cssi/SciSciGPT-SciSciNet huggingface dataset:
Evolution of functional diversity in the holozoan tyrosine kinome.

The emergence of multicellularity is strongly correlated with the expansion of tyrosine kinases, a conserved family of signaling enzymes that regulates pathways essential for cell-to-cell communication. Although tyrosine kinases have been classified from several model organisms, a molecular-level understanding of tyrosine kinase evolution across all holozoans is currently lacking. Using a hierarchical sequence constraint-based classification of diverse holozoan tyrosine kinases, we construct a new phylogenetic tree that identifies two ancient clades of cytoplasmic and receptor tyrosine kinases separated by the presence of an extended insert segment in the kinase domain connecting the D and E-helices. Present in nearly all receptor tyrosine kinases, this fast-evolving insertion imparts diverse functionalities such as post-translational modification sites and regulatory interactions. Eph and EGFR receptor tyrosine kinases are two exceptions which lack this insert, each forming an independent lineage characterized by unique functional features. We also identify common constraints shared across multiple tyrosine kinase families which warrant the designation of three new subgroups: Src Module (SrcM), Insulin Receptor Kinase-Like (IRKL), and Fibroblast, Platelet-derived, Vascular, and growth factor Receptors (FPVR). Subgroup-specific constraints reflect shared autoinhibitory interactions involved in kinase conformational regulation. Conservation analyses describe how diverse tyrosine kinase signaling functions arose through the addition of family-specific motifs upon subgroup-specific features and co-evolving protein domains. We propose the oldest tyrosine kinases, IRKL, SrcM, and Csk, originated from unicellular pre-metazoans and were co-opted for complex multicellular functions. The increased frequency of oncogenic variants in more recent tyrosine kinases suggests that lineage-specific functionalities are selectively altered in human cancers.
Brain tumor grade classification Using LSTM Neural Networks with Domain Pre-Transforms

The performance of image classification methods heavily relies on the high-quality annotations, which are not easily affordable, particularly for medical data. To alleviate this limitation, in this study, we propose a weakly supervised image classification method based on combination of hand-crafted features. We hypothesize that integration of these hand-crafted features alongside Long short-term memory (LSTM) classifier can reduce the adverse effects of weak labels in classification accuracy. Our proposed algorithm is based on selecting the appropriate domain representations of the data in Wavelet and Discrete Cosine Transform (DCT) domains. This information is then fed into LSTM network to account for the sequential nature of the data. The proposed efficient, low dimensional features exploit the power of shallow deep learning models to achieve higher performance with lower computational cost. In order to show efficacy of the proposed strategy, we have experimented classification of brain tumor grades and achieved the state of the art performance with the resolution of 256 × 256. We also conducted a comprehensive set of experiments to analyze the effect of each component on the performance.
How Do Firms Respond to Corporate Taxes

Using a novel empirical approach and newly available administrative data on US tax filings, we estimate the corporate elasticity of taxable income and determine how such tax responsiveness varies depending on accounting method, firm size, and interest rate. In response to a 10 percent increase in the expected marginal tax rate, private US firms decrease taxable income by 9.1 percent, which indicates a discernibly more elastic response than prevailing estimates. This response reflects a decrease in taxable income of 3.0% arising from real economic adjustments to a firm's scale of operations and 6.0 percent arising from tax adjustments via (e.g.) revenue and cost timing. Responsiveness to the corporate tax rate is more elastic if a firm uses cash (9.9%) rather than accrual accounting (7.4%), if the firm is small (9.9%) rather than large (8.6%), and if the firm has relatively high-cost access to capital.
Improving Multilingual Translation by Representation and Gradient Regularization

Multilingual Neural Machine Translation (NMT) enables one model to serve all translation directions, including ones that are unseen during training, i.e. zero-shot translation. Despite being theoretically attractive, current models often produce low quality translations – commonly failing to even produce outputs in the right target language. In this work, we observe that off-target translation is dominant even in strong multilingual systems, trained on massive multilingual corpora. To address this issue, we propose a joint approach to regularize NMT models at both representation-level and gradient-level. At the representation level, we leverage an auxiliary target language prediction task to regularize decoder outputs to retain information about the target language. At the gradient level, we leverage a small amount of direct data (in thousands of sentence pairs) to regularize model gradients. Our results demonstrate that our approach is highly effective in both reducing off-target translation occurrences and improving zero-shot translation performance by +5.59 and +10.38 BLEU on WMT and OPUS datasets respectively. Moreover, experiments show that our method also works well when the small amount of direct data is not available.
The CEO Problem With Inter-Block Memory

An $n$ -dimensional source with memory is observed by $K$ isolated encoders via parallel channels, who compress their observations to transmit to the decoder via noiseless rate-constrained links while leveraging their memory of the past. At each time instant, the decoder receives $K$ new codewords from the observers, combines them with the past received codewords, and produces a minimum-distortion estimate of the latest block of $n$ source symbols. This scenario extends the classical one-shot CEO problem to multiple rounds of communication with communicators maintaining the memory of the past. We extend the Berger-Tung inner and outer bounds to the scenario with inter-block memory, showing that the minimum asymptotically (as $n \to \infty $ ) achievable sum rate required to achieve a target distortion is bounded by minimal directed mutual information problems. For the Gauss-Markov source observed via $K$ parallel AWGN channels, we show that the inner bound is tight and solve the corresponding minimal directed mutual information problem, thereby establishing the minimum asymptotically achievable sum rate. Finally, we explicitly bound the rate loss due to a lack of communication among the observers; that bound is attained with equality in the case of identical observation channels. The general coding theorem is proved via a new nonasymptotic bound that uses stochastic likelihood coders and whose asymptotic analysis yields an extension of the Berger-Tung inner bound to the causal setting. The analysis of the Gaussian case is facilitated by reversing the channels of the observers.
Improved Schottky Array Performance With Lenticulated Faceplate

Laboratory evaluation is provided of the improved focal plane array performance realized with a novel optical technique that increases the fill factor of Schottky IRCCD mosaics. Specifically, a lenticulated silicon faceplate is installed on the IRCCD chip to redirect focused image irradiance away from nonsensitive areas in the focal plane and to the infrared-sensitive elements. A technique has been developed for successfully fabricating these optical faceplates with the necessary geometrical requirements. The performance data contained herein were obtained with an RCA-supplied 32 x 63 Schottky IRCCD mosaic having a lenticulated faceplate installed on a portion of the array surface. The adjacent dual construction allowed sensitivity and resolution differences to be easily evaluated under identical operating conditions. The enhanced performance was determined experimentally and then compared to predicted fill-factor improvement.
Estimating the drivers of urban economic complexity and their connection to economic performance.

Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated i...
Self-Replication via Tile Self-Assembly (Extended Abstract).

In this paper we present a model containing modifications to the Signal-passing Tile Assembly Model (STAM), a tile-based self-assembly model whose tiles are capable of activating and deactivating glues based on the binding of other glues. These modifications consist of an extension to 3D, the ability of tiles to form "flexible" bonds that allow bound tiles to rotate relative to each other, and allowing tiles of multiple shapes within the same system. We call this new model the STAM*, and we present a series of constructions within it that are capable of self-replicating behavior. Namely, the input seed assemblies to our STAM* systems can encode either "genomes" specifying the instructions for building a target shape, or can be copies of the target shape with instructions built in. A universal tile set exists for any target shape (at scale factor 2), and from a genome assembly creates infinite copies of the genome as well as the target shape. An input target structure, on the other hand, can be "deconstructed" by the universal tile set to form a genome encoding it, which will then replicate and also initiate the growth of copies of assemblies of the target shape. Since the lengths of the genomes for these constructions are proportional to the number of points in the target shape, we also present a replicator which utilizes hierarchical self-assembly to greatly reduce the size of the genomes required. The main goals of this work are to examine minimal requirements of self-assembling systems capable of self-replicating behavior, with the aim of better understanding self-replication in nature as well as understanding the complexity of mimicking it.
Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy

Compressed sensing fluorescence microscopy (CS-FM) proposes a scheme whereby less measurements are collected during sensing and reconstruction is performed to recover the image. Much work has gone into optimizing the sensing and reconstruction portions separately. We propose a method of jointly optimizing both sensing and reconstruction end-to-end under a total measurement constraint, enabling learning of the optimal sensing scheme concurrently with the parameters of a neural network-based reconstruction network. We train our model on a rich dataset of confocal, two-photon, and wide-field microscopy images comprising of a variety of biological samples. We show that our method outperforms several baseline sensing schemes and a regularized regression reconstruction algorithm. Our code is publicly-available at https://github.com/alanqrwang/csfm.
FrogCap: A modular sequence capture probe-set for phylogenomics and population genetics for all frogs, assessed across multiple phylogenetic scales.

Despite the prevalence of high-throughput sequencing in phylogenetics, many relationships remain difficult to resolve because of conflicting signal among genomic regions. Selection of different types of molecular markers from different genomic regions is required to overcome these challenges. For evolutionary studies in frogs, we introduce the publicly available FrogCap suite of genomic resources, which is a large collection of ~15,000 markers that unifies previous genetic sequencing efforts. FrogCap is designed to be modular, such that subsets of markers and SNPs can be selected based on the desired phylogenetic scale. FrogCap uses a variety of marker types that include exons and introns, ultraconserved elements, and previously sequenced Sanger markers, which span up to 10,000 bp in alignment lengths; in addition, we demonstrate potential for SNP-based analyses. We tested FrogCap using 121 samples distributed across five phylogenetic scales, comparing probes designed using a consensus- or exemplar genome-based approach. Using the consensus design is more resilient to issues with sensitivity, specificity, and missing data than picking an exemplar genome sequence. We also tested the impact of different bait kit sizes (20,020 vs. 40,040) on depth of coverage and found triple the depth for the 20,020 bait kit. We observed sequence capture success (i.e., missing data, sequenced markers/bases, marker length, and informative sites) across phylogenetic scales. The incorporation of different marker types is effective for deep phylogenetic relationships and shallow population genetics studies. Having demonstrated FrogCap's utility and modularity, we conclude that these new resources are efficacious for high-throughput sequencing projects across variable timescales.
On leaky forcing and resilience

Abstract A leak is a vertex that is not allowed to perform a force during the zero forcing process. Leaky forcing was recently introduced as a new variation of zero forcing in order to analyze how leaks in a network disrupt the zero forcing process. The l -leaky forcing number of a graph is the size of the smallest zero forcing set that can force a graph despite l leaks. A graph G is l -resilient if its zero forcing number is the same as its l -leaky forcing number. In this paper, we analyze l -leaky forcing and show that if an ( l − 1 ) -leaky forcing set B is robust enough, then B is an l -leaky forcing set. This provides the framework for characterizing l -leaky forcing sets. Furthermore, we consider structural implications of l -resilient graphs. We apply these results to bound the l -leaky forcing number of several graph families including trees, supertriangles, and grid graphs. In particular, we resolve a question posed by Dillman and Kenter concerning the upper bound on the 1-leaky forcing number of grid graphs.
Design-Driven Requirements for Computationally Co-Creative Game AI Design Tools

Game AI designers must manage complex interactions between the AI character, the game world, and the player, while achieving their design visions. Computational co-creativity tools can aid them, but first, AI and HCI researchers must gather requirements and determine design heuristics to build effective co-creative tools. In this work, we present a participatory design study that categorizes and analyzes game AI designers’ workflows, goals, and expectations for such tools. We evince deep connections between game AI design and the design of co-creative tools, and present implications for future co-creativity tool research and development.
Uniform Object Rearrangement: From Complete Monotone Primitives to Efficient Non-Monotone Informed Search

Object rearrangement is a widely-applicable and challenging task for robots. Geometric constraints must be carefully examined to avoid collisions and combinatorial issues arise as the number of objects increases. This work studies the algorithmic structure of rearranging uniform objects, where robot-object collisions do not occur but object-object collisions have to be avoided. The objective is minimizing the number of object transfers under the assumption that the robot can manipulate one object at a time. An efficiently computable decomposition of the configuration space is used to create a "region graph", which classifies all continuous paths of equivalent collision possibilities. Based on this compact but rich representation, a complete dynamic programming primitive DFS DP performs a recursive depth first search to solve monotone problems quickly, i.e., those instances that do not require objects to be moved first to an intermediate buffer. DFS DP is extended to solve single-buffer, non-monotone instances, given a choice of an object and a buffer. This work utilizes these primitives as local planners in an informed search framework for more general, non-monotone instances. The search utilizes partial solutions from the primitives to identify the most promising choice of objects and buffers. Experiments demonstrate that the proposed solution returns near-optimal paths with higher success rate, even for challenging non-monotone instances, than other leading alternatives.
Spatiotemporal Co-Dependency between Macrophages and Exhausted CD8 + T Cells in Cancer

T cell exhaustion is a major impediment to anti-tumor immunity. However, it remains elusive how other immune cells in the tumor microenvironment (TME) contribute to this dysfunctional state. Here we show that the biology of tumor-associated macrophages (TAM) and exhausted T cells (Tex) in the TME is extensively linked. We demonstrate that in vivo depletion of TAM reduces exhaustion programs in tumor-infiltrating CD8+ T cells and reinvigorates their effector potential. Reciprocally, transcriptional and epigenetic profiling reveals that Tex express factors that actively recruit monocytes to the TME and shape their differentiation. Using lattice light sheet microscopy, we show that TAM and CD8+ T cells engage in unique long-lasting antigen-specific synaptic interactions that fail to activate T cells, but prime them for exhaustion, which is then accelerated in hypoxic conditions. Spatially resolved sequencing supports a spatiotemporal self-enforcing positive feedback circuit that is aligned to protect rather than destroy a tumor.
In situ transmission electron microscopy investigation of nucleation of GP zones under natural aging in Al-Zn-Mg alloy

Abstract This investigation reveals very early-stage (within an hour) precipitation during natural-aging of Al-Zn-Mg alloy can have very complex processes with strong fluctuations in precipitate types and formation mechanisms. In situ heating followed by quenching and subsequent natural-aging at room temperature was carried inside transmission electron microscope to study the formation and evolution of early-stage precipitation. Investigation reveals formation of solute clusters at ∼2 mins and subsequent nucleation of GP-II zone adjacent to clusters at ∼10 mins during very early-stage natural-aging. Moreover, nucleation of GP-II is found to be related to GP-I but not in one unique mechanism. GP-I precipitates were observed to act as sites for the formation of GP-II either by ‘separated’ nucleation (i.e. from the interface between GP-I and Al matrix) or via in situ nucleation (i.e. from a GP-I precipitate). Occasionally, some GP-II precipitates were observed to dissolve into Al matrix without further transforming to ƞ′ precipitates.
Challenges of Numerical Simulation of Dynamic Wetting Phenomena: A Review

Abstract Wetting is fundamental to many technological applications that involve the motion of the fluid-fluid interface on a solid. While static wetting is well understood in the context of thermodynamic equilibrium, dynamic wetting is more complicated in that liquid interactions with a solid phase, possibly on molecular scales, can strongly influence the macroscopic scale dynamics. The problem with continuum models of wetting phenomena is then that they ought to be augmented with microscopic models to describe the molecular neighborhood of the moving contact line. In this review, widely used models for the computation of wetting flows are summarized first, followed by an overview of direct numerical simulations based on the Volume-of-Fluid approach. Recent developments in the Volume-of-Fluid simulations of the wetting are then reviewed, with a particular attention paid on combining macro-scale simulations with the hydrodynamic theory near the moving contact line, as well as including a microscopic description by coupling with the van der Waals interface model. Finally, the extension to modeling the contact line motion on non-flat surfaces is surveyed, followed by hot topics in nucleate boiling.
Cladribine therapy for advanced and indolent systemic mastocytosis: Mayo Clinic experience in 42 consecutive cases.

We describe our single institution experience with cladribine therapy in 42 patients with systemic mastocytosis (SM): 22 advanced (adv-SM; median age 65 years, 68% males) and 20 indolent/smouldering SM (ISM/SSM; median age 56 years, 45% males); subcategories included eight aggressive, 13 associated with another haematological neoplasm, one mast cell leukaemia, 17 ISM and three SSM. Overall/major response rates were 77%/45% for adv-SM and 70%/60% for ISM/SSM, and median (range) duration of response 10 (4-75) and 46 (4-140) months respectively. A >50% reduction in bone marrow mast cell burden and serum tryptase level was documented in 63% and 67% of patients with adv-SM and 50% and 46% with ISM/SSM respectively. The presence of KIT proto-oncogene, receptor tyrosine kinase (KIT)D816V predicted response in adv-SM: 17 (90%) of 19 with and none of three without the mutation responded (P < 0·01). Treatment-emergent adverse events were mostly limited to transient cytopenias: Grade 3/4 neutropenia, thrombocytopenia, or lymphopenia occurred in 27%, 27% and 27% of patients with adv-SM, and 5%, 5% and 30% with ISM/SSM respectively. The present study provides practical information that might be considered when making treatment choices between cladribine and newer KIT-targeted therapies and identifies the absence of KITD816V as a potential marker of cladribine resistance in advanced SM; the latter observation needs confirmation in a larger study.
FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers

Federated learning (FL) involves training a model over massive distributed devices, while keeping the training data localized and private. This form of collaborative learning exposes new tradeoffs among model convergence speed, model accuracy, balance across clients, and communication cost, with new challenges including: (1) straggler problem---where clients lag due to data or (computing and network) resource heterogeneity, and (2) communication bottleneck---where a large number of clients communicate their local updates to a central server and bottleneck the server. Many existing FL methods focus on optimizing along only one single dimension of the tradeoff space. Existing solutions use asynchronous model updating or tiering-based, synchronous mechanisms to tackle the straggler problem. However, asynchronous methods can easily create a communication bottleneck, while tiering may introduce biases that favor faster tiers with shorter response latencies. To address these issues, we present FedAT, a novel Federated learning system with Asynchronous Tiers under Non-i.i.d. training data. FedAT synergistically combines synchronous, intra-tier training and asynchronous, cross-tier training. By bridging the synchronous and asynchronous training through tiering, FedAT minimizes the straggler effect with improved convergence speed and test accuracy. FedAT uses a straggler-aware, weighted aggregation heuristic to steer and balance the training across clients for further accuracy improvement. FedAT compresses uplink and downlink communications using an efficient, polyline-encoding-based compression algorithm, which minimizes the communication cost. Results show that FedAT improves the prediction performance by up to 21.09% and reduces the communication cost by up to 8.5×, compared to state-of-the-art FL methods.
Conflict-Averse Gradient Descent for Multi-task learning

The goal of multi-task learning is to enable more efficient learning than single task learning by sharing model structures for a diverse set of tasks. A standard multi-task learning objective is to minimize the average loss across all tasks. While straightforward, using this objective often results in much worse final performance for each task than learning them independently. A major challenge in optimizing a multi-task model is the conflicting gradients, where gradients of different task objectives are not well aligned so that following the average gradient direction can be detrimental to specific tasks' performance. Previous work has proposed several heuristics to manipulate the task gradients for mitigating this problem. But most of them lack convergence guarantee and/or could converge to any Pareto-stationary point. In this paper, we introduce Conflict-Averse Gradient descent (CAGrad) which minimizes the average loss function, while leveraging the worst local improvement of individual tasks to regularize the algorithm trajectory. CAGrad balances the objectives automatically and still provably converges to a minimum over the average loss. It includes the regular gradient descent (GD) and the multiple gradient descent algorithm (MGDA) in the multi-objective optimization (MOO) literature as special cases. On a series of challenging multi-task supervised learning and reinforcement learning tasks, CAGrad achieves improved performance over prior state-of-the-art multi-objective gradient manipulation methods.
Frequent paternal mitochondrial inheritance and rapid haplotype frequency shifts in copepod hybrids.

Mitochondria are assumed to be maternally inherited in most animal species, and this foundational concept has fostered advances in phylogenetics, conservation, and population genetics. Like other animals, mitochondria were thought to be solely maternally inherited in the marine copepod Tigriopus californicus, which has served as a useful model for studying mitonuclear interactions, hybrid breakdown, and environmental tolerance. However, we present PCR, Sanger sequencing, and Illumina Nextera sequencing evidence that extensive paternal mitochondrial DNA (mtDNA) transmission is occurring in inter-population hybrids of T. californicus. PCR on four types of crosses between three populations (total sample size of 376 F1 individuals) with 20% genome-wide mitochondrial divergence showed 2% to 59% of F1 hybrids with both paternal and maternal mtDNA, where low and high paternal leakage values were found in different cross directions of the same population pairs. Sequencing methods further verified nucleotide similarities between F1 mtDNA and paternal mtDNA sequences. Interestingly, the paternal mtDNA in F1s from some crosses inherited haplotypes that were uncommon in the paternal population. Compared to some previous research on paternal leakage, we employed more rigorous methods to rule out contamination and false detection of paternal mtDNA due to non-functional nuclear mitochondrial DNA fragments. Our results raise the potential that other animal systems thought to only inherit maternal mitochondria may also have paternal leakage, which would then affect the interpretation of past and future population genetics or phylogenetic studies that rely on mitochondria as uniparental markers.
Truly two-dimensional black holes under dimensional transitions of spacetime

A sufficiently massive star in the end of its life will inevitably collapse into a black hole as more deconfined degrees of freedom make the core ever softer. One possible way to avoid the singular...
Driven-dissipative ising model: Dynamical crossover at weak dissipation

Driven quantum systems coupled to an environment typically exhibit effectively thermal behavior with relaxational dynamics near criticality. However, a different qualitative behavior might be expected in the weakly dissipative limit due to the competition between coherent dynamics and weak dissipation. In this work, we investigate a driven-dissipative infinite-range Ising model in the presence of individual atomic dissipation, a model that emerges from the paradigmatic open Dicke model in the large-detuning limit. We show that the system undergoes a dynamical crossover from relaxational dynamics, with a characteristic dynamical exponent $\zeta=1/2$, to underdamped critical dynamics governed by the exponent $\zeta=1/4$ in the weakly dissipative regime; a behavior that is markedly distinct from that of equilibrium. Finally, utilizing an exact diagrammatic representation, we demonstrate that the dynamical crossover to underdamped criticality is not an artifact of the mean-field nature of the model and persists even in the presence of short-range perturbations.
The Harish-Chandra integral: An introduction with examples

This expository paper introduces the theory of Harish-Chandra integrals, a family of special functions that express the integral of an exponential function over the adjoint orbits of a compact Lie group. Originally studied in the context of harmonic analysis on Lie algebras, Harish-Chandra integrals now have diverse applications in many areas of mathematics and physics. We review a number of these applications, present several different proofs of Harish-Chandra's celebrated exact formula for the integrals, and give detailed derivations of the specific integral formulae for all compact classical groups. These notes are intended for mathematicians and physicists who are familiar with the basics of Lie groups and Lie algebras but who may not be specialists in representation theory or harmonic analysis.
Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.
Liouville Operators over the Hardy Space

Abstract The role of Liouville operators in the study of dynamical systems through the use of occupation measures have been an active area of research in control theory over the past decade. This manuscript investigates Liouville operators over the Hardy space, which encode complex ordinary differential equations in an operator over a reproducing kernel Hilbert space.
Zug- und Scherverhalten der Laminatschichten

Eine grundlegende Materialcharakterisierung von kontinuierlich faserverstarkten Verbunden zielt auf die Festlegung der inneren elastischen Eigenschaften sowie Festigkeitseigenschaften und thermischer Ausdehnungscharakteristik der, ein multidirektionales Laminat bildenden Teile, den Schichten. In diesem Kapitel sowie Kapitel 6 bis 9 werden Verfahren zur Bestimmung der inneren mechanischen Eigenschaften und thermischen Ausdehnungseigenschaften, als auch die entsprechenden Auswerteverfahren beschrieben.
Áreas de alta vulnerabilidad ambiental en América Latina y el Caribe: una perspectiva regional a escala subnacional

En el presente articulo se distinguen areas de alta vulnerabilidad ambiental en America Latina y el Caribe mediante un analisis exploratorio a escala subnacional, basado en la distincion de dos planos de vulnerabilidad: externo e interno. La integracion de tres bases de datos espaciales –sobre desastres naturales, poblacion y pobreza— en un sistema de informacion geografica permitio identificar areas de alta vulnerabilidad, el tamano y la distribucion de la poblacion de cada una de ellas y la existencia de diferentes niveles de pobreza. Los resultados muestran una gran heterogeneidad entre paises y dentro de ellos, lo que destaca la importancia de considerar diferentes escalas espaciales en el analisis de la vulnerabilidad ambiental
Kinetic mechanism of the DNA-dependent DNA polymerase activity of human immunodeficiency virus reverse transcriptase.

Abstract The kinetic pathway of DNA-dependent DNA polymerase activity of human immunodeficiency virus reverse transcriptase (HIV RT) as determined by pre-steady-state methods using a defined primer/template is as follows, [formula: see text] where E is RT, Dn,n+1 is primer/template, dNTP is deoxyribonucleoside triphosphate, and PPi is pyrophosphate. The rate-determining step for enzyme turnover in single nucleotide addition is the dissociation of enzyme from DNA (k6 = 0.11 s-1). The observation of an E'.DNA.dNTP intermediate by pulse-chase analysis and the absence of a phosphorothioate elemental effect identified the rate-limiting step for nucleotide addition as a conformational change of the E.DNA.dNTP complex (k3 = 83 s-1) prior to the chemical step. Biphasic kinetics of single-turnover pyrophosphorolysis suggested that this conformational change (k-3 = 0.3 s-1) is also rate-limiting for the reverse reaction. The equilibrium constant for the chemical step (K4) is 3.8, in slight favor of the forward reaction. The large equilibrium constant (K3 = 280) for the conformational change effectively renders nucleotide addition kinetically irreversible. The dissociation constant for primer/template is 26 nM, and the association rate of enzyme and DNA (k1) is 2.3 x 10(6) M-1 s-1. Equilibrium dissociation constants for dTTP and PPi are 18 microM and 7.2 mM, respectively. Mg2+ enhances productive interaction of RT with DNA as judged by a 50% increase in burst amplitude in the single nucleotide addition reaction and by an 8-fold decrease in KD for the RT.DNA complex as determined by gel mobility shift assay. Secondary interactions of the RT.DNA complex with free DNA were observed in the absence of Mg2+.
Enhancing the Accounting Major with Online Learning

Accounting majors who wish to be successful in life must learn to acquire knowledge using all kinds of platforms. The belief that the only way people can learn is by classroom instruction is not supported by research. The authors show how online learning is an important tool for achieving the various goals of accounting education that should include creativity, collaboration, communication, critical thinking and problem solving. The authors conclude that the optimal method to teach accounting is by combining face-to-face learning with on-line learning.
POP: Preoperative Planning and Simulation Software for Total Hip Replacement Surgery

Proper implant placement during total hip replacement (THR) surgery has been shown to reduce short and long term complication including dislocations, accelerated wear, and loosening of the implants. Correct implant orientation is the most important factor in preventing impingement, which is a major cause of dislocation and wear following total hip replacement surgery. However, proper implant orientation is also dependent upon patient-specific factors such as pelvic anatomy bone coverage and level of femoral osteotomy, and can affect leg lengths and offsets. This paper describes a preoperative planner for THR that enables the surgeon to determine the optimal placement of the femoral and acetabular components for THR taking all of these factors into account. Coupled with a computer-assisted clinical system for precise implant positioning, this approach could significantly improve patient outcomes and lower costs.
LONG-PULSE NEUTRAL INJECTOR DEVELOPMENT AT THE LAWRENCE BERKELEY LABORATORY*

ABSTRACT The program elements for the development of long-pulse deuterium accelerators for neutral-beam injection into fusion plasmas are described. Operational characteristics of a 4-grid, 80-kV, 40-A accelerator, designed for 30-sec operation but limited to 800 msec operation by the test facility, are presented. These pulses are long enough to establish thermal equilibrium of the accelerator grids. Beam divergences of 1.0° × 0.4° have been achieved at 80 kV, 36 A for deuterium; 0.44° × 1.0° at 80 kV, 47 A for hydrogen. Measured heat loads on each grid are of the order of 0.5% of the beam power.
Approach and avoidance motivation.

In this article, we introduce this special issue by establishing a conceptual foundation for the distinction between approach and avoidance motivation. We do so primarily by explicating several reasons why the approach–avoidance distinction should be viewed as fundamental and basic to the study of human behavior. In addition, we compare and contrast the “approach–avoidance” designation with other designations that have been used in the motivational literature to cover the same or similar conceptual ground. Finally, we conclude by briefly overviewing the other contributions to this special issue, specifically highlighting how they make use of the approach–avoidance distinction.
Probabilistic promotion revisited

Promotion is the relation between an act and a desire that obtains when the act advances or serves the desire. Under what conditions does an act promote a desire? Probabilistic accounts of promotion, the most prominent accounts, analyze promotion in terms of an increase in the probability of the desire’s satisfaction. In this paper, we clarify the promotion relation and explain why probabilistic accounts are attractive. Then we identify two questions probabilistic accounts must answer: the Baseline Question and the Interpretation Question. We discuss and reject the three answers to the Baseline Question found in the literature, and explain the challenge future attempts at answering this question will face. Proponents of probabilistic accounts have not adequately addressed the Interpretation Question. We survey three answers to this question, finding each unsatisfactory. We conclude that no satisfactory probabilistic account has yet been offered, and that there are significant hurdles to providing one in the future.
"Does Ketamine Have Rapid Anti-Suicidal Ideation Effects?"

Suicide is defined as an act of violence toward oneself with the intention to die. Suicide completion is a prominent cause of worldwide mortality and its prevention poses a major challenge to the psychiatric and world health communities. The Centers for Disease Control and Prevention (CDC) reported that as of 2013, suicide was the 10th major cause of death – totaling 41,149 deaths in the United States (US) (Centers for Disease Control and Prevention, CDC)[1]. Despite a growing armamentarium of the psychiatric medications to treat mood disorders, effective pharmacologic interventions for suicidality continue to elude us. Statistics demonstrate no meaningful decrease in the rate of suicide [2, 3]. In fact, within the US, there has been an alarming 28.4% increase in the age-adjusted suicide rates (from 13.7 to 17.6 per 100, 000) for adults aged 35–64 years between 1999 and 2010 (CDC [4]), as well as a 2.4% increase in the age-adjusted death rate due to suicide in 2012 compared to 2011[5]. Suicide is a multi-factorial phenomenon and our current nosology addresses it within symptom components of other psychiatric conditions exclusively. Almost 90% of suicide cases are associated with some form of psychiatric illness, chiefly Major Depressive Disorder (MDD), Psychotic Disorders, or Borderline Personality Disorder [2]. The new DSM-5 Task Force and work groups recognized an emerging need for the investigation of suicidality as an independent phenomenon. To stimulate thinking along these lines, a new category “suicidal behavior disorder” was added to the manual under “Conditions for Further Study”[6]. Recent guidelines from the National Alliance for Suicide Prevention Research Task Force outline priority questions to guide current and future research on suicide. Paramount among this research agenda is defining the etiology of suicide with the aim of increasing detection and accurately predicting suicide risk to provide effective preventive services and interventions. In this review, we will describe current treatment approaches to suicidality and summarize the existing literature on ketamine as a potential treatment candidate. We will consider clinical trial data concerning the rapid antidepressant effects of ketamine in mood disorders, as well as the strength of evidence for ketamine’s anti-suicidal effect beyond its antidepressant actions. The neurobiology of suicide, including the role of glutamate, will be discussed.
Symplectic integrators for the multilevel Redfield equation

Abstract We develop a method for solving the Redfield equation using symplectic integrators (SI). We show how the Redfield equation for a reduced density matrix of a multi-level system interacting with a thermal bath can be rewritten in a symplectic form so that numerical algorithms used in classical mechanics can readily be applied. The symplectic structure of the Redfield equation is established for a superoperator which is complex, non-Hermitian, and explicitly time-dependent in some cases. The efficiency of several SI schemes are studied and compared for a model dissipative system: electron transfer coupled to a vibrational mode and a thermal bath.
Regulation of Messenger Ribonucleic Acid Levels for Five Urea Cycle Enzymes in Cultured Rat Hepatocytes. Requirements for Cyclic Adenosine Monophosphate, Glucocorticoids, and Ongoing Protein Synthesis

In adult rat liver, amounts of the urea cycle enzymes are regulated by diet, glucocorticoids, and cAMP. Rat hepatocytes cultured in chemically defined medium were used to precisely define the roles of glucocorticoids and cAMP in regulation of these enzymes at the pretranslational level. With the exception of ornithine transcarbamylase mRNA, cultured rat hepatocytes retain the capacity to express mRNAs for the urea cycle enzymes at the same level observed for liver of intact rats. In the absence of added hormones, mRNAs for argininosuccinate synthetase and argininosuccinate lyase remained at or above normal in vivo levels, while mRNAs for the other three enzymes declined to very low levels. Messenger RNAs for carbamyl phosphate synthetase I, argininosuccinate synthetase, argininosuccinate lyase, and arginase increased in response to either dexamethasone or 8-(4-chlorophenylthio) cAMP (CPT-cAMP). Half-maximal responses occurred at 2-3 nM dexamethasone and at 2-7 microM CPT-cAMP. Cycloheximide abolished the response to dexamethasone but not to CPT-cAMP, suggesting that dexamethasone induced expression of an intermediate gene product required for induction of these mRNAs. The effects of a combination of both hormones were additive for argininosuccinate lyase mRNA and synergistic for carbamyl phosphate synthetase I, argininosuccinate synthetase, and arginase mRNAs. Messenger RNA for ornithine transcarbamylase showed little or no response to any condition tested. Depending on the particular mRNA and hormonal condition tested, increases in mRNA levels ranged from 1.4- to 70-fold above control values.(ABSTRACT TRUNCATED AT 250 WORDS)
Rayleigh and predissociative fluorescence imaging of densities from an internal combustion engine using a tunable KrF laser

We apply light scattering to the production of species-, space-, and time-resolved images from a Sandia transparent engine, which operates with propane and air. By appropriate tuning of our KrF laser, and by treating the scattered light with an appropriate filter, we can image (a) the total density (and thus the temperature), via Rayleigh scattering, and (b) densities of OH, and of hot O2 (i.e., vibrational states 6 and 7) via laser-induced fluorescence.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
(Solid + liquid) phase equilibria and solid-compound formation in 1,2-dimethoxyethane + tetrachloromethane, + trichlorofluoromethane, and + trichloromethane

Abstract (Solid + liquid) phase diagrams have been constructed for 1,2-dimethoxyethane + tetrachloromethane, + trichlorofluoromethane, and + trichloromethane. Solid addition compounds form with the empirical formulae: C 4 H 10 O 2 ·(CCl 4 ) 2 , C 4 H 10 O 2 ·(CFCl 3 ) 2 , C 4 H 10 O 2 ·(CFCl 3 ) 4 , C 4 H 10 O 2 ·CHCl 3 , and C 4 H 10 O 2 ·(CHCl 3 ) 2 , although the composition of the second compound with CFCl 3 is not certain. The C 4 H 10 O 2 ·(CHCl 3 ) 2 is interesting in that a metastable form can be made to crystallize from solution. Compound formation is attributed to a charge-transfer interaction in the first two mixtures and to hydrogen bonding in the last.
Growing Embedded Librarians like Kudzu: How the Embedded Extension Service Creates More Embedded Librarians without Creating New Positions

In an era of exploding online enrollment and tight budgets, Central Piedmont Community College (CPCC) struggles to meet the needs of online students. CPCC librarians went one step towards solving that problem in 2009–2010 by launching an embedded librarian program. CPCC's program became so successful that it struggled to meet demand. In 2013, CPCC Libraries reached out to nearby MLIS program at The University of North Carolina at Greensboro (UNCG) to create a project that links this demand with a creative solution: the Embedded Extension Service (EES). Student interns from UNCG are trained in embedded librarianship practices and tools while providing reference services to CPCC online classes. EES is 100% online, making it easier for students to participate from anywhere. This is beneficial for both schools because CPCC is able to offer embedded services to more classes and UNCG is able to facilitate practical, real world experience for budding librarians.
Environmental assessment of plug-in hybrid electric vehicles using naturalistic drive cycles and vehicle travel patterns: A Michigan case study

Plug-in hybrid electric vehicles (PHEVs) use grid electricity as well as on-board gasoline for motive force. These multiple energy sources make prediction of PHEV energy consumption challenging and also complicate evaluation of their environmental impacts. This paper introduces a novel PHEV energy consumption modeling approach and compares it to a second approach from the literature, each using actual trip patterns from the 2009 National Household Travel Survey (NHTS). The first approach applies distance-dependent fuel efficiency and on-road electricity consumption rates based on naturalistic or real world, driving information to determine gasoline and electricity consumption. The second uses consumption rates derived in accordance with government certification testing. Both approaches are applied in the context of a location-specific case study that focuses on the state of Michigan. The two PHEV models show agreement in electricity demand due to vehicle charging, gasoline consumption, and life cycle environmental impacts for this case study. The naturalistic drive cycle approach is explored as a means of extending location-specific driving data to supplement existing PHEV impact assessments methods.
Theory and opposed-systems design:

I. Madness in Methodology? When, after nearly a decade of study and work in the field, I left mathematical logic and the logic of science, I made a resolution not to write papers on the methodology or logic of social science-for fear I would never learn any social science. It was all too easy at the time to publish applications of Boolean algebra or the calculus of relations or the like that could just conceivably be relevant to some future empirical study, in, say, economics. But I had the uneasy feeling that in offering guides for new approaches to social science, I might never approach very closely myself. And I did want to learn something of the facts of life and the substantive issues whose powerful interest had dragged me away from the more chaste attractions of logic. I also had an uncomfortable suspicion that the devastating remark of the great French mathematician, Henri Poincare, about sociology ("The most methods, and the least results") might only too accurately describe the way one might dally in the approach to any social science in order to avoid actually going in and getting lost in a very dense jungle. Maps, brochures, the purchase of compasses, machetes, bush jackets, and rakish tropical helmets can be used as a