was also classified into asymptomatic or symptomatic. The incidence of low T3 syndrome was significantly higher among patients who developed HT than among those without HT. Moreover, the more severe the HT, the lower the detected T3 levels. Multivariate-adjusted binary logistic regression showed that low T3 syndrome was an independent risk factor for HT and symptomatic HT in AIS patients. Low T3 syndrome was also significantly associated with a higher risk of PH, but not with the risk of HI. Thus, low T3 syndrome was independently associated with the risk of HT, symptomatic HT, and severe HT (PH) in AIS patients, which suggests monitoring T3 could be a useful means of preventing HT in patients with ischemic stroke.
Application of details management in airway management of patients in the neurological intensive care unit

Objective: To investigate the application effect of details management method on airway management of patients receiving neurological intensive care. Methods: A total of 180 patients in the neurological intensive care unit (NICU) of Liaocheng People’s Hospital receiving tracheal intubation from March 2015 to January 2017 were selected as objects of study, and randomly divided into two groups, with 90 cases in each group. The conventional airway management method was adopted in the control group, while the details management method was incorporated in the observation group based on the conventional method. The intubation time, length of stay in NICU, hospitalization expense, incidence rate of abnormal blood pressure, aspiration rate of sputum scab in the airway, positive rate of sputum culture, Glasgow coma scale (GCS) score, incidence rates of adverse reactions, final clinical outcome, and nursing satisfaction rate were compared and analyzed between the two groups. Results: The intubation time and length of stay in NICU in the observation group were significantly shorter than those in the control group, and differences were statistically significant (both P < 0.05). The average hospitalization expense in the observation group was significantly lower than that in the control group, and the difference was statistically significant (P < 0.05). In the observation group, there were 13 cases (14.44%) of positive sputum culture, 4 cases (4.44%) of respiratory tract infection, 3 cases (3.33%) of pulmonary infection, 7 cases (7.78%) of aspiration of sputum scab, and 32 cases (35.56%) of abnormal blood pressure, and differences were statistically significant (all P < 0.05). There was no statistically significant difference in the GCS score between the two groups of patients before operation, while the GCS score in the observation group after operation was significantly higher than that in the control group, and the difference was statistically significant (P < 0.05). The incidence rates of adverse reactions in the observation group were obviously lower than those in the control group, and differences were statistically significant (P < 0.05). The mortality rate in the observation group (n=2, 2.22%) was lower than that in the control group (n=12, 13.33%). The nursing satisfaction rate in the observation group was higher than that in the control group, and the difference was statistically significant (P < 0.05). Conclusion: Incorporating details management in airway management of patients receiving neurological intensive care based on conventional nursing can significantly shorten the intubation time and reduce the incidence rate of complications and mortality rate of patients, which is conducive to the rehabilitation of patients and able to improve nursing effectiveness and satisfaction, so it is worth popularizing.
Modeling median will-cost estimates for defense acquisition programs

Purpose The introduction of “should cost” in 2011 required all Major Defense Acquisition Programs (MDAP) to create efficiencies and improvements to reduce a program’s “will-cost” estimate. Realistic “will-cost” estimates are a necessary condition for the “should cost” analysis to be effectively implemented. Owing to the inherent difficulties in establishing a program’s will-cost estimate, this paper aims to propose a new model to infuse realism into this estimate. Design/methodology/approach Using historical data from 73 Departments of Defense programs as recorded in the selected acquisition reports (SARs), the analysis uses mixed stepwise regression to predict a program’s cost from Milestone B (MS B) to initial operational capability (IOC). Findings The presented model explains 83 per cent of the variation in the program acquisition cost. Significant predictor variables include: projected duration (months from MS B to IOC); the amount of research development test and evaluation (RDTE whether the program is considered a fixed-wing aircraft; whether a program is considered an electronic system program; whether a program is considered ACAT I at MS B; and the program size relative to the total program’s projected acquisition costs at MS B. Originality/value The model supports the “will-cost and should-cost” requirement levied in 2011 by providing an objective and defensible cost for what a program should actually cost based on what has been achieved in the past. A quality will-cost estimate provides a starting point for program managers to examine processes and find efficiencies that lead to reduced program costs.
DDDT_A_200147 2491..2502

*These authors contributed equally to this work Abstract: Psoriasis is a chronic immune-mediated skin disease affecting multiple systems, and tumor necrosis factor-α (TNF-α) plays a significant role in the initiation and progression of the disease process. Psoriasis has a high prevalence rate in the Western world, especially in the USA and Australia; in China, although the prevalence rate is much lower, there is still a large number of patients suffering from psoriasis and its comorbidities. As TNF-α is thought to be crucial in the pathogenesis of psoriasis, specific therapy blocking TNF-α may be beneficial in the treatment of this disease. Infliximab, a murine–human monoclonal antibody, is highly efficacious in the treatment of moderate-to-severe psoriasis, with better skin clearance and faster onset of action than topical medications such as methotrexate, narrow-band ultraviolet B, and calcipotriol. Lack of adherence to infliximab therapy is mainly due to loss of response (LOR) over time and adverse events, particularly because infusion reactions are usually encountered. Anti-infliximab antibody is thought to be responsible for the LOR and infusion reactions. However, the mechanism underlying the formation of anti-infliximab antibody and its side effects remains unclear. Further studies identifying patients at risk for LOR will probably help clinicians to select the right patients for anti-TNFα therapy and to increase the durability of the treatment. This review discusses the efficacy of infliximab as demonstrated by various clinical trials, LOR to infliximab, combatting LOR, as well as the adverse events usually faced during the use of infliximab therapy and the infliximab biosimilar Remsima. We hope that we can discover a better way to use infliximab in the therapy of psoriasis from the current research data.
Stable isotopes are quantitative indicators of trophic niche

Abstract Hette‐Tronquart (2019, Ecol. Lett.) raises three concerns about our interpretation of stable isotope data in Sheppard et al. (2018, Ecol. Lett., 21, 665). We feel that these concerns are based on comparisons that are unreasonable or ignore the ecological context from which the data were collected. Stable isotope ratios provide a quantitative indication of, rather than being exactly equivalent to, trophic niche.
The association between neighborhood social cohesion and sleep duration in Latinos

ABSTRACT Objectives To examine the association between neighborhood social cohesion and sleep duration among Latinos, and whether this association varies by Latino subgroup. Design We used cross-sectional data from the 2013–2015 National Health Interview Survey (NHIS) on 13,537 Latino adults aged ≥18 years originating from 5 countries/regions (i.e. Latinos of Mexican/Mexican-American, Puerto Rican, Dominican, Central or South American, and Cuban/Cuban-American origin). Multivariate logistic regression models were used to estimate the associations between neighborhood social cohesion and sleep duration, and whether associations varied by Latino subgroup. Results Among Mexicans/Mexican-Americans, medium and high levels of neighborhood social cohesion were associated with normal sleep duration, relative to short sleep duration (Odds Ratio [OR]: 1.31; 95% Confidence Interval [CI]: 1.08–1.57, and OR: 1.46; 95% CI: 1.26–1.69, respectively). Among Puerto Ricans, Cubans/Cuban Americans, and Central or South Americans, high neighborhood social cohesion was significantly associated with normal sleep duration (OR: 1.53; 95% Confidence Interval [CI]: 1.10–2.11, OR: 1.94; 95% CI: 1.10–3.42, and OR: 1.78; 95% CI: 1.35–2.34, respectively). Conclusions The variation in the contribution of neighborhood social cohesion to sleep duration by Latino subgroup should be considered in health promotion programs aimed at improving sleep among Latinos.