cssi/SciSciGPT-SciSciNet huggingface dataset:
SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation

Supervised training of abstractive language generation models results in learning conditional probabilities over language sequences based on the supervised training signal. When the training signal contains a variety of writing styles, such models may end up learning an ‘average’ style that is directly influenced by the training data make-up and cannot be controlled by the needs of an application. We describe a family of model architectures capable of capturing both generic language characteristics via shared model parameters, as well as particular style characteristics via private model parameters. Such models are able to generate language according to a specific learned style, while still taking advantage of their power to model generic language phenomena. Furthermore, we describe an extension that uses a mixture of output distributions from all learned styles to perform on-the-fly style adaptation based on the textual input alone. Experimentally, we find that the proposed models consistently outperform models that encapsulate single-style or average-style language generation capabilities.
The costs and benefits of bank capital requirements

Since the immediate aftermath of the 2007–2009 financial crisis, several studies have produced estimates of the short-term and long-term impact of increases in bank regulatory capital on bank lending and real activity. As documented in BCBS (2016), earlier studies concluded that permanent and significant increases in capital requirements would result in relatively small declines in bank lending and modest declines in real activity. More recent studies have detected cases in which the short-term impact of increases in capital requirements may be large, but a gradual phasing-in of these requirements may spread their costs out evenly in the long-term. Importantly, most studies conclude that the long-term costs of higher capital requirements are lower than the benefits arising from their lowering the probability of banking crises with their attendant real costs…
Deuce: a lightweight user interface for structured editing

We present a structure-aware code editor, called Deuce, that is equipped with direct manipulation capabilities for invoking automated program transformations. Compared to traditional refactoring environments, Deuce employs a direct manipulation interface that is tightly integrated within a text-based editing workflow. In particular, Deuce draws (i) clickable widgets atop the source code that allow the user to structurally select the unstructured text for subexpressions and other relevant features, and (ii) a lightweight, interactive menu of potential transformations based on the current selections. We implement and evaluate our design with mostly standard transformations in the context of a small functional programming language. A controlled user study with 21 participants demonstrates that structural selection is preferred to a more traditional text-selection interface and may be faster overall once users gain experience with the tool. These results accord with Deuce's aim to provide human-friendly structural interactions on top of familiar text-based editing.
Comparative Pathogenesis of Asian and African-Lineage Zika Virus in Indian Rhesus Macaque's and Development of a Non-Human Primate Model Suitable for the Evaluation of New Drugs and Vaccines.

The establishment of a well characterized non-human primate model of Zika virus (ZIKV) infection is critical for the development of medical interventions. In this study, challenging Indian rhesus macaques (IRMs) with ZIKV strains of the Asian lineage resulted in dose-dependent peak viral loads between days 2 and 5 post infection and a robust immune response which protected the animals from homologous and heterologous re-challenge. In contrast, viremia in IRMs challenged with an African lineage strain was below the assay’s lower limit of quantitation, and the immune response was insufficient to protect from re-challenge. These results corroborate previous observations but are contrary to reports using other African strains, obviating the need for additional studies to elucidate the variables contributing to the disparities. Nonetheless, the utility of an Asian lineage ZIKV IRM model for countermeasure development was verified by vaccinating animals with a formalin inactivated reference vaccine and demonstrating sterilizing immunity against a subsequent subcutaneous challenge.
On the Nature of Trapped-Hole States in CdS Nanocrystals and the Mechanism of Their Diffusion

Recent transient absorption experiments on CdS nanorods suggest that photoexcited holes rapidly trap to the surface of these particles and then undergo diffusion along the rod surface. In this Letter, we present a semiperiodic density functional theory model for the CdS nanocrystal surface, analyze it, and comment on the nature of both the hole-trap states and the mechanism by which the holes diffuse. Hole states near the top of the valence band form an energetic near continuum with the bulk and localize to the nonbonding sp3 orbitals on surface sulfur atoms. After localization, the holes form nonadiabatic small polarons that move between the sulfur orbitals on the surface of the particle in a series of uncorrelated, incoherent, thermally activated hops at room temperature. The surface-trapped holes are deeply in the weak-electronic coupling limit and, as a result, undergo slow diffusion.
Twofold C−H Functionalization: Palladium-Catalyzed Ortho Arylation of Anilides

The ortho arylation of anilides to form biphenyls via a twofold C−H functionalization/C−C bond-forming process is described. The oxidative coupling takes place in the presence of 5−10 mol % of Pd(OAc)2, 10−20 mol % of DMSO, and 4−11 equiv of the aryl substrate in TFA under an oxygen atmosphere. No metal-containing cocatalyst is required.
Generational Succession in American Giving: Donors Down, Dollars Per Donor Holding Steady But Signs That It Is Starting to Slip:

Comparing two generations at the same point in their life cycles, four decades apart, indicates that average giving to charitable organizations (not including congregations) by Baby Boom families h...
Finding Frequent Entities in Continuous Data.

In many applications that involve processing high-dimensional data, it is important to identify a small set of entities that account for a significant fraction of detections. Rather than formalize this as a clustering problem, in which all detections must be grouped into hard or soft categories, we formalize it as an instance of the frequent items or heavy hitters problem, which finds groups of tightly clustered objects that have a high density in the feature space. We show that the heavy hitters formulation generates solutions that are more accurate and effective than the clustering formulation. In addition, we present a novel online algorithm for heavy hitters, called HAC, which addresses problems in continuous space, and demonstrate its effectiveness on real video and household domains.
Sentiment-driven Community Profiling and Detection on Social Media

Web 2.0 helps to expand the range and depth of conversation on many issues and facilitates the formation of online communities. Online communities draw various individuals together based on their common opinions on a core set of issues. Most existing community detection methods merely focus on discovering communities without providing any insight regarding the collective opinions of community members and the motives behind the formation of communities. Several efforts have been made to tackle this problem by presenting a set of keywords as a community profile. However, they neglect the positions of community members towards keywords, which play an important role for understanding communities in the highly polarized atmosphere of social media. To this end, we present a sentiment-driven community profiling and detection framework which aims to provide community profiles presenting positive and negative collective opinions of community members separately. With this regard, our framework initially extracts key expressions in users' messages as representative of issues and then identifies users' positive/negative attitudes towards these key expressions. Next, it uncovers a low-dimensional latent space in order to cluster users according to their opinions and social interactions (i.e., retweets). We demonstrate the effectiveness of our framework through quantitative and qualitative evaluations.
Tuning the electrochemical potential of perfunctionalized dodecaborate clusters through vertex differentiation

We report a new class of redox-active vertex-differentiated dodecaborate clusters featuring pentafluoroaryl groups. These [B12(OR)11NO2] clusters share several unique photophysical properties with their [B12(OR)12] analogues, while exhibiting significantly higher (+0.5 V) redox potentials. This work describes the synthesis, characterization, and isolation of [B12(O–CH2C6F5)11NO2] clusters in all 3 oxidation states (dianion, radical, and neutral). Reactivity to post-functionalization with thiol species via SNAr on the pentafluoroaryl groups is also demonstrated.
A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.
Personality in the Human Robot Interaction Literature: A Review and Brief Critique

Personality have been identified as an important facilitator of human robot interaction. Despite this, the research on personality in the human robot interaction literature remains fragmented and lacks a coherent framework. This makes it difficult for scholars to comprehend what is known and what is not. This paper reviews the literature on personality and robots. This review: (1) highlights three major research areas, (2) identifies gaps to be addressed and (3) presents major conclusions from the literature.
Band structure of twisted bilayer graphene: Emergent symmetries, commensurate approximants, and Wannier obstructions

Motivated by the exciting discovery of correlated insulating behavior and superconductivity in magic-angle bilayer graphene, the authors discuss here the salient features of the band structure of this system. A remarkable feature is the appearance of isolated, nearly flat bands around the magic angles. The authors discuss the importance of emergent symmetries of this system and clarify some potential confusion regarding commensurate structures of twisted bilayer graphene. Furthermore, they discuss the band topology, which leads to obstructions to constructing well-localized Wannier functions of the nearly flat bands, and give directions towards overcoming the difficulties.
Variance Reduction for Reinforcement Learning in Input-Driven Environments

We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system. Input processes arise in many applications, including queuing systems, robotics control with disturbances, and object tracking. Since the state dynamics and rewards depend on the input process, the state alone provides limited information for the expected future returns. Therefore, policy gradient methods with standard state-dependent baselines suffer high variance during training. We derive a bias-free, input-dependent baseline to reduce this variance, and analytically show its benefits over state-dependent baselines. We then propose a meta-learning approach to overcome the complexity of learning a baseline that depends on a long sequence of inputs. Our experimental results show that across environments from queuing systems, computer networks, and MuJoCo robotic locomotion, input-dependent baselines consistently improve training stability and result in better eventual policies.
To Index or Not to Index: Optimizing Exact Maximum Inner Product Search

Exact Maximum Inner Product Search (MIPS) is an important task that is widely pertinent to recommender systems and high-dimensional similarity search. The brute-force approach to solving exact MIPS is computationally expensive, thus spurring recent development of novel indexes and pruning techniques for this task. In this paper, we show that a hardware-efficient brute-force approach, blocked matrix multiply (BMM), can outperform the state-of-the-art MIPS solvers by over an order of magnitude, for some—but not all—inputs. In this paper we also present a novel MIPS solution, MAX-IMUS, that takes advantage of hardware efficiency and pruning of the search space. Like BMM, MAXIMUS is faster than other solvers by up to an order of magnitude, but again only for some inputs. Since no single solution offers the best runtime performance for all inputs, we introduce a new data-dependent optimizer, OPTIMUS, that selects online with minimal overhead the best MIPS solver for a given input. Together, OPTIMUS and MAXIMUS outperform state-of-the-art MIPS solvers by 3.2× on average, and up to 10.9×, on widely studied MIPS datasets.
Chronic Aortitis Following Furosemide Therapy

A significant increase in histopathologic nonspecific chronic aortitis was found when 100 autopsy specimens from 1965 were compared with series from 1974 and 1980. The chronic aortitis was correlated with furosemide diuretic administration during the last hospitalization. Furosemide is albumin bound, produces vasodilation, and is suspected of having induced a subclinical haptenic immunologic reaction in about one third of those treated.
Corrective policy reactions: positive and negative budgetary punctuations

Punctuated equilibrium theory seeks to explain policy volatility and stability in government attention. In previous research into the temporal dynamics of punctuations, scholars found that punctuations occur in clusters – a recent budgetary punctuation increases the likelihood of a subsequent punctuation. This article examines the direction, positive or negative, of budgetary punctuations over time. Are budgetary punctuations corrective, grouping positive and negative changes? Or, do budgetary punctuations occur in cumulative trends of positive or negative changes? These questions address the heart of the theoretical metaphor for punctuated equilibrium. In an analysis of over 1,000 Texas school districts for nearly a 20-year-period, results support the notion of reactive patterns of budgetary punctuations – positive and negative budgetary punctuations pair up at a rate much higher than expected by chance. The findings demonstrate that even though it is likely to see consecutive positive and negative punctuations, they are not always fully corrective.
Advertising and brand attitudes: Evidence from 575 brands over five years

Little is known about how different types of advertising affect brand attitudes. We investigate the relationships between three brand attitude variables (perceived quality, perceived value and recent satisfaction) and three types of advertising (national traditional, local traditional and digital). The data represent ten million brand attitude surveys and $264 billion spent on ads by 575 regular advertisers over a five-year period, approximately 37% of all ad spend measured between 2008 and 2012. Inclusion of brand/quarter fixed effects and industry/week fixed effects brings parameter estimates closer to expectations without major reductions in estimation precision. The findings indicate that (i) national traditional ads increase perceived quality, perceived value, and recent satisfaction; (ii) local traditional ads increase perceived quality and perceived value; (iii) digital ads increase perceived value; and (iv) competitor ad effects are generally negative.
DropBlock: A regularization method for convolutional networks

Deep neural networks often work well when they are over-parameterized and trained with a massive amount of noise and regularization, such as weight decay and dropout. Although dropout is widely used as a regularization technique for fully connected layers, it is often less effective for convolutional layers. This lack of success of dropout for convolutional layers is perhaps due to the fact that activation units in convolutional layers are spatially correlated so information can still flow through convolutional networks despite dropout. Thus a structured form of dropout is needed to regularize convolutional networks. In this paper, we introduce DropBlock, a form of structured dropout, where units in a contiguous region of a feature map are dropped together. We found that applying DropbBlock in skip connections in addition to the convolution layers increases the accuracy. Also, gradually increasing number of dropped units during training leads to better accuracy and more robust to hyperparameter choices. Extensive experiments show that DropBlock works better than dropout in regularizing convolutional networks. On ImageNet classification, ResNet-50 architecture with DropBlock achieves $78.13\%$ accuracy, which is more than $1.6\%$ improvement on the baseline. On COCO detection, DropBlock improves Average Precision of RetinaNet from $36.8\%$ to $38.4\%$.
Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA

High-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with great accuracy, they fall short of analyzing how these individual events are combined into complete RNA transcript isoforms. Because of this shortfall, long-distance information is required to complement short-read sequencing to analyze transcriptomes on the level of full-length RNA transcript isoforms. While long-read sequencing technology can provide this long-distance information, there are issues with both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) long-read sequencing technologies that prevent their widespread adoption. Briefly, PacBio sequencers produce low numbers of reads with high accuracy, while ONT sequencers produce higher numbers of reads with lower accuracy. Here, we introduce and validate a long-read ONT-based sequencing method. At the same cost, our Rolling Circle Amplification to Concatemeric Consensus (R2C2) method generates more accurate reads of full-length RNA transcript isoforms than any other available long-read sequencing method. These reads can then be used to generate isoform-level transcriptomes for both genome annotation and differential expression analysis in bulk or single-cell samples.
The Double Weakness of Girls: Discrimination and Sexual Violence in Haiti

This paper presents findings of an empirical research study conducted in the capital of Haiti, Port-au-Prince, exploring the cultural beliefs and criminal justice responses to practices of gender-based violence. Plagued by destitution, political instability and bloody confrontations among rival armed groups, Haiti endures the widespread use of systematic rape as a weapon of war affecting 50% of girls living in the conflict areas of Port-au-Prince. Through an involved fieldwork consisting of face-to-face open-ended interviews with informants from international and national institutions, governmental representatives and a few victims, this study proposes an understanding of the cultural root causes grounding the practices of discrimination and sexual violence against girls in the country as well as shedding light on the untold stories of victims suffering for the dual weakness of being women in a child’s body. By means of an engaged analysis of the international human rights standards on the one hand, and the criminal legal responses on the other, this research offers a window to the dim vacuum between international law aspirations and human rights violations, revealing that the extant criminal judicial system remains largely inadequate and profoundly informed by corruption, internal dysfunctions and gender bias. This same analysis serves the purpose of envisaging potential strategies, future preventive approaches as well as legal proposals and policy recommendations aimed at ensuring effective protection for girls in Haiti and honoring the ultimate quest for human rights.
Auditor Responses to Shareholder Activism

In this paper, we investigate how auditors respond to shareholder activism against their clients. Our study is important because activism may be viewed by auditors as a source of increased engagement risk, thereby impacting audit outcomes. The potential relationship between shareholder activism and audit outcomes leads us to predict that activism targets will pay higher audit fees and also will be more likely to receive adverse internal control opinions (ICOs) and first‐time going concern opinions (GCOs). Our results, which support all three predictions, suggest that the public scrutiny associated with activism campaigns heightens auditors' concerns about reputational damage and litigation risk. Consistent with this notion, we find that activism targets are more likely to experience accounting‐related lawsuits. We also find that the increased likelihood of adverse ICOs documented in our baseline tests reflects higher‐quality reporting rather than increased auditor conservatism. Overall, our findings suggest that activism campaigns spur auditor diligence while also increasing the possibility of negative outcomes that may not be fully anticipated by activist investors. Reponses des auditeurs a l'activisme des actionnaires Dans cet article, nous examinons de quelle facon les auditeurs repondent a l'activisme des actionnaires a l'encontre de leurs clients. Notre etude est importante, car l'activisme peut etre percu par les auditeurs comme une source d'accroissement du risque de mission, et peut donc avoir une incidence sur les resultats d'audit. La relation possible entre l'activisme des actionnaires et les resultats d'audit nous laisse presager que les societes qui font l'objet d'un tel activisme assument des frais d'audit plus eleves et sont plus susceptibles de recevoir une opinion sur le controle interne negative et une premiere opinion sur la continuite de l'exploitation. Nos observations, qui soutiennent ces trois previsions, portent a croire que l'examen du public associe aux campagnes d'activisme accroit les preoccupations des auditeurs quant aux risques d'atteinte a la reputation et de litige. Conformement a cette notion, nous constatons que les societes ciblees par l'activisme sont plus susceptibles de faire face a des poursuites judiciaires liees a leurs activites comptables. Nous montrons egalement que la hausse de la probabilite de recevoir une opinion sur le controle interne negative documentee dans nos tests de base est attribuable a une communication d'information de meilleure qualite plutot qu'a un conservatisme accru de la part des auditeurs. Dans l'ensemble, nos observations donnent a penser que les campagnes d'activisme encouragent la diligence des auditeurs tout en augmentant la possibilite de resultats negatifs que ne peuvent pas entierement prevoir les investisseurs activistes.
Facilitating moral maturity: integrating developmental and cultural approaches

This study integrates developmental and cultural approaches to student development and finds that millennial college students are responsive to moral formation. A particular challenge to prosociali...
Interdependence as a Frame for Assistive Technology Research and Design

In this paper, we describe interdependence for assistive technology design, a frame developed to complement the traditional focus on independence in the Assistive Technology field. Interdependence emphasizes collaborative access and people with disabilities' important and often understated contribution in these efforts. We lay the foundation of this frame with literature from the academic discipline of Disability Studies and popular media contributed by contemporary disability justice activists. Then, drawing on cases from our own work, we show how the interdependence frame (1) synthesizes findings from a growing body of research in the Assistive Technology field and (2) helps us orient to additional technology design opportunities. We position interdependence as one possible orientation to, not a prescription for, research and design practice--one that opens new design possibilities and affirms our commitment to equal access for people with disabilities.
Tax Reform Made Me Do It

Executive SummaryThis paper examines corporations’ actions, and statements about actions, following the tax law change known as the Tax Cuts and Jobs Act of 2017 (TCJA). Specifically, we examine fo...
The Role of Apoptotic Signaling in Axon Guidance

Navigating growth cones are exposed to multiple signals simultaneously and have to integrate competing cues into a coherent navigational response. Integration of guidance cues is traditionally thought to occur at the level of cytoskeletal dynamics. Drosophila studies indicate that cells exhibit a low level of continuous caspase protease activation, and that axon guidance cues can activate or suppress caspase activity. We base a model for axon guidance on these observations. By analogy with other systems in which caspase signaling has non-apoptotic functions, we propose that caspase signaling can either reinforce repulsion or negate attraction in response to external guidance cues by cleaving cytoskeletal proteins. Over the course of an entire trajectory, incorrectly navigating axons may pass the threshold for apoptosis and be eliminated, whereas axons making correct decisions will survive. These observations would also explain why neurotrophic factors can act as axon guidance cues and why axon guidance systems such as Slit/Robo signaling may act as tumor suppressors in cancer.
Surgical Management of Trigeminal Neuralgia in Children.

Background Trigeminal neuralgia (TN) is a well-recognized facial pain syndrome. Discrete forms with disparate pain symptoms include classic and atypical. However, atypical facial pain includes neuralgiform pain along a spectrum. Most cases of TN are diagnosed in the adult population. Case reports and series of children have presented TN as a similar entity, with treatment similar to that for adults. We reviewed the pertinent data and present 2 pediatric TN cases successfully treated with microvascular decompression (MVD). Case Description Two pediatric patients (age 12 and 15 years) with TN refractory to previous medical therapy were identified. Both patients were deemed appropriate surgical candidates and underwent MVD to manage their TN. TN compression was arterial in both cases and involved portions of the anterior inferior cerebellar artery. Patient 1 was pain free 6 months after the procedure. Patient 2 was pain free immediately after the procedure and had been weaned off preoperative symptomatic management at the latest follow-up visit. The most recent follow-up examination was 12 and 8 months for patients 1 and 2, respectively, with both experiencing continued freedom from pain. Conclusions Few studies have reported on the effectiveness of MVD in the pediatric population for the management of TN. The supporting data and our 2 cases have demonstrated that MVD is effective for pediatric patients to treat their TN. Furthermore, the side effects appear to be minimal, with excellent pain relief after MVD in this patient population.
Reliability Assessment Tool: Development and Prototype Testing:

This paper presents a monitoring system that was developed to assess travel time reliability for observed operating conditions by utilizing traffic stream and non-transportation related data. A pro...
Comparative genomics analysis to differentiate metabolic and virulence gene potential in gastric versus enterohepatic Helicobacter species

The genus Helicobacter are gram-negative, microaerobic, flagellated, mucus-inhabiting bacteria associated with gastrointestinal inflammation and classified as gastric or enterohepatic Helicobacter species (EHS) according to host species and colonization niche. While there are over 30 official species, little is known about the physiology and pathogenic mechanisms of EHS, which account for most in the genus, as well as what genetic factors differentiate gastric versus EHS, given they inhabit different hosts and colonization niches. The objective of this study was to perform a whole-genus comparative analysis of over 100 gastric versus EHS genomes in order to identify genetic determinants that distinguish these Helicobacter species and provide insights about their evolution/adaptation to different hosts, colonization niches, and mechanisms of virulence. Whole-genome phylogeny organized Helicobacter species according to their presumed gastric or EHS classification. Analysis of orthologs revealed substantial heterogeneity in physiological and virulence-related genes between gastric and EHS genomes. Metabolic reconstruction predicted that unlike gastric species, EHS appear asaccharolytic and dependent on amino/organic acids to fuel metabolism. Additionally, gastric species lack de novo biosynthetic pathways for several amino acids and purines found in EHS and instead rely on environmental uptake/salvage pathways. Comparison of virulence factor genes between gastric and EHS genomes identified overlapping yet distinct profiles and included canonical cytotoxins, outer membrane proteins, secretion systems, and survival factors. The major differences in predicted metabolic function suggest gastric species and EHS may have evolved for survival in the nutrient-rich stomach versus the nutrient-devoid environments, respectively. Contrasting virulence factor gene profiles indicate gastric species and EHS may utilize different pathogenic mechanisms to chronically infect hosts and cause inflammation and tissue damage. The findings from this study provide new insights into the genetic differences underlying gastric versus EHS and support the need for future experimental studies to characterize these pathogens.
An experimental information gathering and utilization systems (IGUS) robot to demonstrate the “physics of now”

The past, present, and future are not fundamental properties of Minkowski spacetime. It has been suggested that they are properties of a class of information gathering and utilizing systems (IGUSs). A human is a model IGUS robot. We provide a demonstration that what is perceived as past, present, and future is not uniquely determined from the laws of physics by constructing a robot that process information differently and therefore experience different “presents.” We construct a customized virtual reality (VR) system which allows an observer to switch between present and past moments. This “robot” (human with VR system) can experience immersion in the immediate past ad libitum. Being able to actually construct an IGUS that has the same “present” at two different coordinates along the worldline lends support to the IGUS approach for explaining the psychological nature of past/present/future.
Late to the Game? Capital Flows to the Western Balkans

The boom and bust in capital flows to the New Member States (NMS) has received considerable attention, relatively little has, however, been written about capital flows to the Western Balkans, often perceived to be ‘late arrivals’ to large capital flows. We find that while financial integration took off later in the Western Balkans, it has increased rapidly, despite lower capital account openness. Capital inflows are (perhaps surprisingly) diverse in terms of source countries, but broadly similar in terms of drivers and composition, though with equity shares higher than they were in the NMS at comparable levels of development.
The Markovian Price of Information

Suppose there are n Markov chains and we need to pay a per-step price to advance them. The “destination” states of the Markov chains contain rewards; however, we can only get rewards for a subset of them that satisfy a combinatorial constraint, e.g., at most k of them, or they are acyclic in an underlying graph. What strategy should we choose to advance the Markov chains if our goal is to maximize the total reward minus the total price that we pay?
Unseen companions of V Hya inferred from periodic ejections

A recent study using $Hubble$ $Space$ $Telescope$ observations found periodic, high-speed, collimated ejections (or "bullets") from the star V Hya. The authors of that study proposed a model associating these bullets with the periastron passage of an unseen, substellar companion in an eccentric orbit and with an orbital period of $\sim8$ yrs. Here we propose that V Hya is part of a triple system, with a substellar companion having an orbital period of $\sim8$ yrs, and a tertiary object on a much wider orbit. In this model, the more distant object causes high-eccentricity excitations on the substellar companion's orbit via the Eccentric Kozai-Lidov mechanism. These eccentricities can reach such high values that they lead to Roche-lobe crossing, producing the observed bullet ejections via a strongly enhanced accretion episode. For example, we find that a ballistic bullet ejection mechanism can be produced by a brown-dwarf-mass companion, while magnetically driven outflows are consistent with a Jovian-mass companion. Finally, we suggest that the distant companion may reside at few a hundred AU on an eccentric orbit.
Online Multi-Object Tracking With Instance-Aware Tracker and Dynamic Model Refreshment

Recent progresses in model-free single object tracking (SOT) algorithms have largely inspired applying SOT to multi-object tracking (MOT) to improve the robustness as well as relieving dependency on external detector. However, SOT algorithms are generally designed for distinguishing a target from its environment, and hence meet problems when a target is spatially mixed with similar objects as observed frequently in MOT. To address this issue, in this paper we propose an instance-aware tracker to integrate SOT techniques for MOT by encoding awareness both within and between target models. In particular, we construct each target model by fusing information for distinguishing target both from background and other instances (tracking targets). To conserve uniqueness of all target models, our instance-aware tracker considers response maps from all target models and assigns spatial locations exclusively to optimize the overall accuracy. Another contribution we make is a dynamic model refreshing strategy learned by a convolutional neural network. This strategy helps to eliminate initialization noise as well as to adapt to variation of target size and appearance. To show the effectiveness of the proposed approach, it is evaluated on the popular MOT15 and MOT16 challenge benchmarks. On both benchmarks, our approach achieves the best overall performances in comparison with published results.
Investigation of modified Water chemistry for improved oil recovery: Application of DLVO theory and surface complexation model

Abstract It is widely accepted that oil recovery during waterflooding can be improved by modifying the composition of the injected brine. A typical approach is diluting the formation water to a specific lower salinity. However, recent experimental studies report the adverse effect of formation water dilution on oil recovery for specific oil/brine/rock systems. The adverse effect depends on the interactions within the system and is more pronounced in carbonates. In this study, we investigated the effect of water composition on the performance of low salinity water injection by considering the complex interaction of oil, brine, and rock system. A surface complexation model (SCM) is developed to calculate the zeta-potential at oil and rock surfaces. Considering a water film between oil and rock and using DLVO theory, attractive/repulsive forces between oil/brine and brine/rock interfaces are calculated. Contact angle is predicted employing the augmented Young-Laplace equation. Our zeta potential calculations based on the SCM reproduced the experimental data of oil/brine and brine/calcite zeta potential measurements. Our contact angle calculations using the DLVO theory and the augmented Young-Laplace equation accurately estimated the dynamic trend of contact angle during low salinity flood. Modeling wettability alteration as a function of contact angle was sufficient to predict the low salinity effect. The developed model is implemented in a comprehensive compositional reactive transport simulator to validate the proposed approach.
Evolutionary Semigroups and Lyapunov Theorems in Banach Spaces

We present a spectral mapping theorem for continuous semigroups of operators on any Banach space E. The condition for the hyperbolicity of a semigroup on E is given in terms of the generator of an evolutionary semigroup acting in the space of E-valued functions. The evolutionary semigroup generated by the propagator of a nonautonomous differential equation in E is also studied. A "discrete" technique for investigating the evolutionary semigroup is developed and applied in describing the hyperbolicity (exponential dichotomy) of the nonautonomous equation.
Enhancement of lithium amide to lithium imide transition via mechanical activation.

The decomposition of lithium amide (LiNH2) to lithium imide (Li2NH) and ammonia (NH3) with and without high-energy ball milling is investigated to lay a foundation for identifying methods to enhanc...
Host−Guest Symmetry and Charge Matching in Two Germanates with Intersecting Three-Dimensional Channels

Two germanates reported here illustrate important effects of host−guest symmetry matching (or mismatching) on the host framework symmetry, the ordering of extraframework species, and the coordination number of germanium. For a strong structure-directing agent, the symmetry of the host framework is dictated by the symmetry of the ordered guest molecules, whereas for a relatively weaker structure-directing agent, the siting of guest molecules must conform to the symmetry of the host framework through specific molecular conformation or multiple orientations.
Analyzing the Effects of Financial and Housing Wealth on Consumption using Micro Data

This paper analyzes the existence of “wealth effects” derived from net equity (in the form of housing, financial assets, and total net worth) on consumption. The study uses longitudinal household-level data?from the Panel Study of Income Dynamics (PSID) ?covering about 7,000-9,000 households in the U.S., with the estimations carried over the period 1999-2017. Overall, wealth effects are found to be relatively large and significant for housing wealth, but less so for other types of wealth, including stocks. Furthermore, the analysis shows how these estimated marginal propensities to consume (MPC) from wealth are closely linked to household characteristics, including income and demographic factors. Finally, underlying structural changes in household characteristics point to potentially lower aggregate MPCs from wealth going forward.
Microbial communities across a hillslope‐riparian transect shaped by proximity to the stream, groundwater table, and weathered bedrock

Watersheds are important suppliers of freshwater for human societies. Within mountainous watersheds, microbial communities impact water chemistry and element fluxes as water from precipitation events discharge through soils and underlying weathered rock, yet there is limited information regarding the structure and function of these communities. Within the East River, CO watershed, we conducted a depth-resolved, hillslope to riparian zone transect study to identify factors that control how microorganisms are distributed and their functions. Metagenomic and geochemical analyses indicate that distance from the East River and proximity to groundwater and underlying weathered shale strongly impact microbial community structure and metabolic potential. Riparian zone microbial communities are compositionally distinct, from the phylum down to the species level, from all hillslope communities. Bacteria from phyla lacking isolated representatives consistently increase in abundance with increasing depth, but only in the riparian zone saturated sediments we found Candidate Phyla Radiation bacteria. Riparian zone microbial communities are functionally differentiated from hillslope communities based on their capacities for carbon and nitrogen fixation and sulfate reduction. Selenium reduction is prominent at depth in weathered shale and saturated riparian zone sediments and could impact water quality. We anticipate that the drivers of community composition and metabolic potential identified throughout the studied transect will predict patterns across the larger watershed hillslope system.
Inference of species phylogenies from bi-allelic markers using pseudo-likelihood

Motivation Phylogenetic networks represent reticulate evolutionary histories. Statistical methods for their inference under the multispecies coalescent have recently been developed. A particularly powerful approach uses data that consist of bi-allelic markers (e.g. single nucleotide polymorphism data) and allows for exact likelihood computations of phylogenetic networks while numerically integrating over all possible gene trees per marker. While the approach has good accuracy in terms of estimating the network and its parameters, likelihood computations remain a major computational bottleneck and limit the method's applicability. Results In this article, we first demonstrate why likelihood computations of networks take orders of magnitude more time when compared to trees. We then propose an approach for inference of phylogenetic networks based on pseudo-likelihood using bi-allelic markers. We demonstrate the scalability and accuracy of phylogenetic network inference via pseudo-likelihood computations on simulated data. Furthermore, we demonstrate aspects of robustness of the method to violations in the underlying assumptions of the employed statistical model. Finally, we demonstrate the application of the method to biological data. The proposed method allows for analyzing larger datasets in terms of the numbers of taxa and reticulation events. While pseudo-likelihood had been proposed before for data consisting of gene trees, the work here uses sequence data directly, offering several advantages as we discuss. Availability and implementation The methods have been implemented in PhyloNet (http://bioinfocs.rice.edu/phylonet).
A tandem simulation framework for predicting mapping quality.

Read alignment is the first step in most sequencing data analyses. Because a read’s point of origin can be ambiguous, aligners report a mapping quality, which is the probability that the reported alignment is incorrect. Despite its importance, there is no established and general method for calculating mapping quality. I describe a framework for predicting mapping qualities that works by simulating a set of tandem reads. These are like the input reads in important ways, but the true point of origin is known. I implement this method in an accurate and low-overhead tool called Qtip, which is compatible with popular aligners.
Catalytic Antibodies in Synthesis: Design and Synthesis of a Hapten for Application to the Preparation of a Scalemic Pyrrolidine Ring Synthon for Ptilomycalin A

A catalytic antibody-based approach toward the synthesis of an optically active pyrrolidine ring synthon potentially useful for ptilomycalin A is described. Enantiomerically pure hapten 37 was designed and constructed with the eventual goal of generating antibodies for the enantioselective partial hydrolysis of a meso diester such as 44 into a monoacid 45. This transition state analog possesses a phosphonate group containing the requisite oxyanionic character of the tetrahedral intermediate for ester hydrolysis. A newly developed carbamate-based linker, which was found to be much more hydrolytically stable than the commonly used glutarate ester, was developed for coupling of the hapten to a carrier protein.
Synthetic and structural studies on new vinylcyclopentadienyl derivatives of titanium, iron and thallium

Abstract An improved procedure for the preparation of vinylcyclopentadienyllithium (1) from 6-methylfulvene and lithium diisopropylamide in THF solution has been developed. Reaction of 1 with thallium ethoxide in THF has produced vinylcyclopentadienylthallium (3). Compounds 1 and 3 have been used in the synthesis of vinyl- (4) and 1,1′-divinyltitanocene dichloride (5). Treatment of 1,2,3,4,6-pentamethylfulvene with lithium diisopropylamide in THF solution has afforded vinyltetramethylcyclopentadienyllithium (2) in high yield. Reactions of 2 with FeCl2 or TiCl4 have led to bis(η5-vinyltetramethylcyclopentadienyl)iron (7) and (η5-vinyltetramethylcyclopentadienyl)titanium trichloride (8), respectively. Compound 8 reacts with (η5-C5H5)T1 to produce 1-vinyl-2,3,4,5-tetramethyltitanocene dichloride (9) in high yield. The crystal structure of 5 has been determined. 5 is monoclinic, C21/c, with a = 14.420(3), b = 6.610(2), c = 14.111(3) A, β = 102.18(2)° and Dcalc = 1.52 g cm−3 for Z = 4. The Ti atom resides on a crystallographic two-fold axis. The η5-vinylcyclopentadienyl groups are slightly staggered with the carbons bonded to the vinyl groups next to one another and between the ClTiCl bond. The TiC(η5) separations range from 2.343(4) to 2.450(3) A, the latter values for the carbon atoms bonded to the vinyl group.
A framework for offline evaluation and optimization of real-time algorithms for use in neurofeedback, demonstrated on an instantaneous proxy for correlations.

Abstract Interest in real-time fMRI neurofeedback has grown exponentially over the past few years, both for use as a basic science research tool, and as part of the search for novel clinical interventions for neurological and psychiatric illnesses. In order to expand the range of questions which can be addressed with this tool however, new neurofeedback methods must be developed, going beyond feedback of activations in a single region. These new methods, several of which have already been proposed, are by their nature complex, involving many possible parameters. Here we suggest a framework for evaluating and optimizing algorithms for use in a real-time setting, before beginning the neurofeedback experiment, by offline simulations of algorithm output using a previously collected dataset. We demonstrate the application of this framework on the instantaneous proxy for correlations which we developed for training connectivity between different network nodes, identify the optimal parameters for use with this algorithm, and compare it to more traditional correlation methods. We also examine the effects of advanced imaging techniques, such as multi-echo acquisition, and the integration of these into the real-time processing stream.
Lewis acid activated and catalyzed cyclizations of aminyl radicals from N-hydroxypyridine-2-thione carbamates

Abstract A variety of Lewis acids promote 5-exo cyclizations of δ,e-unsaturated aminyl radicals produced from N-hydroxypyridine-2-thione carbamates under very mild conditions; catalysis was demonstrated in several cases.