Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the Range of Chinese Mitten Crabs in Europe

Abstract: Ecological niche modeling provides a means for predicting the potential future distribution of a nonindigenous species based on environmental characteristics of the species' native range. We applied this method to the Chinese mitten crab (Eriocheir sinensis), a catadromous crustacean with a long history of invasion in Europe. We used genetic algorithm for rule‐set prediction to predict the potential European distribution of mitten crab based on its distribution in 42 locations in its native Asia. The climatic variables, air temperature, number of days, amount of precipitation, and wetness index, contributed significantly to predictions of native distribution limits. Although the genetic algorithm for rule‐set prediction model was developed for the native range, the species' extensive distribution in Europe (n =434) allowed independent validation of the predictions. Application of the model to Europe was successful, with 84% of occurrences in regions predicted to be suitable by >80% of the models and <4% of occurrences in areas predicted suitable by <50% of the models (mainly along the northern range). At the watershed scale, areas with established mitten crab populations had significantly higher habitat matching than sites that were not invaded. The independent validation of the Asian‐based model by the European distribution revealed that predictions were highly accurate. The model also identified large areas of Europe, particularly along the Mediterranean coast, as vulnerable to future invasion. These predictions can be used to develop strategies to control the spread of mitten crab by preventing introductions into vulnerable areas.
Ophthalmic lymphoma: epidemiology and pathogenesis

With a lifetime risk of 1% and 700 new cases per year, Non‐Hodgkin lymphoma (NHL) is the seventh most frequent type of cancer in Denmark. The incidence of NHL has increased considerably in Western countries over the last decades; consequently, NHL is an increasing clinical problem.
Cross-Polarization Modulation in Polarization-Division Multiplex Transmission

We show theoretically and with the aid of computer simulations that the nonlinear depolarization induced by cross-polarization modulation leads to crosstalk between the polarization-division multiplex (PolDM) subchannels during their demultiplexing. This additive crosstalk can be approximated as additive Gaussian noise, and we derive expressions to estimate its variance. It can lead to significant penalties of up to several decibels for PolDM transmission and must be properly accounted for. We also show why time-interleaving both subchannels can significantly reduce these penalties.
In vitro activity and mechanism of action of A21978C1, a novel cyclic lipopeptide antibiotic

The in vitro activity of A21978C1, a novel cyclic polypeptide antibiotic, was compared with those of vancomycin, teichomycin, and several beta-lactam antibiotics against gram-positive bacteria. The new drug was at least as active as vancomycin against all species of streptococci and staphylococci tested, including methicillin-resistant Staphylococcus aureus and penicillin-resistant pneumococci. Activity of the drug was found to be strongly correlated with the calcium concentration in test media. Against enterococci, A21978C1 was bactericidal at concentrations near the MIC (MIC for 100% of the strains, 2 micrograms/ml), but combining that drug with gentamicin resulted in bactericidal synergism by time-kill methods. Studies were undertaken to examine the mechanism of action of the drug. A21978C1 did not interact with penicillin-binding proteins of bacterial cell membranes. No direct effect of the drug on the synthesis of DNA, RNA, or protein by a susceptible strain of Streptococcus faecalis could be demonstrated. However, A21978C1 inhibited peptidoglycan synthesis in early-log-phase cultures of both Streptococcus faecalis and Staphylococcus aureus.
Acute hyperglycemia exacerbates myocardial ischemia/reperfusion injury and blunts cardioprotective effect of GIK.

There is a close association between hyperglycemia and increased risk of mortality after acute myocardial infarction (AMI). However, whether acute hyperglycemia exacerbates myocardial ischemia/reperfusion (MI/R) injury remains unclear. We observed the effects of acute hyperglycemia on MI/R injury and on the cardioprotective effect of glucose-insulin-potassium (GIK). Male rats were subjected to 30 min of myocardial ischemia and 6 h of reperfusion. Rats were randomly received one of the following treatments (at 4 ml.kg(-1). h(-1) iv): Vehicle, GIK (GIK during reperfusion; glucose: 200g/l, insulin: 60 U/l, KCL: 60 mmol/l), HG (high glucose during ischemia; glucose:500 g/l), GIK + HG (HG during I and GIK during R) or GIK + wortmannin (GIK during R and wortmannin 15 min before R). Blood glucose, plasma insulin concentration and left ventricular pressure (LVP) were monitored throughout the experiments. Hyperglycemia during ischemia not only significantly increased myocardial apoptosis (23.6 +/- 1.7% vs. 18.8 +/- 1.4%, P < 0.05 vs. vehicle), increased infarct size (IS) (45.6 +/- 3.0% vs. 37.6 +/- 2.0%, P < 0.05 vs. vehicle), decreased Akt and GSK-3beta phosphorylations (0.5 +/- 0.2 and 0.6 +/- 0.1% fold of vehicle, respectively, P < 0.05 vs. vehicle) following MI/R, but almost completely blocked the cardioprotective effect afforded by GIK, as evidenced by significantly increased apoptotic index (19.1 +/- 2.0 vs. 10.3 +/- 1.2%, P < 0.01 vs. GIK), increased myocardial IS (39.2 +/- 2.8 vs. 27.2 +/- 2.1%, P < 0.01 vs. GIK), decreased Akt phosphorylation (1.1 +/- 0.1 vs. 1.7 +/- 0.2%, P < 0.01 vs. GIK) and GSK-3beta phosphorylation (1.4 +/- 0.2 vs. 2.3 +/- 0.2%, P < 0.05 vs. GIK). Hyperglycemia significantly exacerbates MI/R injury and blocks the cardioprotective effect afforded by GIK, which is, at least in part, due to hyperglycemia-induced decrease of myocardial Akt activation.
Projected Subgradient Methods for Learning Sparse Gaussians

Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our approach uses the l1-norm as a regularization on the inverse covariance matrix. We utilize a novel projected gradient method, which is faster than previous methods in practice and equal to the best performing of these in asymptotic complexity. We also extend the l1-regularized objective to the problem of sparsifying entire blocks within the inverse covariance matrix. Our methods generalize fairly easily to this case, while other methods do not. We demonstrate that our extensions give better generalization performance on two real domains—biological network analysis and a 2D-shape modeling image task.
Early abandon to accelerate exact dynamic time warping

Dynamic time warping is one of the important distance measures in similarity search of time series; however, the exact calculation of dynamic time warping has become a bottleneck. We propose an approach, named early abandon dynamic time warping, to accelerate the calculation. The method checks if values of the neighbouring cells in the cumulative distance matrix exceed the tolerance, and if so, it will terminate the calculation of the related cell. We demonstrate the idea of early abandon on dynamic time warping by theoretical analysis, and show the utilities of early abandon dynamic time warping by thorough empirical experiments performed both on synthetic datasets and real datasets. The results show, early abandon dynamic time warping outperforms the dynamic time warping calculation in the light of processing time, and is much better when the tolerance is below the real dynamic time warping distance.
The Development of an MPA Major Field Test

This article describes the yearlong process of systematically developing an MPA Major Field Test with a team of five schools in various regions of the United States. Each school professor on the test team interviewed numerous practitioners to determine current issues in the profession. The practitioner information was filtered through at least one academic team member who used the information to create exam questions and submitted them for peer review. The test is based on NASPAA’s five competencies for the MPA degree. Four schools list the data gleaned from the test results and its impact on their MPA program. Though the data set is currently not large enough to determine validity or reliability, the article describes the process and the utility of the test to offer the first collaborative measurement for schools to determine the strength of their MPA program.
Asyrl?totically Nonparametric Seque~rrial Selection Proceduresi

which are stochastically ordered or tail ordered. ~ The ranking goal is to select the stochastically largest population or the population with the lightest tail. Sequential selection rules in the spirit of Robbins, Sobel, and Starr (lS68) and Geertsema (1972) are proposed and studied. The above problems are corollaries of a general TheoreM proposed, and the solutions are nonpararnetric in an asymptotic sense.
Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions

Many cities and countries are now striving to create intelligent transportation systems that utilize the current abundance of multisource and multiform data related to the functionality and the use of transportation infrastructure to better support human mobility, interests, and lifestyles. Such intelligent transportation systems aim to provide novel services that can enable transportation consumers and managers to be better informed and make safer and more efficient use of the infrastructure. However, the transportation domain is characterized by both complex data and complex problems, which calls for visual analytics approaches. The science of visual analytics is continuing to develop principles, methods, and tools to enable synergistic work between humans and computers through interactive visual interfaces. Such interfaces support the unique capabilities of humans (such as the flexible application of prior knowledge and experiences, creative thinking, and insight) and couple these abilities with machines’ computational strengths, enabling the generation of new knowledge from large and complex data. In this paper, we describe recent developments in visual analytics that are related to the study of movement and transportation systems and discuss how visual analytics can enable and improve the intelligent transportation systems of the future. We provide a survey of literature from the visual analytics domain and organize the survey with respect to the different types of transportation data, movement and its relationship to infrastructure and behavior, and modeling and planning. We conclude with lessons learned and future directions, including social transportation, recommender systems, and policy implications.
Type-II InAs/GaSb/AlSb superlattice-based heterojunction phototransistors: back to the future

Most of reported HPTs in literatures are based on InGaAs compounds that cover NIR spectral region. However, InGaAs compounds provide limited cut-off wavelength tunability. In contrast, type-II superlattices (T2SLs) are a developing new material system with intrinsic advantages such as great flexibility in bandgap engineering, low growth and manufacturing cost, high-uniformity, auger recombination suppression, and high carrier effective mass that are becoming an attractive candidate for infrared detection and imaging from short-wavelength infrared to very long wavelength infrared regime. We present the recent advancements in T2SL-based heterojunction phototransistors in e– SWIR, MWIR and LWIR spectral ranges. A mid-wavelength infrared heterojunction phototransistor based on type-II InAs/AlSb/GaSb superlattices on GaSb substrate has been demonstrated. Then, we present the effect of vertical scaling on the optical and electrical performance of heterojunction phototransistors, where the performance of devices with different base width was compared as the base was scaled from 60 down to 40 nm.
Temperature change as a probe of muscle crossbridge kinetics: a review and discussion

Following the ideas introduced by Huxley (Huxley 1957, Prog. Biophys. Biophys. Chem. 7, 255–318), it is generally supposed that muscle contraction is produced by temporary links, called crossbridges, between myosin and actin filaments, which form and break in a cyclic process driven by ATP splitting. Here we consider the interaction of the energy in the crossbridge, in its various states, and the force exerted. We discuss experiments in which the mechanical state of the crossbridge is changed by imposed movement and the energetic consequence observed as heat output and the converse experiments in which the energy content is changed by altering temperature and the mechanical consequences are observed. The thermodynamic relationship between the experiments is explained and, at the first sight, the relationship between the results of these two types of experiment appears paradoxical. However, we describe here how both of them can be explained by a model in which mechanical and energetic changes in the crossbridges occur in separate steps in a branching cycle.
A new algorithm for Kohonen layer learning with application to power system stability analysis

In certain classification problems, input patterns are not distributed in a clustering manner but distributed uniformly in an input space and there exist certain critical hyperplanes called decision boundaries. Since learning vector quantization (LVQ) classifies an input vector based on the nearest neighbor, the codebook vectors away from the decision boundaries are redundant. This paper presents an alternative algorithm called boundary search algorithm (BSA) for the purpose of solving this redundancy problem. The BSA finds a fixed number of codebook vectors near decision boundaries by selecting appropriate training vectors. It is found to be more efficient compared with LVQ and its validity is demonstrated with satisfaction in the transient stability analysis of a power system.
ALPACAS: A Large-Scale Privacy-Aware Collaborative Anti-Spam System

While the concept of collaboration provides a natural defense against massive spam emails directed at large numbers of recipients, designing effective collaborative anti-spam systems raises several important research challenges. First and foremost, since emails may contain confidential information, any collaborative anti-spam approach has to guarantee strong privacy protection to the participating entities. Second, the continuously evolving nature of spam demands the collaborative techniques to be resilient to various kinds of camouflage attacks. Third, the collaboration has to be lightweight, efficient, and scalable. Towards addressing these challenges, this paper presents ALPACAS - a privacy-aware framework for collaborative spam filtering. In designing the ALPACAS framework, we make two unique contributions. The first is a feature-preserving message transformation technique that is highly resilient against the latest kinds of spam attacks. The second is a privacy-preserving protocol that provides enhanced privacy guarantees to the participating entities. Our experimental results conducted on a real email dataset shows that the proposed framework provides a 10 fold improvement in the false negative rate over the Bayesian-based Bogofilter when faced with one of the recent kinds of spam attacks. Further, the privacy breaches are extremely rare. This demonstrates the strong privacy protection provided by the ALPACAS system.
The Relationship Between Multiple Forms of Discrimination, Neighborhood Characteristics, and Depression Among Illicit Drug Users in New York City

It is plausible that features of the social environment combined with experiences of discrimination may help further explain experiences of depression among illicit drug users. We examined the influence of census tract-level characteristics and multiple forms of individual-level discrimination on lifetime depression among illicit drug users in New York City enrolled in the “Social Ties Associated With Risk of Transition” study. Population average models accounted for clustering of individuals within census tracts. Discrimination based on prior incarceration explained Hispanic/White differences in depression and was independently associated with depression after accounting for neighborhood characteristics. Neighborhood poverty was only marginally related to lifetime depression. These data provide evidence supporting the influence of discrimination on depression among drug users. Research is needed to confirm these findings and highlight specific mechanisms through which discrimination and neighborhood socioeconomic status may operate to influence mental health.
Learning and knowledge generation in General Games

General Game Playing (GGP) aims at developing game playing agents that are able to play a variety of games and in the absence of game specific knowledge, become proficient players. Most GGP players have used standard tree-search techniques enhanced by automatic heuristic learning. In this paper we explore knowledge representation and learning in GGP using Reinforcement Learning and Ant Colony Algorithms. Knowledge is created by simulating random games. We test the quality of the knowledge by comparing the performance of players using the knowledge in a variety of games. The ideas presented in this paper provide the potential for a framework for learning and knowledge representation, given the total absence of any prior knowledge.
Trace-based Approach to Editability and Correspondence Analysis for Bidirectional Graph Transformations

Bidirectional graph transformation is expected to play an important role in model-driven software engineering where artifacts are often rened through compositions of model transformations, by propa- gating changes in the artifacts over transformations bidirectionally. How- ever, it is often difficult to understand the correspondence among ele- ments of the artifacts such as to which part in the source an edit on the view is to be propagated. It is equally hard to predict whether an edit is propagable to the source, if the edit affects other parts in the target, or where in the transformation should be changed to accommodate the edit. These issues are critical for more complex transformations. In this paper, we propose an approach to analyzing the above correspondence as well as to classifying edges according to their editability on the target, in a compositional framework of bidirectional graph transformation. These are achieved by augmenting the forward semantics of the transforma- tions with explicit correspondence traces. By leveraging this approach, it is possible to solve the above issues, without executing the entire back- ward transformation. We demonstrate the effectiveness of our approach via GUI using non-trivial transformations.
Designing Phononic Crystals with Wide and Robust Band Gaps

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects), and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters and uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originated from a local resonances dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (3 unit cells) to obtain broad, robust and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices. 2
The implications of autonomy: Viewed in the light of efforts to uphold patients dignity and integrity

This article focuses on Danish patients’ experience of autonomy and its interplay with dignity and integrity in their meeting with health professionals. The aim is to chart the meanings and implications of autonomy for persons whose illness places them in a vulnerable life situation. The interplay between autonomy and personal dignity in the meeting with health care staff are central concepts in the framework. Data collection and findings are based on eight qualitative semi-structured interviews with patients. Patients with acute, chronic, and life threatening diseases were represented including surgical as well as medical patients. The values associated with autonomy are in many ways vitalising, but may become so dominant, autonomy seeking, and pervasive that the patient's dignity is affected. Three types of patient behaviour were identified. (1) The proactive patient: Patients feel that they assume responsibility for their own situation, but it may be a responsibility that they find hard to bear. (2) The rejected patient: proactive patients take responsibility on many occasions but very active patients are at risk of being rejected with consequences for their dignity. (3) The knowledgeable patient: when patients are health care professionals, the patient's right of self-determination was managed in a variety of ways, sometimes the patient's right of autonomy was treated in a dignified way but the opposite was also evident. In one way, patients are active and willing to take responsibility for themselves, and at the same time they are “forced” to do so by health care staff. Patients would like health professionals to be more attentive and proactive.
Event Series Prediction via Non-Homogeneous Poisson Process Modelling

Data streams whose events occur at random arrival times rather than at the regular, tick-tock intervals of traditional time series are increasingly prevalent. Event series are continuous, irregular and often highly sparse, differing greatly in nature to the regularly sampled time series traditionally the concern of hard sciences. As mass sets of such data have become more common, so interest in predicting future events in them has grown. Yet repurposing of traditional forecasting approaches has proven ineffective, in part due to issues such as sparsity, but often due to inapplicable underpinning assumptions such as stationarity and ergodicity. In this paper we derive a principled new approach to forecasting event series that avoids such assumptions, based upon: 1. The processing of event series datasets in order to produce a first parameterized mixture model of non-homogeneous Poisson processes, and 2. Application of a technique called parallel forecasting that uses these processes' rate functions to directly generate accurate temporal predictions for new query realizations. This approach uses forerunners of a stochastic process to shed light on the distribution of future events, not for themselves, but for realizations that subsequently follow in their footsteps.