cssi/SciSciGPT-SciSciNet huggingface dataset:
How Global is the Common Law? A Comparative Study of Asian Common Law Systems – Hong Kong, Malaysia, and Singapore

This article compares three common law jurisdictions in Asia – Hong Kong, Malaysia, and Singapore. By studying the use of foreign citations in the reported opinions of these jurisdictions, we show that they have acquired a judicial character that is distinctively outward-looking and global. The variety and range of foreign citations suggest that the phenomenon cannot be fully explained as a matter of colonial legacy. The article further discusses the ways in which the use of foreign case citations serve as a means for legal and professional enrichment.
Touring the Saturnian System

The Cassini mission to Saturn employs a Saturn orbiter and a Titan probe to conduct an intensive investigation of the Saturnian system. The orbiter flies a series of orbits, incorporating flybys of the Saturnian satellites, called the ‘satellite tour.’ During the tour, the gravitational fields of the satellites (mainly Titan) are used to modify and control the orbit, targeting from one satellite flyby to the next. The tour trajectory must also be designed to maximize opportunities for a diverse set of science observations, subject to mission-imposed constraints. Tour design studies have been conducted for Cassini over a period of several years to identify trades and strategies for achieving these sometimes conflicting goals. Concepts, strategies, and techniques previously developed for the Galileo mission to Jupiter have been modified, and new ones have been developed, to meet the requirements of the Cassini mission. A sample tour is presented illustrating the application of tour design strategies developed for Cassini.
A space and time-efficient index for the compacted colored de Bruijn graph

Motivation Indexing reference sequences for search-both individual genomes and collections of genomes-is an important building block for many sequence analysis tasks. Much work has been dedicated to developing full-text indices for genomic sequences, based on data structures such as the suffix array, the BWT and the FM-index. However, the de Bruijn graph, commonly used for sequence assembly, has recently been gaining attention as an indexing data structure, due to its natural ability to represent multiple references using a graphical structure, and to collapse highly-repetitive sequence regions. Yet, much less attention has been given as to how to best index such a structure, such that queries can be performed efficiently and memory usage remains practical as the size and number of reference sequences being indexed grows large. Results We present a novel data structure for representing and indexing the compacted colored de Bruijn graph, which allows for efficient pattern matching and retrieval of the reference information associated with each k-mer. As the popularity of the de Bruijn graph as an index has increased over the past few years, so have the number of proposed representations of this structure. Existing structures typically fall into two categories; those that are hashing-based and provide very fast access to the underlying k-mer information, and those that are space-frugal and provide asymptotically efficient but practically slower pattern search. Our representation achieves a compromise between these two extremes. By building upon minimum perfect hashing and making use of succinct representations where applicable, our data structure provides practically fast lookup while greatly reducing the space compared to traditional hashing-based implementations. Further, we describe a sampling scheme for this index, which provides the ability to trade off query speed for a reduction in the index size. We believe this representation strikes a desirable balance between speed and space usage, and allows for fast search on large reference sequences. Finally, we describe an application of this index to the taxonomic read assignment problem. We show that by adopting, essentially, the approach of Kraken, but replacing k-mer presence with coverage by chains of consistent unique maximal matches, we can improve the space, speed and accuracy of taxonomic read assignment. Availability and implementation pufferfish is written in C++11, is open source, and is available at https://github.com/COMBINE-lab/pufferfish. Supplementary information Supplementary data are available at Bioinformatics online.
Single-molecule diffusometry reveals the nucleotide-dependent oligomerization pathways of Nicotiana tabacum Rubisco activase

Oligomerization plays an important role in the function of many proteins, but a quantitative picture of the oligomer distribution has been difficult to obtain using existing techniques. Here we describe a method that combines sub-stoichiometric labeling and recently developed single-molecule diffusometry to measure the size distribution of oligomers under equilibrium conditions in solution, one molecule at a time. We use this technique to characterize the oligomerization behavior of Nicotiana tabacum (Nt) Rubisco activase (Nt-Rca), a chaperone-like AAA-plus ATPase essential in regulating carbon fixation during photosynthesis. We directly observed monomers, dimers, and a tetramer/hexamer mixture and extracted their fractional abundance as a function of protein concentration. We show that the oligomerization pathway of Nt-Rca is nucleotide dependent: ATPγS binding strongly promotes tetramer/hexamer formation from dimers and results in a preferred tetramer/hexamer population for concentrations in the 1-10 μM...
An Empirical Examination of the Bennett Hypothesis in Law School Prices

Abstract Whether colleges increase tuition in response to increased federal student loan limits (the Bennett Hypothesis) has been a topic of debate in the higher education community for decades, yet most studies have been based on small increases to Pell Grant or undergraduate student loan limits. In this paper, I leverage a large increase in graduate student lending limits that took place in 2006 followed by an expansion of federal income-driven repayment programs to examine whether law schools responded by raising tuition and whether student debt levels also increased. Using data from 2001 to 2015 across public and private law schools and both interrupted time series and difference-in-differences analytical techniques, I found rather modest relationships across both public and private nonprofit law schools. I conclude with some possible explanations for the lack of strong empirical support for the Bennett Hypothesis.
Order Without Intellectual Property Law: Open Science in Influenza

Today, intellectual property (IP) scholars accept that IP as an approach to information production has serious limits. But what lies beyond IP? A new literature on "intellectual production without IP" (or "IP without IP") has emerged to explore this question, but its examples and explanations have yet to convince skeptics. This Article reorients this new literature via a study of a hard case: a global influenza virus-sharing network that has for decades produced critically important information goods, at significant expense, and in a loose-knit group--all without recourse to IP. I analyze the Network as an example of "open science," a mode of information production that differs strikingly from conventional IP, and yet that successfully produces important scientific goods in response to social need. The theory and example developed here refute the most powerful criticisms of the emerging "IP without IP" literature, and provide a stronger foundation for this important new field. Even where capital costs are high, creation without IP can be reasonably effective in social terms, if it can link sources of funding to reputational and evaluative feedback loops like those that characterize open science. It can also be sustained over time, even by loose-knit groups and where the stakes are high, because organizations and other forms of law can help to stabilize cooperation. I also show that contract law is well suited to modes of information production that rely upon a "supply side" rather than "demand side" model. In its most important instances, "order without IP" is not order without governance, nor order without law. Recognizing this can help us better ground this new field, and better study and support forms of knowledge production that deserve our attention, and that sometimes sustain our very lives.
Adam Smith on the Future of Experimental Evolution and Economics

Experimental evolution is difficult to apply to humans because of the need to study possible changes over many generations. A similar method, though, may see history as a substitute for experiments. The 18th century economist Adam Smith uses methods compatible with the logic of experimental evolution, through the assumption of human homogeneity and the study of history, to explain endogenous variations of preferences and institutions.
Plant growth regulators ameliorate or exacerbate abiotic, biotic and combined stress interaction effects on Zea mays kernel weight with inbred-specific patterns

Abstract Plant growth regulators have documented roles in plant responses to single stresses. In combined-stress environments, plants exhibit novel genetic architecture for growth traits and physiological responses can display synergistic effects. Synergistic responses have been used to optimize agronomic production and recommendations for adaptation to weather and field conditions can be used to improve selective breeding for higher yielding crops. We hypothesized that alterations in hormone balance would alter phenotypic responses to abiotic and crowding stress in a genotype-specific manner. We investigated the role of plant growth regulators in modulating combined-stress growth responses in Zea mays. Maize inbreds were exposed to all single, double and triple combinations of the following stressors in a field environment: drought, nitrogen deprivation, and increased plant density. Growth regulator chemical treatments were applied in a factorial design using a range of inbred genotypes. We found significant differences between the seed weights of plants given different chemical treatments and when single-stress environments were compared to combined stress environments. Different inbred genotypes exhibited contrasting patterns of response to combined stress and plant growth regulator treatment. Plant growth regulators altered combined-stress response pathways in maize inbreds; predictions of growth regulator effects would be improved by better characterization of stress environments and genotype-environment interactions.
THE MEANING OF FAILED REPLICATIONS: A REVIEW AND PROPOSAL

The welcome rise of replication tests in economics has not been accompanied by a consensus standard for determining what constitutes a replication. A discrepant replication, in current usage of the term, can signal anything from an unremarkable disagreement over methods to scientific incompetence or misconduct. This paper proposes a standard for classifying one study as a replication of some other study. It is a standard that places the burden of proof on a study to demonstrate that it should have obtained identical results to the original, a conservative standard that is already used implicitly by many researchers. It contrasts this standard with decades of unsuccessful attempts to harmonize terminology, and argues that many prominent results described as replication tests should not be described as such. Adopting a conservative standard like this one can improve incentives for researchers, encouraging more and better replication tests.
Work-Life Balance and Labor Force Attachment at Older Ages

We use data from the Health and Retirement Study to examine the role of work-life balance as a non-monetary determinant of retirement transitions, conditional on job attributes such as hours of work, compensation, and benefits. We rely on self-reported measures of work-life conflict to proxy for low levels of work-life balance. We show that high levels of work-life conflict are significantly associated with subsequent reductions in labor supply for workers aged 51 to 79, and document heterogeneity by gender and employment status. Moreover, work-life conflict moderates labor supply responses to spousal health shocks. Workers who report higher levels of work-life conflict are significantly more likely to reduce their labor supply in the two years following a spouse’s health shock, and this effect is once more heterogeneous. The moderating effect of work-life conflict is stronger for women than men and, among female workers, stronger for those employed part-time at baseline.
Did the 2005 Deferred Prosecution Agreement Adversely Impact KPMG's Audit Practice?

We examine the consequences of misconduct in a Big 4 firm's nonaudit practice for its audit practice. Specifically, we examine whether KPMG's audit practice suffered a loss of audit fees and clients and/or a decline in factual audit quality following the 2005 deferred prosecution agreement (DPA) with the Department of Justice for marketing questionable tax shelters. We find little evidence that the DPA adversely impacted KPMG's audit practice by way of either audit fees or the likelihood of client gains/losses, suggesting little or no harm to KPMG's audit reputation. We also find that the DPA had no effect on the firm's factual audit quality, even for those audit clients that dropped KPMG as their tax service provider. Collectively, our findings suggest that there was no spillover effect from the DPA to KPMG's audit practice.
Enabling resilient microgrid through programmable network

In this paper, we integrate programmable networks in microgrid to provide flexible and easy-to-manage communication solutions, thus enabling resilient microgrid operations in face of various cyber and physical disturbances. Specifically, two contributions have been made: (1) Establish a novel softwaredefined networking (SDN) based communication architecture that abstracts the network infrastructure from the upper-level applications to significantly expedite the development of microgrid applications; (2) Create a hardware-in-the-loop cyberphysical platform for evaluating and validating the performance of the presented architecture, control techniques and SDN based functionalities. Test results have demonstrated that the new architecture can significantly enhance microgrid resilience, particularly for those that have high penetration of renewable energy sources.
A path out: Prescription drug abuse, treatment, and suicide

Abstract In this paper we investigate the dual role of supply restrictions and drug treatment in combating the concurrent rise of opioid abuse and suicide in the United States over the last two decades. We find that supply-side interventions decrease suicides in places with strong addiction-help networks, implying that prescription drug abuse is associated with an inherent risk of suicide. Our findings support an important role for access to treatment services in policies designed to combat the opioid epidemic.
Identifying High-Priority Proteins Across the Human Diseasome Using Semantic Similarity.

Identifying the genes and proteins associated with a biological process or disease is a central goal of the biomedical research enterprise. However, relatively few systematic approaches are available that provide objective evaluation of the genes or proteins known to be important to a research topic, and hence researchers often rely on subjective evaluation of domain experts and laborious manual literature review. Computational bibliometric analysis, in conjunction with text mining and data curation, attempts to automate this process and return prioritized proteins in any given research topic. We describe here a method to identify and rank protein-topic relationships by calculating the semantic similarity between a protein and a query term in the biomerical literature while adjusting for the impact and immediacy of associated research articles. We term the calculated metric the weighted co-publication distance (WCD) and show that it compares well to related approaches in predicting benchmark protein lists...
Soccer on Your Tabletop

We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewer or through an Augmented Reality device. At the heart of our paper is an approach to estimate the depth map of each player, using a CNN that is trained on 3D player data extracted from soccer video games. We compare with state of the art body pose and depth estimation techniques, and show results on both synthetic ground truth benchmarks, and real YouTube soccer footage.
Trip and parking generation rates for different housing types: Effects of compact development:

Guidelines for trip and parking generation in the United States come mainly from the Institute of Transportation Engineers (ITE). However, their trip and parking manuals focus on suburban locations...
Elite Colleges and Upward Mobility to Top Jobs and Top Incomes

This paper asks whether elite colleges help students outside of historically advantaged groups reach top positions in the economy. I combine administrative data on income and leadership teams at publicly traded firms with a regression discontinuity design based on admissions rules at elite business-focused degree programs in Chile. The 1.8% of college students admitted to these programs account for 41% of leadership positions and 39% of top 0.1% incomes. Admission raises the number of leadership positions students hold by 44% and their probability of attaining a top 0.1% income by 51%. However, these gains are driven by male applicants from high-tuition private high schools, with zero effects for female students or students from other school types with similar admissions test scores. Admissions effects are equal to 38% of the gap in rates of top attainment by gender and 54% of the gap by high school background for male students. A difference-in-differences analysis of the rates at which pairs of students lead the same firms suggests that peer ties formed between college classmates from similar backgrounds may play an important role in driving the observed effects.
Coverage-Rate Tradeoff Analysis in mmWave Heterogeneous Cellular Networks

In this paper, we first introduce a generalized modeling and analysis framework to explore the fundamental interactions between user association, coverage probability, and link rate in a millimeter-wave (mmWave) heterogeneous cellular network (HetNet), in which there are multiple tiers of the ultra-high-frequency (UHF) macrocell and small-cell base stations (BSs) and a single tier of mmWave small-cell BSs. A generalized user association scheme that can cover many path-loss-based user association schemes is proposed, and its related probabilistic properties that facilitate the derivations of the coverage probability and link rate are derived. The derived general expressions of the coverage and link rate not only shed light on how to design user association functions in order to maximize the coverage and link rate but also show that it is impossible to devise a user association scheme that maximizes the coverage and link rate at the same time. Namely, there exists a fundamental tradeoff between the coverage and link rate in mmWave HetNets with distinct bandwidths in the UHF and mmWave bands while a user is mymargin associating with a BS. We characterize the coverage-optimal and rate-optimal user association schemes and numerically validate their performances and show the coverage-rate tradeoff problem.
Well-being of child and family participants in phase 1 pediatric oncology clinical trials

Problem identification Pediatric oncology phase 1 clinical trials (P1Ts) are essential to developing new anticancer therapies; however, they raise complex ethical concerns about balancing the need for this research with the well-being of participating children. The purpose of this integrative review was to synthesize and appraise the evidence of how P1T participation, which begins with consent and ends with the transition off the P1T, can affect the well-being (either positively or negatively) of children with cancer. The Resilience in Individuals and Families Affected by Cancer Framework, which has an outcome of well-being, was used to synthesize findings. Literature search Articles on the experiences of child (n = 21) and adult (n = 31) P1T participants were identified through systematic searches. Data evaluation Articles were evaluated on rigor and relevance to P1T participant experiences as high, medium, or low. Synthesis Minimal empirical evidence was found regarding the effect of P1T participation on the well-being of children with cancer. Adult P1T participant experiences provide insights that could also be important to children's P1T experiences. Implications for practice To achieve a balanced approach in P1T consent discussions, nurses and healthcare providers who work with children considering participation in a P1T should share the potential effect of participation on participants' well-being.
Statistical Distributions of Pavement Damage Associated with Overweight Vehicles: Methodology and Case Study:

The trucking industry is the primary mode of transporting for goods and commodities in the United States. Currently, there is an increasing trend in the use of overweight (OW) vehicles on the highw...
Renal Imaging With Dual Energy Projection Radiography

Applications of dual energy radiography to renal imaging were evaluated using an experimental system for line-scanned projection radiography. This system combines digital radiographs simultaneously obtained at two differing x-ray energies (85 and 135 kVp) to create images in which materials of a desired mean atomic number are selectively cancelled. A preliminary evaluation of the technique was performed for three renal imaging problems: detection and characterization of renal masses of low radiographic contrast, evaluation of renal artery stenosis and unilateral renal ischemia, and detection of renal calculi. In all three applications, the dual energy technique produced results indicating potential advantages over conventional radiographic studies.
Detecting Egregious Responses in Neural Sequence-to-sequence Models

In this work, we attempt to answer a critical question: whether there exists some input sequence that will cause a well-trained discrete-space neural network sequence-to-sequence (seq2seq) model to generate egregious outputs (aggressive, malicious, attacking, etc.). And if such inputs exist, how to find them efficiently. We adopt an empirical methodology, in which we first create lists of egregious output sequences, and then design a discrete optimization algorithm to find input sequences that will cause the model to generate them. Moreover, the optimization algorithm is enhanced for large vocabulary search and constrained to search for input sequences that are likely to be input by real-world users. In our experiments, we apply this approach to dialogue response generation models trained on three real-world dialogue data-sets: Ubuntu, Switchboard and OpenSubtitles, testing whether the model can generate malicious responses. We demonstrate that given the trigger inputs our algorithm finds, a significant number of malicious sentences are assigned large probability by the model, which reveals an undesirable consequence of standard seq2seq training.
Watch Your Step: Learning Node Embeddings via Graph Attention

Graph embedding methods represent nodes in a continuous vector space, preserving different types of relational information from the graph. There are many hyper-parameters to these methods (e.g. the length of a random walk) which have to be manually tuned for every graph. In this paper, we replace previously fixed hyper-parameters with trainable ones that we automatically learn via backpropagation. In particular, we propose a novel attention model on the power series of the transition matrix, which guides the random walk to optimize an upstream objective. Unlike previous approaches to attention models, the method that we propose utilizes attention parameters exclusively on the data itself (e.g. on the random walk), and are not used by the model for inference. We experiment on link prediction tasks, as we aim to produce embeddings that best-preserve the graph structure, generalizing to unseen information. We improve state-of-the-art results on a comprehensive suite of real-world graph datasets including social, collaboration, and biological networks, where we observe that our graph attention model can reduce the error by up to 20\%-40\%. We show that our automatically-learned attention parameters can vary significantly per graph, and correspond to the optimal choice of hyper-parameter if we manually tune existing methods.
DF-Net: Unsupervised Joint Learning of Depth and Flow Using Cross-Task Consistency

We present an unsupervised learning framework for simultaneously training single-view depth prediction and optical flow estimation models using unlabeled video sequences. Existing unsupervised methods often exploit brightness constancy and spatial smoothness priors to train depth or flow models. In this paper, we propose to leverage geometric consistency as additional supervisory signals. Our core idea is that for rigid regions we can use the predicted scene depth and camera motion to synthesize 2D optical flow by backprojecting the induced 3D scene flow. The discrepancy between the rigid flow (from depth prediction and camera motion) and the estimated flow (from optical flow model) allows us to impose a cross-task consistency loss. While all the networks are jointly optimized during training, they can be applied independently at test time. Extensive experiments demonstrate that our depth and flow models compare favorably with state-of-the-art unsupervised methods.
A probabilistic population code based on neural samples

Sensory processing is often characterized as implementing probabilistic inference: networks of neurons compute posterior beliefs over unobserved causes given the sensory inputs. How these beliefs are computed and represented by neural responses is much-debated (Fiser et al. 2010, Pouget et al. 2013). A central debate concerns the question of whether neural responses represent samples of latent variables (Hoyer & Hyvarinnen 2003) or parameters of their distributions (Ma et al. 2006) with efforts being made to distinguish between them (Grabska-Barwinska et al. 2013). A separate debate addresses the question of whether neural responses are proportionally related to the encoded probabilities (Barlow 1969), or proportional to the logarithm of those probabilities (Jazayeri & Movshon 2006, Ma et al. 2006, Beck et al. 2012). Here, we show that these alternatives -- contrary to common assumptions -- are not mutually exclusive and that the very same system can be compatible with all of them. As a central analytical result, we show that modeling neural responses in area V1 as samples from a posterior distribution over latents in a linear Gaussian model of the image implies that those neural responses form a linear Probabilistic Population Code (PPC, Ma et al. 2006). In particular, the posterior distribution over some experimenter-defined variable like "orientation" is part of the exponential family with sufficient statistics that are linear in the neural sampling-based firing rates.
Misdemeanor Records and Employment Outcomes: An Experimental Study:

This study examined whether misdemeanor drug convictions impact entry-level hiring outcomes. An experimental correspondence study was used whereby fictitious resumes are sent to employers. Resumes ...
Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts.

We introduce an adversarial method for producing high-recall explanations of neural text classifier decisions. Building on an existing architecture for extractive explanations via hard attention, we add an adversarial layer which scans the residual of the attention for remaining predictive signal. Motivated by the important domain of detecting personal attacks in social media comments, we additionally demonstrate the importance of manually setting a semantically appropriate “default” behavior for the model by explicitly manipulating its bias term. We develop a validation set of human-annotated personal attacks to evaluate the impact of these changes.
On Conditions for Rate-induced Tipping in Multi-dimensional Dynamical Systems

The possibility of rate-induced tipping (R-tipping) away from an attracting fixed point has been thoroughly explored in 1-dimensional systems. In these systems, it is impossible to have R-tipping away from a path of quasi-stable equilibria that is forward basin stable (FBS), but R-tipping is guaranteed for paths that are non-FBS of a certain type. We will investigate whether these results carry over to multi-dimensional systems. In particular, we will show that the same conditions guaranteeing R-tipping in 1-dimension also guarantee R-tipping in higher dimensions; however, it is possible to have R-tipping away from a path that is FBS even in 2-dimensional systems. We will propose a different condition, forward inflowing stability (FIS), which we show is sufficient to prevent R-tipping in all dimensions. The condition, while natural, is difficult to verify in concrete examples. Monotone systems are a class for which FIS is implied by an easily verifiable condition. As a result, we see how the additional structure of these systems makes predicting the possibility of R-tipping straightforward in a fashion similar to 1-dimension. In particular, we will prove that the FBS and FIS conditions in monotone systems reduce to comparing the relative positions of equilibria over time. An example of a monotone system is given that demonstrates how these ideas are applied to determine exactly when R-tipping is possible.
Learning algorithms for scheduling in wireless networks with unknown channel statistics

Abstract We study the problem of learning channel statistics to efficiently schedule transmissions in wireless networks subject to interference constraints. We propose an algorithm that uses greedily-constructed schedules in order to learn the channels’ transmission rates, while simultaneously exploiting previous observations to obtain high throughput. Comparison to the offline solution shows our algorithm to have good performance that scales well with the number of links in the network. We then turn our attention to the stochastic setting where packets randomly arrive to the network and await transmission in queues at the nodes. We develop a queue-length-based scheduling policy that uses the channel learning algorithm as a component. We analyze our method in time-varying environments and show that it achieves the same stability region as that of a greedy policy with full channel knowledge.
A Swiss Army Infinitesimal Jackknife

The error or variability of machine learning algorithms is often assessed by repeatedly refitting a model with different weighted versions of the observed data. The ubiquitous tools of cross-validation (CV) and the bootstrap are examples of this technique. These methods are powerful in large part due to their model agnosticism but can be slow to run on modern, large data sets due to the need to repeatedly re-fit the model. In this work, we use a linear approximation to the dependence of the fitting procedure on the weights, producing results that can be faster than repeated re-fitting by an order of magnitude. This linear approximation is sometimes known as the “infinitesimal jackknife” in the statistics literature, where it is mostly used as a theoretical tool to prove asymptotic results. We provide explicit finite-sample error bounds for the infinitesimal jackknife in terms of a small number of simple, verifiable assumptions. Our results apply whether the weights and data are stochastic or deterministic, and so can be used as a tool for proving the accuracy of the infinitesimal jackknife on a wide variety of problems. As a corollary, we state mild regularity conditions under which our approximation consistently estimates true leave k-out cross-validation for any fixed k. These theoretical results, together with modern automatic differentiation software, support the application of the infinitesimal jackknife to a wide variety of practical problems in machine learning, providing a “Swiss Army infinitesimal jackknife.” We demonstrate the accuracy of our methods on a range of simulated and real datasets.
What Do Schools of Public Health Have to Say About Diversity and Inclusion

Objective. The purpose of this study was to understand how schools of public health (SPHs) define and operationalize diversity and inclusion. Methods. Data were collected in February 2017 from publ...
Towards Blockchain-Driven, Secure and Transparent Audit Logs

Audit logs serve as a critical component in the enterprise business systems that are used for auditing, storing, and tracking changes made to the data. However, audit logs are vulnerable to a series of attacks, which enable adversaries to tamper data and corresponding audit logs. In this paper, we present BlockAudit: a scalable and tamper-proof system that leverages the design properties of audit logs and security guarantees of blockchains to enable secure and trustworthy audit logs. Towards that, we construct the design schema of BlockAudit, and outline its operational procedures. We implement our design on Hyperledger and evaluate its performance in terms of latency, network size, and payload size. Our results show that conventional audit logs can seamlessly transition into BlockAudit to achieve higher security, integrity, and fault tolerance.
Future Nuisance Flooding in Norfolk, VA, From Astronomical Tides and Annual to Decadal Internal Climate Variability

Abstract Increasing sea level rise will lead to more instances of nuisance flooding along the Virginia coastline in the coming decades, causing road closures and deteriorating infrastructure. These minor flood events can be caused by astronomical tides alone, in addition to internal climate variability on annual to decadal timescales. An assessment of nuisance flooding from these two effects is presented up until the year2050 for Norfolk, Virginia. The analysis of water levels indicates that nuisance flooding from tides alone in conjunction with a medium-high sea level scenario will result in flooding beginning in 2030 with frequency increasing thereafter. The addition of climate variability, by use of an empirical mode decomposition, leads to a substantial increase of flooding relative to the tides-alone analysis and shows flood events beginning as soon as 2020. High tides in the future will produce nuisance flooding without the need of other drivers such as coastal storms.
Characterizing Super-Posters in a MOOC for Teachers' Professional Development.

Massive Open Online Courses (MOOCs) attract thousands of participants who each exercise autonomy by engaging with resources and with other participants to whatever degree they wish. When analyzing participants’ patterns of engagement in MOOCs it is possible to notice that certain participants exhibit high levels of participation, actively engaging with others in forums. This study focuses on characterizing these highly active participants, and understanding their contributions back to the network in a MOOC designed for teachers’ professional development. Connectivism is used as theoretical lens to describe super-posters’ engagement in forums. Data from participants’ demographics, click-data, and forum posts are used to identify these highly active users. Qualitative content analysis is used to categorize the content of their posts, and social network analysis is used to represent their patterns of engagement. Results show that super-posters are generators of engagement, repurposing the content learned from the MOOC and feeding-forward new resources to the network. Super-posters can be seen as representatives of participation inequality in forums. They position themselves as the most prestigious and most influential nodes in the networks created by participants as they engage in forums. In some networks super-posters served as bridges, connecting people from different discussion threads and helping information to flow through the network. This study provides to MOOC designers and MOOC instructors an affordable method to identify and classify super-posters in any MOOC. Findings of this study could be used by MOOC designers and MOOC instructors to develop pedagogical interventions to give these participants a special role in the next MOOC cohort, which may foster engagement in MOOC forums and nurture the cyclical process of learning described in Connectivism. Regarding implications for research, this study attends the need for qualitative methods when analyzing participants’ engagement in MOOC forums and contributes to our knowledge of participation inequality. It also extends the literature of super-posters by showing their characterization in a MOOC focused on teachers’ professional development.
Ventral Tegmental Dopamine Neurons Participate in Reward Identity Predictions

Dopamine (DA) neurons in the ventral tegmental area (VTA) and substantia nigra (SNc) encode reward prediction errors (RPEs) and are proposed to mediate error-driven learning. However, the learning strategy engaged by DA-RPEs remains controversial. RPEs might imbue predictive cues with pure value, independently of representations of their associated outcome. Alternatively, RPEs might promote learning about the sensory features (the identity) of the rewarding outcome. Here, we show that, although both VTA and SNc DA neuron activation reinforces instrumental responding, only VTA DA neuron activation during consumption of expected sucrose reward restores error-driven learning and promotes formation of a new cue→sucrose association. Critically, expression of VTA DA-dependent Pavlovian associations is abolished following sucrose devaluation, a signature of identity-based learning. These findings reveal that activation of VTA- or SNc-DA neurons engages largely dissociable learning processes with VTA-DA neurons capable of participating in outcome-specific predictive learning, and the role of SNc-DA neurons appears limited to reinforcement of instrumental responses.
Dyscalculia and Typical Math Achievement Are Associated With Individual Differences in Number-Specific Executive Function.

Deficits in numerical magnitude perception characterize the mathematics learning disability developmental dyscalculia (DD), but recent studies suggest the relation stems from inhibitory control demands from incongruent visual cues in the nonsymbolic number comparison task. This study investigated the relation among magnitude perception during differing congruency conditions, executive function, and mathematics achievement measured longitudinally in children (n = 448) from ages 4 to 13. This relation was investigated across achievement groups and as it related to mathematics across the full range of achievement. Only performance on incongruent trials related to achievement. Findings indicate that executive function in a numerical context, beyond magnitude perception or executive function in a non-numerical context, relates to DD and mathematics across a wide range of achievement.
Seasonal climatology and dynamical mechanisms of rainfall in the Caribbean

The Caribbean is a complex region that heavily relies on its rainfall cycle for its economic and societal needs. This makes the Caribbean especially susceptible to hydro-meteorological disasters (i.e. droughts and floods). Previous studies have investigated the seasonal cycle of rainfall in the Caribbean with monthly or longer resolutions that often mask the seasonal transitions and regional differences of rainfall. This has resulted in inconsistent findings on the seasonal cycle. In addition, the mechanisms that shape the climatological rainfall cycle in the region are not fully understood. To address these problems, this study conducts: (i) a principal component analysis of the annual cycle of precipitation across 38 Caribbean stations using daily observed precipitation data; and, (ii) a moisture budget analysis for the Caribbean, using the ERA-Interim Reanalysis. This study finds that the seasonal cycle of rainfall in the Caribbean hinges on three main facilitators of moisture convergence: the Eastern Pacific ITCZ, the Atlantic ITCZ, and the western flank of the North Atlantic Subtropical High (NASH). The Atlantic Warm Pool and Caribbean Low-Level Jet modify the extent of moisture provided by these main facilitators. The expansion and contraction of the western flank of NASH generate the bimodal pattern of the precipitation annual cycle in the northwestern Caribbean, central Caribbean, and with the Eastern Pacific ITCZ the western Caribbean. This study identifies the Atlantic ITCZ as the major source of precipitation for the central and southern Lesser Antilles, which is responsible for their unimodal rainfall pattern. Convergence by sub-monthly transients contributes little to Caribbean rainfall.
Proceedings of the 1st ACM workshop on Networking, systems, and applications for mobile handhelds

It is our great pleasure to welcome you to the 1st ACM Workshop on Networking, Systems, and Applications for Mobile Handhelds -- MobiHeld 2009. Today mobile handheld devices come in many forms, ranging from traditional cellular phones, smart phones, music players, electronic book readers, computation capable watches, and many more. This platform has grown both in numbers and their programmability in the recent years and is likely to change the computing, communications landscape in a radical ways in the years to come. The goal of this workshop is to provide a forum for researchers and practitioners to discuss, debate, demonstrate, and speculate on emerging challenges in this domain within the broad context of its networking, systems, and applications related issues. In this first year, MobiHeld attracted 21 paper submissions from a diverse set of countries, including Belgium, England, Finland, France, Germany, India, Israel, Slovenia, and the United States. The program committee deliberated over all of these submissions and accepted 10 of these papers for regular presentation in the workshop. These papers cover a wide range of topics, such as new input mechanisms, collaborative video recording, tracking medical drugs, facilitating electronic payments, enabling distributed computation, multi-player online games, web search techniques, energy efficiency issues, and user privacy. In addition, MobiHeld also accepted 8 posters and 2 demonstrations, some of which were picked from the paper submissions. These proceedings capture all of the above content, and we hope that they will serve as a valuable reference this growing community.
Team Dispersion and Performance: The Role of Team Communication and Transformational Leadership:

Organizations increasingly rely on virtual teams to access geographically dispersed expertise. Yet, team dispersion introduces challenges to team communication that may negatively influence team pe...
Microdroplet self-propulsion during dropwise condensation on lubricant-infused surfaces

Water vapor condensation is common in nature and widely used in industrial applications, including water harvesting, power generation, and desalination. As compared to traditional filmwise condensation, dropwise condensation on lubricant-infused surfaces (LIS) can lead to an order-of-magnitude increase in heat transfer rates. Small droplets (D ≤ 100 μm) account for nearly 85% of the total heat transfer and droplet sweeping plays a crucial role in clearing nucleation sites, allowing for frequent re-nucleation. Here, we focus on the dynamic interplay of microdroplets with the thin lubricant film during water vapor condensation on LIS. Coupling high-speed imaging, optical microscopy, and interferometry, we show that the initially uniform lubricant film re-distributes during condensation. Governed by lubricant height gradients, microdroplets as small as 2 μm in diameter undergo rigorous and gravity-independent self-propulsion, travelling distances multiples of their diameters at velocities up to 1100 μm s-1. Although macroscopically the movement appears to be random, we show that on a microscopic level capillary attraction due to asymmetrical lubricant menisci causes this gravity-independent droplet motion. Based on a lateral force balance analysis, we quantitatively find that the sliding velocity initially increases during movement, but decreases sharply at shorter inter-droplet spacing. The maximum sliding velocity is inversely proportional to the oil viscosity and is strongly dependent of the droplet size, which is in excellent agreement with the experimental observations. This novel and non-traditional droplet movement is expected to significantly enhance the sweeping efficiency during dropwise condensation, leading to higher nucleation and heat transfer rates.
A statistical model for predicting neutropenic fever.

e18050 Background: Febrile neutropenia (FN) is a common occurrence associated with chemotherapy regimens used in patients with acute myelogenous leukemia (AML). To our knowledge, there is no eviden...
Polarity Determination for Mocvd Growth of GaN on Si(111) by Convergent Beam Electron Diffraction

The polarity of laterally epitaxially overgrown (LEO) GaN on Si(111) with an AlN buffer layer grown by MOCVD has been studied by convergent beam electron diffraction (CBED). The LEO GaN was studied by cross-section and plan-view transmission electron microscopy (TEM). The threading dislocation density is less than 108 cm−2 and no inversion domains were observed. CBED patterns were obtained at 200 kV for the $$\left\langle {1\bar 100} \right\rangle $$ zone. Simulation was done by many-beam solution with 33 zero-order beams. The comparison of experimental CBED patterns and simulated patterns indicates that the polarity of GaN on Si(111) is Ga face.