cssi/SciSciGPT-SciSciNet huggingface dataset:
β-HPV 8E6 Attenuates ATM and ATR Signaling in Response to UV Damage

Given the high prevalence of cutaneous genus beta human papillomavirus (β-HPV) infections, it is important to understand how they manipulate their host cells. This is particularly true for cellular responses to UV damage, since our skin is continually exposed to UV. The E6 protein from β-genus HPV (β-HPV E6) decreases the abundance of two essential UV-repair kinases (ATM and ATR). Although β-HPV E6 reduces their availability, the impact on downstream signaling events is unclear. We demonstrate that β-HPV E6 decreases ATM and ATR activation. This inhibition extended to XPA, an ATR target necessary for UV repair, lowering both its phosphorylation and accumulation. β-HPV E6 also hindered POLη accumulation and foci formation, critical steps in translesion synthesis. ATM's phosphorylation of BRCA1 is also attenuated by β-HPV E6. While there was a striking decrease in phosphorylation of direct ATM/ATR targets, events further down the cascade were not reduced. In summary, despite being incomplete, β-HPV 8E6's hindrance of ATM/ATR has functional consequences.
A-sequences, Z-sequence, and B-sequences of Riordan matrices

Abstract We define two type B -sequences of Riordan arrays and present the A -sequence characterization and Z -sequence characterization of the Riordan matrices with two type B -sequences. The subgroups characterized by A -sequences and Z -sequences are studied. The application of the sequence characterization to the RNA type matrices is discussed. Finally, we investigate the A - and B -sequences of the Pascal like Riordan matrices.
Loss of the Krüppel-like factor 4 tumor suppressor is associated with epithelial-mesenchymal transition in colorectal cancer.

Aim Colorectal cancer (CRC) is the third leading cancer-related cause of death due to its propensity to metastasize. Epithelial-mesenchymal transition (EMT) is a multistep process important for invasion and metastasis of CRC. Kruppel-like factor 4 (KLF4) is a zinc finger transcription factor highly expressed in differentiated cells of the intestinal epithelium. KLF4 has been shown to play a tumor suppressor role during CRC tumorigenesis - its loss accelerates development and progression of cancer. The present study examined the relationship between KLF4 and markers of EMT in CRC. Methods Immunofluorescence staining for KLF4 and EMT markers was performed on archived patient samples after colorectal cancer resection and on colonic tissues of mice with colitis-associated cancer. Results We found that KLF4 expression is lost in tumor sections obtained from CRC patients and in those of mouse colon following azoxymethane and dextran sodium sulfate (AOM/DSS) treatment when compared to their respective normal appearing mucosa. Importantly, in CRC patient tumor sections, we observed a negative correlation between KLF4 levels and mesenchymal markers including TWIST, β-catenin, claudin-1, N-cadherin, and vimentin. Similarly, in tumor tissues from AOM/DSS-treated mice, KLF4 levels were negatively correlated with mesenchymal markers including SNAI2, β-catenin, and vimentin and positively correlated with the epithelial marker E-cadherin. Conclusion These findings suggest that the loss of KLF4 expression is a potentially significant indicator of EMT in CRC.
Towards Dynamic Simulation Guided Optimal Design of Tumbling Microrobots

Design of robots at the small scale is a trial-and-error based process, which is costly and time-consuming. There are no good dynamic simulation tools to predict the motion or performance of a microrobot as it moves against a substrate. At smaller length scales, the influence of adhesion and friction, which scales with surface area, becomes more pronounced. Thus, rigid body dynamic simulators, which implicitly assume that contact between two bodies can be modeled as point contact are not suitable. In this paper, we present techniques for simulating the motion of microrobots where there can be intermittent and non-point contact between the robot and the substrate. We use this simulator to study the motion of microrobots of different shapes and select shapes that are most promising for performing a given task.
A Strategic Approach for Fluorescence Imaging of Membrane Proteins in a Native-like Environment.

Summary Biological membranes are complex barriers in which membrane proteins and thousands of lipidic species participate in structural and functional interactions. Developing a strategic approach that allows uniform labeling of membrane proteins while maintaining a lipidic environment that retains functional interactions is highly desirable for in vitro fluorescence studies. Herein, we focus on complementing current methods by integrating the powerful processes of unnatural amino acid mutagenesis, bioorthogonal labeling, and the detergent-free membrane protein solubilization based on the amphiphilic styrene-maleic acid (SMA) polymer. Importantly, the SMA polymer preserves a thermodynamically stable shell of phospholipids. The approach that we present is both rapid and generalizable providing a population of uniquely labeled membrane proteins in lipid nanoparticles for quantitative fluorescence-based studies.
Building Consistent Transactions with Inconsistent Replication

Application programmers increasingly prefer distributed storage systems with strong consistency and distributed transactions (e.g., Google’s Spanner) for their strong guarantees and ease of use. Unfortunately, existing transactional storage systems are expensive to use—in part, because they require costly replication protocols, like Paxos, for fault tolerance. In this article, we present a new approach that makes transactional storage systems more affordable: We eliminate consistency from the replication protocol, while still providing distributed transactions with strong consistency to applications. We present the Transactional Application Protocol for Inconsistent Replication (TAPIR), the first transaction protocol to use a novel replication protocol, called inconsistent replication, that provides fault tolerance without consistency. By enforcing strong consistency only in the transaction protocol, TAPIR can commit transactions in a single round-trip and order distributed transactions without centralized coordination. We demonstrate the use of TAPIR in a transactional key-value store, TAPIR-KV. Compared to conventional systems, TAPIR-KV provides better latency and better throughput.
Devaluation, Relative Prices, and International Trade; Evidence From Developing Countries

Devaluation is an integral part of adjustment in many developing countries, particularly relied upon by countries facing large external imbalances. A devaluation can only reduce trade imbalances if it translates to a real devaluation and if trade flows respond to relative prices in a sig nificant and predictable manner. However, a recent strand in the empirical trade literature has questioned the existence of a stable relationship between trade flows and its traditional determinants. This paper re-examines the relationship between relative prices and imports and exports in a sample of 12 developing countries.
Distilling Effective Supervision From Severe Label Noise

Collecting large-scale data with clean labels for supervised training of neural networks is practically challenging. Although noisy labels are usually cheap to acquire, existing methods suffer a lot from label noise. This paper targets at the challenge of robust training at high label noise regimes. The key insight to achieve this goal is to wisely leverage a small trusted set to estimate exemplar weights and pseudo labels for noisy data in order to reuse them for supervised training. We present a holistic framework to train deep neural networks in a way that is highly invulnerable to label noise. Our method sets the new state of the art on various types of label noise and achieves excellent performance on large-scale datasets with real-world label noise. For instance, on CIFAR100 with a 40% uniform noise ratio and only 10 trusted labeled data per class, our method achieves 80.2% classification accuracy, where the error rate is only 1.4% higher than a neural network trained without label noise. Moreover, increasing the noise ratio to 80%, our method still maintains a high accuracy of 75.5%, compared to the previous best accuracy 48.2%.
Commensurability growth of branch groups

Fixing a subgroup $\Gamma$ in a group $G$, the commensurability growth function assigns to each $n$ the cardinality of the set of subgroups $\Delta$ of $G$ with $[\Gamma: \Gamma \cap \Delta][\Delta : \Gamma \cap \Delta] = n$. For pairs $\Gamma \leq A$, where $A$ is the automorphism group of a $p$-regular tree and $\Gamma$ is finitely generated, we show that this function can take on finite, countable, or uncountable cardinals. For almost all known branch groups $\Gamma$ (the first Grigorchuk group, the twisted twin Grigorchuk group, Pervova groups, Gupta-Sidki groups, etc.) acting on $p$-regular trees, this function is precisely $\aleph_0$ for any $n = p^k$.
Electric vehicle charging during the day or at night? A perspective on carbon emissions

We propose an emission-oriented charging scheme to evaluate the emissions of electric vehicle (EV) charging from the electricity sector at the region of Electric Reliability Council of Texas (ERCOT). We investigate both day- and night-charging scenarios combined with realistic system load demand under the emission-oriented vs direct charging schemes. Our emission-oriented charging scheme reduces carbon emissions in the day by 13.8 % on average. We also find that emission-oriented charging results in a significant CO 2 reduction in 30% of the days in a year compared with direct charging. Apart from offering a flat rebate for EV owners, our analysis reveals that certain policy incentives (e.g. pricing) regarding EV charging should be taken into account in order to reflect the benefits of emissions reduction that haven't been incorporated in the current market of electricity transactions.
Knowledge or Abilities? How Undergraduates Define Intelligence.

Our results show that undergraduates define intelligence in different ways, and these definitions are not necessarily stable across contexts or over time. Further, these definitions likely impact h...
The Histone Methyltransferase G9a Promotes Cholangiocarcinogenesis through Regulation of the Hippo Pathway Kinase LATS2 and YAP Signaling Pathway.

Background and aims Cholangiocarcinoma (CCA) is a highly malignant epithelial tumor of the biliary tree with poor prognosis. In the current study, we present evidence that the histone-lysine methyltransferase G9a is up-regulated in human CCA and that G9a enhances CCA cell growth and invasiveness through regulation of the Hippo pathway kinase large tumor suppressor 2 (LATS2) and yes-associated protein (YAP) signaling pathway. Approach and results Kaplan-Meier survival analysis revealed that high G9a expression is associated with poor prognosis of CCA patients. In experimental systems, depletion of G9a by small interfering RNA/short hairpin RNA or inhibition of G9a by specific pharmacological inhibitors (UNC0642 and UNC0631) significantly inhibited human CCA cell growth in vitro and in severe combined immunodeficient mice. Increased G9a expression was also observed in mouse CCA induced by hydrodynamic tail vein injection of notch intracellular domain (NICD) and myr-Akt. Administration of the G9a inhibitor UNC0642 to NICD/Akt-injected mice reduced the growth of CCA, in vivo. These findings suggest that G9a inhibition may represent an effective therapeutic strategy for the treatment of CCA. Mechanistically, our data show that G9a-derived dimethylated H3K9 (H3K9me2) silenced the expression of the Hippo pathway kinase LATS2, and this effect led to subsequent activation of oncogenic YAP. Consequently, G9a depletion or inhibition reduced the level of H3K9me2 and restored the expression of LATS2 leading to YAP inhibition. Conclusions Our findings provide evidence for an important role of G9a in cholangiocarcinogenesis through regulation of LATS2-YAP signaling and suggest that this pathway may represent a potential therapeutic target for CCA treatment.
A global sensitivity analysis and reduced-order models for hydraulically fractured horizontal wells

Several factors affect the performance and stimulation design of hydraulically fractured wells. Moreover, the dominant factors vary for different quantities of interest, and vary based on the spatial location and with the time of interest. Thus, it will be beneficial if there is a systematic procedure to identify the dominant factors affecting the quantities of interest. To this end, we present a systematic global sensitivity analysis using the Sobol method which can be utilized to rank the variables that affect two quantity of interests—pore pressure depletion and stress change—around a hydraulically fractured horizontal well based on their degree of importance. These variables include rock properties and stimulation design variables. A fully coupled poroelastic hydraulic fracture model is used to account for pore pressure and stress changes due to production. To ease the computational cost of a simulator, we also provide reduced-order models (ROMs), which can be used to replace the complex numerical model with a rather simple analytical model, for calculating the pore pressure and stresses at different locations around hydraulic fractures. The two main reasons for choosing the Sobol method are that it can capture the individual and interaction effects of input variables on the variance of outputs (which is not the case with local sensitivity analysis techniques). It also furnishes a systematic procedure with strong mathematical underpinning to generate ROMs for various quantities of interests for a given mathematical model and for a given set of input variables. The main findings of this research are as follows: (i) mobility, production pressure, and fracture half-length are the main contributors to the changes in the quantities of interest. The percentage of the contribution of each parameter depends on the location with respect to pre-existing hydraulic fractures and the quantity of interest. (ii) As time progresses, the effect of mobility decreases and the effect of production pressure increases. (iii) These two variables are also dominant for horizontal stresses at large distances from hydraulic fractures. (iv) At zones close to hydraulic fracture tips or inside the spacing area, other parameters such as fracture spacing and half-length are the dominant factors that affect the minimum horizontal stress. The results of this study will provide useful guidelines for the stimulation design of legacy wells and secondary operations such as refracturing and infill drilling.
Locally CR spherical three manifolds

Every open and orientable three manifold has a CR structure which is locally equivalent to the standard CR structure on $S^3$.
High-field spatial imaging of charge transport in silicon at low temperature

We present direct imaging measurements of charge transport across a 1 cm × 1 cm × 4 mm-thick crystal of high purity silicon (∼15 kΩ-cm) at temperatures of 5 K and 500 mK. We use these data to measure lateral diffusion of electrons and holes as a function of the electric field applied along the [111] crystal axis and to verify our low-temperature Monte Carlo software. The range of field strengths in this paper exceed those used in our previous study [R. A. Moffatt et al., Appl. Phys. Lett. 114, 032104 (2019)] by a factor of 10 and now encompass the region in which some recent silicon dark matter detectors operate [R. Agnese et al., Phys. Rev. Lett. 121, 051301 (2018)]. We also report on a phenomenon of surface charge trapping, which can reduce expected charge collection.
Overview of Vocational Rehabilitation Data about People with Visual Impairments: Demographics, Services, and Long-Run Labor Market Trends:

Introduction:This study describes the characteristics of, services received by, and labor market outcomes of applicants with visual impairments to three state vocational rehabilitation programs. Ou...
Social media surveillance for perceived therapeutic effects of cannabidiol (CBD) products.

Abstract Background CBD products have risen in popularity given CBD's therapeutic potential and lack of legal oversight, despite lacking conclusive scientific evidence for widespread over-the-counter usage for many of its perceived benefits. While medical evidence is being generated, social media surveillance offers a fast and inexpensive alternative to traditional surveys in ascertaining perceived therapeutic purposes and modes of consumption for CBD products. Methods We collected all comments from the CBD subreddit posted between January 1 and April 30, 2019 as well as comments submitted to the FDA regarding regulation of cannabis-derived products and analyzed them using a rule-based language processing method. A relative ranking of popular therapeutic uses and product groups for CBD is obtained based on frequency of pattern matches including precise queries that entail identifying mentions of the condition, a CBD product, and some “trigger” phrase indicating therapeutic use. We validated the social media-based findings using a similar analysis on comments to the U.S. Food and Drug Administration's (FDA) 2019 request-for-comments on cannabis-derived products. Results CBD is mostly discussed as a remedy for anxiety disorders and pain and this is consistent across both comment sources. Of comments posted to the CBD subreddit during the monitored time span, 6.19% mentioned anxiety at least once with at least 6.02% of these comments specifically mentioning CBD as a treatment for anxiety (i.e., 0.37% of total comments). The most popular CBD product group is oil and tinctures. Conclusion Social media surveillance of CBD usage has the potential to surface new therapeutic use-cases as they are posted. Contemporary social media data indicate, for example, that stress and nausea are frequently mentioned as therapeutic use cases for CBD without corresponding evidence, that affirms or denies, in the research literature. However, the abundance of anecdotal claims warrants serious scientific exploration moving forward. Meanwhile, as FDA ponders regulation, our effort demonstrates that social data offers a convenient affordance to surveil for CBD usage patterns in a way that is fast and inexpensive and can inform conventional electronic surveys.
Data analysis implications of moderately eccentric gravitational waves

While the expectation is that the majority of gravitational wave events observable by ground-based detectors will be emitted by compact binaries in quasi-circular orbits, the growing number of detections suggests the possibility of detecting waves from binaries with non-negligible orbital eccentricity in the near future. Several gravitational wave models incorporate the effects of small orbital eccentricities ($e \lesssim 0.2$), but these models may not be sufficient to analyze waves from systems with moderate eccentricity. We recently developed a gravitational wave model that faithfully accounts for eccentric corrections in the moderate eccentricity regime ($e \lesssim 0.8$ for certain source masses) at 3rd post-Newtonian order. Here we consider the data analysis implications of this particular waveform model by producing and analyzing posteriors via Markov Chain Monte Carlo methods. We find that the accuracy to which eccentricity and source masses can be measured can increase by 2 orders of magnitude with increasing eccentricity of the signal. We also find that signals with low eccentricity can be confidently identified as eccentric as soon as their eccentricity exceeds 0.008 (0.05) for low (high) mass systems, suggesting eccentric detections are likely to come first from low-mass systems. We complete our analysis by investigating the systematic (mismodeling) error inherent in our post-Newtonian model, finding that for signals with a signal-to-noise ratio of 15, the systematic error is below the statistical error for eccentricities as high as 0.8 (0.5) for low (high) mass systems. We also investigate the systematic error that arises from using a model that neglects eccentricity when the signal is truly eccentric, finding that the systematic error exceeds the statistical error in mass for eccentricities as small as 0.02. As a byproduct of this work we also present some new measures of the accuracy of our model, and investigate the efficiency of the model.
Regional convergence-and divergence-in the US

Abstract Previous studies on regional convergence in the US have employed varied methodologies and yielded different conclusions. Some authors report evidence that convergence has grown stronger in recent decades, while others find recent years have seen an end to convergence. We test for convergence with a method that allows for structural change. We find, first, that there is little overall evidence for convergence within the US. Results also indicate a series of positive breaks in the 1980s, indicating movement away from convergence was pronounced during this decade. Diverging housing costs may have played a role in limiting convergence.
BEYOND DENSITY FUNCTIONAL THEORY: THE DOMESTICATION OF NONLOCAL POTENTIALS

Due to efficient scaling with electron number N, density functional theory (DFT) is widely used for studies of large molecules and solids. Restriction of an exact mean-field theory to local potential functions has recently been questioned. This review summarizes motivation for extending current DFT to include nonlocal one-electron potentials, and proposes methodology for implementation of the theory. The theoretical model, orbital functional theory (OFT), is shown to be exact in principle for the general N-electron problem. In practice it must depend on a parametrized correlation energy functional. Functionals are proposed suitable for short-range Coulomb-cusp correlation and for long-range polarization response correlation. A linearized variational cellular method (LVCM) is proposed as a common formalism for molecules and solids. Implementation of nonlocal potentials is reduced to independent calculations for each inequivalent atomic cell.
Molecular investigations into the unfoldase action of severing enzymes on microtubules

Microtubule (MT)-associated proteins regulate the dynamic behavior of MTs during cellular processes. MT severing enzymes are the associated proteins which destabilize MTs by removing subunits from the lattice. One model for how severing enzymes remove tubulin dimers from the MT lattice is by unfolding its subunits through pulling on the carboxy-terminal tails of tubulin dimers. This model stems from the fact that severing enzymes are AAA+ unfoldases. To test this mechanism, we apply pulling forces on the carboxy-terminal regions of MT subunits using coarse grained molecular simulations. In our simulations, we used different MT lattices and concentrations of severing enzymes. We compare our simulation results with data from in vitro severing assays and find that the experimental data is best fit by a model of cooperative removal of protofilament fragments by severing enzymes, which depends on the severing enzyme concentration and placement on the MT lattice.
Electronic and Vibrational Contributions to the Bulk Stabilities of Trivalent 3d Transition Metal Oxyhydroxides from Electronic Structure Calculations

Any understanding of the thermodynamic driving forces active in the global cycles of earth abundant metals requires attendant knowledge of the bulk mineral free energies. This can be particularly c...
An inducible Cre mouse line to sparsely target nervous system cells, including Remak Schwann cells

Nerves of the peripheral nervous system contain two classes of Schwann cells: myelinating Schwann cells that ensheath large caliber axons and generate the myelin sheath, and Remak Schwann cells that surround smaller axons and do not myelinate. While tools exist for genetic targeting of Schwann cell precursors and myelinating Schwann cells, such reagents have been challenging to generate specifically for the Remak population, in part because many of the genes that mark this population in maturity are also robustly expressed in Schwann cell precursors. To circumvent this challenge, we utilized BAC transgenesis to generate a mouse line expressing a tamoxifen-inducible Cre under the control of a Remak-expressed gene promoter (Egr1). However, as Egr1 is also an activity dependent gene expressed by some neurons, we flanked this Cre by flippase (Flpe) recognition sites, and coinjected a BAC expressing Flpe under control of a pan-neuronal Snap25 promoter to excise the Cre transgene from these neuronal cells. Genotyping and inheritance demonstrate that the two BACs co-integrated into a single locus, facilitating maintenance of the line. Anatomical studies following a cross to a reporter line show sparse tamoxifen-dependent recombination in Remak Schwann cells within the mature sciatic nerve. However, depletion of neuronal Cre activity by Flpe is partial, with some neurons and astrocytes also showing evidence of Cre reporter activity in the central nervous system. Thus, this mouse line will be useful in mosaic loss-of-function studies, lineage tracing studies following injury, live cell imaging studies, or other experiments benefiting from sparse labeling.
An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations

This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring. Such applications involve a high demand for high-throughput data transmissions such as real-time video-, image-, and voice- streaming where the assigned spectrum to the UAV network may not be adequate to provide the desired Quality of Service (QoS). In these scenarios, the aerial network can borrow an additional spectrum from the available terrestrial networks in trade of a relaying service for them. We propose a spectrum sharing model in which the UAVs are grouped into two classes of relaying UAVs that service the spectrum owner and the sensing UAVs that perform the disaster relief mission using the obtained spectrum. The operation of the UAV network is managed by a hierarchical mechanism in which a central controller assigns the tasks of the UAVs based on their resources and determine their operation region based on the level of priority of impacted areas and then the UAVs autonomously fine-tune their position using a model-free reinforcement learning algorithm to maximize the individual throughput and prolong their lifetime. We analyze the performance and the convergence for the proposed method analytically and with extensive simulations in different scenarios.
NF-κB signaling regulates the formation of proliferating Müller glia-derived progenitor cells in the avian retina

Retinal regeneration is robust in some cold-blooded vertebrates, but this process is ineffective in warm-blooded vertebrates. Understanding the mechanisms that suppress the reprogramming of Muller glia into neurogenic progenitors is key to harnessing the regenerative potential of the retina. Inflammation and reactive microglia are known to influence the formation of Muller glia-derived progenitor cells (MGPCs), but the mechanisms underlying this interaction are unknown. We used a chick in vivo model to investigate nuclear factor kappa B (NF-κB) signaling, a critical regulator of inflammation, during the reprogramming of Muller glia into proliferating progenitors. We find that components of the NF-κB pathway are dynamically regulated by Muller glia after neuronal damage or treatment with growth factors. Inhibition of NF-κB enhances, whereas activation suppresses, the formation of proliferating MGPCs. Following microglia ablation, the effects of NF-κB-agonists on MGPC-formation are reversed, suggesting that signals provided by reactive microglia influence how NF-κB impacts Muller glia reprogramming. We propose that NF-κB is an important signaling 'hub' that suppresses the reprogramming of Muller glia into proliferating MGPCs and this 'hub' coordinates signals provided by reactive microglia.
Volume preserving mean curvature flow for star-shaped sets

We study the evolution of star-shaped sets in volume preserving mean curvature flow. Constructed by approximate minimizing movements, our solution preserves a strong version of star-shapedness. We also show that the solution converges to a ball as time goes to infinity. For asymptotic behavior of the solution we use the gradient flow structure of the problem, whereas a modified notion of viscosity solutions is introduced to study the geometric properties of the flow by moving planes method.
Chemotherapy but Not the Tumor Draining Lymph Nodes Determine the Immunotherapy Response in Secondary Tumors.

Summary Immunotherapies are used as adjuvant therapies for cancers. However, knowledge of how traditional cancer treatments affect immunotherapies is limited. Using mouse models, we demonstrate that tumor-draining lymph nodes (TdLNs) are critical for tumor antigen-specific T cell response. However, removing TdLNs concurrently with established primary tumors did not affect the immune checkpoint blockade (ICB) response on localized secondary tumor due to immunotolerance in TdLNs and distribution of antigen-specific T cells in peripheral lymphatic organs. Notably, treatment response improved with sequential administration of 5-fluorouracil (5-FU) and ICB compared with concurrent administration of ICB with 5-FU. Immune profiling revealed that using 5-FU as induction treatment increased tumor visibility to immune cells, decreased immunosuppressive cells in the tumor microenvironment, and limited chemotherapy-induced T cell depletion. We show that the effect of traditional cytotoxic treatment, not TdLNs, influences immunotherapy response in localized secondary tumors. We postulate essential considerations for successful immunotherapy strategies in clinical conditions.
Evaluation methods for rail transit projects

The demand for rail transit funds greatly exceeds available monies. Worse, there is widespread disagreement over the wisdom of building rail systems in American cities. The Urban Mass Transportation Administration's (UMTA's) transit analysis methods have relied on cost-effectiveness measures with little attention devoted to the analysis of economic efficiency. We survey the literature on transportation evaluation and propose a model method based on economic theory and on practice in other federal agencies. We review UMTA's past methods and recommend changes.
Chapter 12 – Cathodic Protection

Publisher Summary Cathodic protection is used in hazardous locations to prevent corrosion in tanks, pipelines, and other associated equipments. It has proven to be unsafe with respect to sparking, and is dangerous in the neighborhood of flammable vapors. Double ground an equipment in a hazardous area with cathodic protection. The transformer of the rectifier unit used in cathodic protection should have a grounded shielding between the primary and secondary windings. This chapter illustrates a case, where the protection against corrosion is considered as a source of explosion danger. A storage tank containing a flammable liquid that must be protected against corrosion caused by the continuous presence of water at the bottom of the tank is considered. A dangerous condition may exist if it is required to disconnect the piping system from the tank, while the current from the rectifier is still flowing. During the first instant of pipe separation, there may be no explosion danger. However, a few moments later when the liquid spill is in its evaporation stage and subsequently entering its explosion range, a dangerous condition may exist.
A Theory of Efficient Cooperation and Competition

This 1987 book looks at competition, attacking the notion that competition always leads to good results and that more competition is better. It also attacks the notion that cooperation is always harmful. An efficient economic equilibrium requires an optimal combination of both cooperation and rivalry. Telser first examines the genesis of certain late nineteenth-century laws that affected competition in the United States. Going on to give theoretical insights into cooperation and rivalry, he shows when unrestricted competition can lead to an efficient equilibrium, as well as when restrictions on competition can provide for the same. The tensions between these two forces are especially pertinent to the study of innovation - the more costly it is to protect the property rights of ideas, the greater is the reliance on secrecy, and hence, the more likely is the wasteful duplication of results.
Who Should Pay for Credit Ratings and How

We analyze a model where investors use a credit rating to decide whether to finance a firm. The rating quality depends on unobservable effort exerted by a credit rating agency (CRA). We study optimal compensation schemes for the CRA when a planner, the firm, or investors order the rating. Rating errors are larger when the firm orders it than when investors do (and both produce larger errors than is socially optimal). Investors overuse ratings relative to the firm or planner. A trade-off in providing time-consistent incentives embedded in the optimal compensation structure makes the CRA slow to acknowledge mistakes.
Chapter 2 – Properties of Laser Light

This chapter discusses various properties of laser light. These properties include: monochromaticity (narrow spectral linewidth), directionality (good collimation of the beam), the spatial and temporal characteristics of the laser beams, coherence properties, radiance, the capability to focus to a small spot, and the high power levels available. These characteristics of the laser light enable lasers to be used for practical applications. Laser light is highly monochromatic. Many lasers operate simultaneously in more than one longitudinal mode, so that the total linewidth approaches the fluorescent linewidth of the laser material. All modes for which the gain is greater than loss can be present in the laser output. The total spectral width covered by many practical lasers is almost as wide as the fluorescent linewidth, often around 10 9 Hz. One of the methods for forcing the output of a pulsed laser into a single longitudinal mode is injection seeding. It directs the output of a small, stable, single frequency laser, called the seed laser, into the laser cavity of the larger laser that provides the output pulse.
Household Debt and Business Cycles Worldwide

An increase in the household debt to GDP ratio predicts lower GDP growth and higher unemployment in the medium run for an unbalanced panel of 30 countries from 1960 to 2012. Low mortgage spreads are associated with an increase in the household debt to GDP ratio and a decline in subsequent GDP growth, highlighting the importance of credit supply shocks. Economic forecasters systematically over-predict GDP growth at the end of household debt booms, suggesting an important role of flawed expectations formation. The negative relation between the change in household debt to GDP and subsequent output growth is stronger for countries with less flexible exchange rate regimes. We also uncover a global household debt cycle that partly predicts the severity of the global growth slowdown after 2007. Countries with a household debt cycle more correlated with the global household debt cycle experience a sharper decline in growth after an increase in domestic household debt.
An improved algorithm for diameter-optimally augmenting paths in a metric space

Abstract Let P be a path graph of n vertices embedded in a metric space. We consider the problem of adding a new edge to P such that the diameter of the resulting graph is minimized. Previously (in ICALP 2015) the problem was solved in O ( n log 3 ⁡ n ) time. In this paper, based on new observations and different algorithmic techniques, we present an O ( n log ⁡ n ) time algorithm.
Environmental Justice in India: Incidence of Air Pollution from Coal-Fired Power Plants

Abstract Air pollution is a vexing problem for emerging countries that strike a delicate balance between environmental protection, health, and energy for growth. We examine these difficulties in a study of disparate levels of exposure to pollution from coal-fired power generation in India, a country with high levels of air pollution and large, marginalized populations. With data on coal plant locations, atmospheric conditions, and census demographics, we estimate exposure to coal plant emissions using models that predict emission transportation. We find that ethnic and poor populations are more likely to be exposed to coal pollution. However, this relationship is sometimes non-linear and follows an inverted u-shape similar to that of an Environmental Kuznets Curve. We theorize that this non-linear relationship is due to the exclusion of marginalized communities from both the negative and positive externalities of industrial development.
Social Network Analysis for Social Neuroscientists

Although social neuroscience is concerned with understanding how the brain interacts with its social environment, prevailing research in the field has primarily considered the human brain in isolation, deprived of its rich social context. Emerging work in social neuroscience that leverages tools from network analysis has begun to advance knowledge of how the human brain influences and is influenced by the structures of its social environment. In this paper, we provide an overview of key theory and methods in network analysis (especially for social systems) as an introduction for social neuroscientists who are interested in relating individual cognition to the structures of an individual's social environments. We also highlight some exciting new work as examples of how to productively use these tools to investigate questions of relevance to social neuroscientists. We include tutorials to help with practical implementations of the concepts that we discuss. We conclude by highlighting a broad range of exciting research opportunities for social neuroscientists who are interested in using network analysis to study social systems.
Rationalist Explanations for Two-Front War

By extending the extant costly-lottery models of war to three-party bargaining scenarios, we offer rationalist explanations for two-front war, where a state at the center is fought by two enemies at opposing peripheries. We found that even though private information exists only in one front, war can break out in both fronts. Because the war outcome in one front can affect the outcome in the other through the shift of military balance, the central state may preemptively initiate war in one front to establish its preponderance in the other (e.g., World War I), or a peripheral state may preventively join the war waging in the other front to leverage its power (e.g., Napoleonic Wars). These findings echo Waltz's neorealism concern that a multi-polar system may not be so stable as the bipolar system that bargaining models of dyadic war commonly presume.
The Demotivating Effects of Communicating a Social-Political Stance: Field Experimental Evidence from an Online Labor Market Platform

Despite a recent surge in corporate activism, with firm leaders communicating about social-political issues unrelated to their core businesses, we know little about its strategic implications. This...
Classical algorithms, correlation decay, and complex zeros of partition functions of Quantum many-body systems

We present a quasi-polynomial time classical algorithm that estimates the partition function of quantum many-body systems at temperatures above the thermal phase transition point. It is known that in the worst case, the same problem is NP-hard below this point. Together with our work, this shows that the transition in the phase of a quantum system is also accompanied by a transition in the hardness of approximation. We also show that in a system of n particles above the phase transition point, the correlation between two observables whose distance is at least Ω(logn) decays exponentially. We can improve the factor of logn to a constant when the Hamiltonian has commuting terms or is on a 1D chain. The key to our results is a characterization of the phase transition and the critical behavior of the system in terms of the complex zeros of the partition function. Our work extends a seminal work of Dobrushin and Shlosman on the equivalence between the decay of correlations and the analyticity of the free energy in classical spin models. On the algorithmic side, our result extends the scope of a recent approach due to Barvinok for solving classical counting problems to quantum many-body systems.
An instrument to assess HIV-related knowledge and adjustment to HIV+ status, and their association with anti-retroviral adherence.

Background Findings on the association between health literacy and anti-retroviral (ARV) adherence are inconsistent. Health literacy is usually operationalized with simple tests of basic literacy, but more complex conceptions of health literacy include content knowledge. People living with chronic illness also conceptualize and experience illness in ways other than biomedical or mechanistic models of disease. Objective There are no instruments that comprehensively assess knowledge of people living with HIV concerning HIV disease and treatment; or psychological adjustment to being HIV+. Little is known about the relationship between factual knowledge, or positive identification as HIV+, and anti-retroviral (ARV) adherence. Methods Formative work with in-depth semi-structured interviews, and cognitive testing, to develop a structured instrument assessing HIV-related knowledge, and personal meanings of living with HIV. Pilot administration of the instrument to a convenience sample of 101 respondents. Key results Respondents varied considerably in their expressed need for in-depth knowledge, the accuracy of their understanding of relevant scientific concepts and facts about ARV treatment, and psychological adjustment and acceptance of HIV+ status. Most knowledge domains were not significantly related to self-reported ARV adherence, but accurate knowledge specifically about ARV treatment was (r = 0.25, p = .02), as was an adapted version of the Need for Cognition scale (r = .256, p = .012). Negative feelings about living with HIV (r = .33, p = .0012), and medication taking (r = .276, p = .008) were significantly associated with non-adherence. Conclusion The instrument may be useful in diagnosing addressable reasons for non-adherence, as a component of psychoeducational interventions, and for evaluation of such interventions.
Domination in direct products of complete graphs

Abstract Let X n denote the unitary Cayley graph of Z ∕ n Z . We continue the study of cases in which the inequality γ t ( X n ) ≤ g ( n ) is strict, where γ t denotes the total domination number, and g is the arithmetic function known as Jacobsthal’s function. The best that is currently known in this direction is a construction of Burcroff which gives a family of n with arbitrarily many prime factors that satisfy γ t ( X n ) ≤ g ( n ) − 2 . We present a new interpretation of the problem which allows us to use recent results on the computation of Jacobsthal’s function to construct n with arbitrarily many prime factors that satisfy γ t ( X n ) ≤ g ( n ) − 16 . We also present new lower bounds on the domination numbers of direct products of complete graphs, which in turn allow us to derive new asymptotic lower bounds on γ ( X n ) , where γ denotes the domination number. Finally, resolving a question of Defant and Iyer, we completely classify all graphs G = ∏ i = 1 t K n i satisfying γ ( G ) = t + 2 .
Deriving Peridynamic Influence Functions for One-dimensional Elastic Materials with Periodic Microstructure

The influence function in peridynamic material models has a large effect on the dynamic behavior of elastic waves and in turn can greatly effect dynamic simulations of fracture propagation and material failure. Typically, the influence functions that are used in peridynamic models are selected for their numerical properties without regard to physical considerations. In this work, we present a method of deriving the peridynamic influence function for a one-dimensional initial/boundary-value problem in a material with periodic microstructure. Starting with the linear local elastodynamic equation of motion in the microscale, we first use polynomial anzatzes to approximate microstructural displacements and then derive the homogenized nonlocal dynamic equation of motion for the macroscopic displacements, which is easily reformulated as linear peridyamic equation with a discrete influence function. The shape and localization of the discrete influence function are completely determined by microstructural mechanical properties and length scales. By comparison with a highly resolved microstructural finite element model and the standard linear peridynamic model with a linearly decaying influence function, we demonstrate that the influence function derived from microstructural considerations is more accurate in predicting time-dependent displacements and wave dynamics.
The histone H3-H4 tetramer is a copper reductase enzyme

Eukaryotic histone H3-H4 tetramers contain a putative copper (Cu2+) binding site at the H3-H3' dimerization interface with unknown function. The coincident emergence of eukaryotes with global oxygenation, which challenged cellular copper utilization, raised the possibility that histones may function in cellular copper homeostasis. We report that the recombinant Xenopus laevis H3-H4 tetramer is an oxidoreductase enzyme that binds Cu2+ and catalyzes its reduction to Cu1+ in vitro. Loss- and gain-of-function mutations of the putative active site residues correspondingly altered copper binding and the enzymatic activity, as well as intracellular Cu1+ abundance and copper-dependent mitochondrial respiration and Sod1 function in the yeast Saccharomyces cerevisiae The histone H3-H4 tetramer, therefore, has a role other than chromatin compaction or epigenetic regulation and generates biousable Cu1+ ions in eukaryotes.
Mixing it up - The case for finite mixture models to study the distribution of income

We offer a brief review of the use of distributional mixture models with a finite number of components for the study of the distribution of income. In general, finite mixture models find a number of applications across fields, but they usually arise from theoretical considerations. Applications to the distribution of income present a joint inference about the number and types of components to include in a mixture, corresponding to how different income generating mechanisms’ statistical signatures are represented in the observed data. Many of the contributions in this area rest on an implicit (and sometimes explicit) information theoretic approach to this inference problem. Our review concludes with new illustrative findings from the US based on restricted-access Census data.