cssi/SciSciGPT-SciSciNet huggingface dataset:
Auditable Data Structures

The classic notion of history-independence guarantees that if a data structure is ever observed, only its current contents are revealed, not the history of operations that built it. This powerful concept has applications, for example, to e-voting and data retention compliance, where data structure histories should be private. The concept of weak history-independence (WHI) assumes only a single observation will ever occur, while strong history-independence (SHI) allows for multiple observations at arbitrary times. WHI constructions tend to be fast, but provide no repeatability, while SHI constructions provide unlimited repeatability, but tend to be slow. We introduce auditable data structures, where an auditor can observe data structures at arbitrary times (as in SHI), but we relax the unrealistic restriction that data structures cannot react to observations, since in most applications of history-independence, data owners know when observations have occurred. We consider two audit scenarios—secure topology, where an auditor can observe the contents and pointers of a data structure, and secure implementation, where an auditor can observe the memory layout of a data structure. We present a generic template for auditable data structures and, as a foundation for any auditable data structure, an Auditable Memory Manager (AMM), which is an efficient memory manager that translates any auditable data structure with a secure topology into one with a secure implementation. We give a prototype implementation that provides empirical evidence that the worst-case time running times of our AMM are 45 to 8,300 faster than those of a well-known SHI memory manager. Thus, auditable data structures provide a practical way of achieving time efficiency, as in WHI, while allowing for multiple audits, as in SHI.
Unnecessary Microscopy in Routine Urinalysis

The consequence of omitting urine sediment microscopy in specimens with normal physicochemical testing was assessed in a retrospective review of laboratory and clinical data in 1,000 patients. The pathologic states of clinical significance most likely to be overlooked were Trichomonas infection and occasional cases of significant bacteriuria. However, the medical benefit of performing urine microscopy in these two groups of patients was not clear. The authors cautiously recommend reserving microscopy for urine specimens that show physicochemical abnormalities.
Jerry Harvey: the quintessential life of sense and nonsense*

AbstractThe author pays homage to his former professor, the iconic, caring, profane, charming, and piercing Jerry B. Harvey. Harvey may have been the first person to teach a course on spirituality in a school of business. His work predated the establishment of the Management, Spirituality, and Religion interest group in the Academy of Management, dating at least to a talk about OD as a Religious Movement in 1964. The article is a critique of Harvey’s œuvre in terms of work that was ahead of its time, work that is timely for today, work that is timeless, and work that feels dated at this point of the twenty-first century. In the final section, the author describes how Harvey’s work impacted his career even several decades later.
Urine From Patients With Transitional-Cell Carcinoma Stimulates Migration of Capillary Endothelial Cells

THE growth of new capillary blood vessels toward a solid tumor is a process that requires both migration and proliferation of capillary endothelial cells.1 As part of our studies of tumor-capillary inter-actions, we have cultured endothelial cells from bovine and human capillaries.2 Using a new quantitative assay for endothelial-cell migration, we found that neoplastic cells release a substance that stimulates the in vitro migration of capillary endothelial cells.3 On the basis of this observation, we postulated that biologic fluids that bathe tumors in vivo may also contain detectable amounts of a factor that stimulates the migration of capillary endothelial cells. . . .
Feedback regulation of steady-state epithelial turnover and organ size

Epithelial organs undergo steady-state turnover throughout adult life, with old cells being continually replaced by the progeny of stem cell divisions. To avoid hyperplasia or atrophy, organ turnover demands strict equilibration of cell production and loss. However, the mechanistic basis of this equilibrium is unknown. Here we show that robustly precise turnover of the adult Drosophila intestine arises through a coupling mechanism in which enterocyte apoptosis breaks feedback inhibition of stem cell division. Healthy enterocytes inhibit stem cell division through E-cadherin, which prevents secretion of mitogenic epidermal growth factors (EGFs) by repressing transcription of the EGF maturation factor rhomboid. Individual apoptotic enterocytes promote divisions by loss of E-cadherin, which releases cadherin-associated β-catenin (Armadillo in Drosophila) and p120-catenin to induce rhomboid. Induction of rhomboid in the dying enterocyte triggers activation of the EGF receptor (Egfr) in stem cells within a discrete radius. When we blocked apoptosis, E-cadherin-controlled feedback suppressed divisions, and the organ retained the same number of cells. When we disrupted feedback, apoptosis and divisions were uncoupled, and the organ developed either hyperplasia or atrophy. Together, our results show that robust cellular balance hinges on the obligate coupling of divisions to apoptosis, which limits the proliferative potential of a stem cell to the precise time and place at which a replacement cell is needed. In this way, localized cell-cell communication gives rise to tissue-level homeostatic equilibrium and constant organ size.
Rental regulation and its consequences on measures of well-being in the Arab Republic of Egypt

The paper delves into the implications of a failure to account for rental regulation in the measurement of households' welfare, poverty, and inequality when using household surveys. Exploiting previously unavailable data for the Egyptian case, the paper illustrates the long-lasting distortions in the rental market that the 1977 rental law has created. The paper finds evidence that earlier studies may have substantially underestimated households’ welfare in urban areas and overestimated urban poverty. National poverty rates show smaller corrections, as poverty is mainly a rural phenomenon in the Arab Republic of Egypt. An appropriate measure of welfare also led to downward corrections in inequality in urban Egypt, while increasing the inequality across regions. These effects counterbalance each other and nationwide inequality estimates are affected only slightly.
Practical Network-Wide Packet Behavior Identification by AP Classifier

Identifying the network-wide forwarding behaviors of a packet is essential for many network management applications, including rule verification, policy enforcement, attack detection, traffic engineering, and fault localization. Current tools that can perform packet behavior identification either incur large time and memory costs or do not support real-time updates. In this paper, we present AP Classifier, a control plane tool for packet behavior identification. AP Classifier is developed based on the concept of atomic predicates, which can be used to characterize the forwarding behaviors of packets. Experiments using the data plane network state of two real networks show that the processing speed of AP Classifier is faster than existing tools by at least an order of magnitude. Furthermore, AP Classifier uses very small memory and is able to support real-time updates.
Overlap among Spatial Memories Triggers Repulsion of Hippocampal Representations.

Summary Across the domains of spatial navigation and episodic memory, the hippocampus is thought to play a critical role in disambiguating (pattern separating) representations of overlapping events. However, it is not fully understood how and why hippocampal patterns become separated. Here, we test the idea that event overlap triggers a "repulsion" among hippocampal representations that develops over the course of learning. Using a naturalistic route-learning paradigm and spatiotemporal pattern analysis of human fMRI data, we found that hippocampal representations of overlapping routes gradually diverged with learning to the point that they became less similar than representations of non-overlapping events. In other words, the hippocampus not only disambiguated overlapping events but formed representations that "reversed" the objective similarity among routes. This finding, which was selective to the hippocampus, is not predicted by standard theoretical accounts of pattern separation. Critically, because the overlapping route stimuli that we used ultimately diverged (so that each route contained overlapping and non-overlapping segments), we were able to test whether the reversal effect was selective to the overlapping segments. Indeed, once overlapping routes diverged (eliminating spatial and visual similarity), hippocampal representations paradoxically became relatively more similar . Finally, using a novel analysis approach, we show that the degree to which individual hippocampal voxels were initially shared across route representations was predictive of the magnitude of learning-related separation. Collectively, these findings indicate that event overlap triggers a repulsion of hippocampal representations—a finding that provides critical mechanistic insight into how and why hippocampal representations become separated.
Why do long distance truck drivers work extremely long hours

While other research has shown that higher paid truck and bus drivers are safer, this is the first study showing why higher paid drivers are safer. We estimate the labour supply curve for long-haul truck drivers in the United States, applying two-stage least squares regression to a national survey of truck drivers. We start with the standard model of the labour supply curve and then develop two novel extensions of it, incorporating pay level and pay method, and testing the target earnings hypothesis. We distinguish between long-haul and short-haul jobs driving commercial motor vehicles. Truck and bus drivers choose between long-distance jobs requiring very long hours of work away from home and short-distance jobs generally requiring fewer hours. The labour supply curve exhibits a classic backward bending shape, reflecting drivers’ preference to work until they reach target earnings. Above target earnings, at a ‘safe rate’ for truck drivers, they trade labour for leisure, working fewer hours, leading to gr...
Direct evidence for the source of reported magnetic behavior in "CoTe"

In order to unambiguously identify the source of magnetism reported in recent studies of the Co-Te system, two sets of high-quality, epitaxial CoTex films (thickness ≈ 300 nm) were prepared by pulse laser deposition (PLD). X-ray diffraction (XRD) shows that all of the films are epitaxial along the [001] direction and have the hexagonal NiAs structure. There is no indication of any second phase metallic Co peaks (either fcc or hcp) in the XRD patterns. The two sets of CoTex films were grown on various substrates with PLD targets having Co:Te in the atomic ratio of 50:50 and 35:65. From the measured lattice parameters c = 5.396 A for the former and c = 5.402 A for the latter, the compositions CoTe1.71 (63.1% Te) and CoTe1.76 (63.8% Te), respectively, are assigned to the principal phase. Although XRD shows no trace of metallic Co second phase, the magnetic measurements do show a ferromagnetic contribution for both sets of films with the saturation magnetization values for the CoTe1.71 films being approximate...
Ligand-Mediated Biofilm Formation via Enhanced Physical Interaction between a Diguanylate Cyclase and Its Receptor.

ABSTRACT The bacterial intracellular second messenger, cyclic dimeric GMP (c-di-GMP), regulates biofilm formation for many bacteria. The binding of c-di-GMP by the inner membrane protein LapD controls biofilm formation, and the LapD receptor is central to a complex network of c-di-GMP-mediated biofilm formation. In this study, we examine how c-di-GMP signaling specificity by a diguanylate cyclase (DGC), GcbC, is achieved via interactions with the LapD receptor and by small ligand sensing via GcbC’s calcium channel chemotaxis (CACHE) domain. We provide evidence that biofilm formation is stimulated by the environmentally relevant organic acid citrate (and a related compound, isocitrate) in a GcbC-dependent manner through enhanced GcbC-LapD interaction, which results in increased LapA localization to the cell surface. Furthermore, GcbC shows little ability to synthesize c-di-GMP in isolation. However, when LapD is present, GcbC activity is significantly enhanced (~8-fold), indicating that engaging the LapD receptor stimulates the activity of this DGC; citrate-enhanced GcbC-LapD interaction further stimulates c-di-GMP synthesis. We propose that the I-site of GcbC serves two roles beyond allosteric control of this enzyme: promoting GcbC-LapD interaction and stabilizing the active conformation of GcbC in the GcbC-LapD complex. Finally, given that LapD can interact with a dozen different DGCs of Pseudomonas fluorescens, many of which have ligand-binding domains, the ligand-mediated enhanced signaling via LapD-GcbC interaction described here is likely a conserved mechanism of signaling in this network. Consistent with this idea, we identify a second example of ligand-mediated enhancement of DGC-LapD interaction that promotes biofilm formation. IMPORTANCE In many bacteria, dozens of enzymes produce the dinucleotide signal c-di-GMP; however, it is unclear how undesired cross talk is mitigated in the context of this soluble signal and how c-di-GMP signaling is regulated by environmental inputs. We demonstrate that GcbC, a DGC, shows little ability to synthesize c-di-GMP in the absence of its cognate receptor LapD; GcbC-LapD interaction enhances c-di-GMP synthesis by GcbC, likely mediated by the I-site of GcbC. We further show evidence for a ligand-mediated mechanism of signaling specificity via increased physical interaction of a DGC with its cognate receptor. We envision a scenario wherein a “cloud” of weakly active DGCs can increase their activity by specific interaction with their receptor in response to appropriate environmental signals, concomitantly boosting c-di-GMP production, ligand-specific signaling, and biofilm formation.
Economic Consequences of the AOCI Filter Removal for Advanced Approaches Banks

ABSTRACT We examine economic consequences of U.S. bank regulators' phased removal of the prudential filter for accumulated other comprehensive income for advanced approaches banks beginning on Janu...
DISSECTING THE MONTY HALL ANOMALY

We assess competing explanations of irrational behavior in the Monty Hall problem by creating new variants of the problem. Some variants employ a feature that automates the merging of probabilities, thus rendering transparent the probabilistic advantage of the rational choice. That feature also enables systematic variation in informational asymmetry, and in ordering of actions. Data from 77 subjects, each of whom makes 30 binary decisions, indicate that automated merging raises the fraction of rational choices from around 40% to over 80%. Other features examined have much less impact, indicating the importance of a Bayesian updating failure. (JEL C91, D02, D81, D83)
Tight Bounds on $\ell_1$ Approximation and Learning of Self-Bounding Functions

We study the complexity of learning and approximation of self-bounding functions over the uniform distribution on the Boolean hypercube ${0,1}^n$. Informally, a function $f:{0,1}^n \rightarrow \mathbb{R}$ is self-bounding if for every $x \in {0,1}^n$, $f(x)$ upper bounds the sum of all the $n$ marginal decreases in the value of the function at $x$. Self-bounding functions include such well-known classes of functions as submodular and fractionally-subadditive (XOS) functions. They were introduced by Boucheron et al. (2000) in the context of concentration of measure inequalities. Our main result is a nearly tight $\ell_1$-approximation of self-bounding functions by low-degree juntas. Specifically, all self-bounding functions can be $\epsilon$-approximated in $\ell_1$ by a polynomial of degree $\tilde{O}(1/\epsilon)$ over $2^{\tilde{O}(1/\epsilon)}$ variables. We show that both the degree and junta-size are optimal up to logarithmic terms. Previous techniques considered stronger $\ell_2$ approximation and proved nearly tight bounds of $\Theta(1/\epsilon^{2})$ on the degree and $2^{\Theta(1/\epsilon^2)}$ on the number of variables. Our bounds rely on the analysis of noise stability of self-bounding functions together with a stronger connection between noise stability and $\ell_1$ approximation by low-degree polynomials. This technique can also be used to get tighter bounds on $\ell_1$ approximation by low-degree polynomials and faster learning algorithm for halfspaces. These results lead to improved and in several cases almost tight bounds for PAC and agnostic learning of self-bounding functions relative to the uniform distribution. In particular, assuming hardness of learning juntas, we show that PAC and agnostic learning of self-bounding functions have complexity of $n^{\tilde{\Theta}(1/\epsilon)}$.
Random access in large-scale DNA data storage

200 MB of digital data is stored in DNA, randomly accessed and recovered using an error-free approach. Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.
An adaptive control architecture for leader–follower multiagent systems with stochastic disturbances and sensor and actuator attacks

ABSTRACTIn this paper, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor ...
Buildup of speaking skills in an online learning community: a network-analytic exploration

Studies in learning communities have consistently found evidence that peer-interactions contribute to students’ performance outcomes. A particularly important competence in the modern context is the ability to communicate ideas effectively. One metric of this is speaking, which is an important skill in professional and casual settings. In this study, we explore peer-interaction effects in online networks on speaking skill development. In particular, we present an evidence for gradual buildup of skills in a small-group setting that has not been reported in the literature. Evaluating the development of such skills requires studying objective evidence, for which purpose, we introduce a novel dataset of six online communities consisting of 158 participants focusing on improving their speaking skills. They video-record speeches for 5 prompts in 10 days and exchange comments and performance-ratings with their peers. We ask (i) whether the participants’ ratings are affected by their interaction patterns with peers, and (ii) whether there is any gradual buildup of speaking skills in the communities towards homogeneity. To analyze the data, we employ tools from the emerging field of Graph Signal Processing (GSP). GSP enjoys a distinction from Social Network Analysis in that the latter is concerned primarily with the connection structures of graphs, while the former studies signals on top of graphs. We study the performance ratings of the participants as graph signals atop underlying interaction topologies. Total variation analysis of the graph signals show that the participants’ rating differences decrease with time (slope = −0.04, p < 0.01), while average ratings increase (slope = 0.07, p < 0.05)—thereby gradually building up the ratings towards community-wide homogeneity. We provide evidence for peer-influence through a prediction formulation. Our consensus-based prediction model outperforms baseline network-agnostic regression models by about 23% in predicting performance ratings. This in turn shows that participants’ ratings are affected by their peers’ ratings and the associated interaction patterns, corroborating previous findings. Then, we formulate a consensus-based diffusion model that captures these observations of peer-influence from our analyses. We anticipate that this study will open up future avenues for a broader exploration of peer-influenced skill development mechanisms, and potentially help design innovative interventions in small-groups to maximize peer-effects.
Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation Using Maximum Entropy-Based Simulations with Application to Central Metabolism of Neurospora crassa

We report the application of a recently proposed approach for modeling biological systems using a maximum entropy production rate principle in lieu of having in vivo rate constants. The method is applied in four steps: (1) a new ordinary differential equation (ODE) based optimization approach based on Marcelin's 1910 mass action equation is used to obtain the maximum entropy distribution; (2) the predicted metabolite concentrations are compared to those generally expected from experiments using a loss function from which post-translational regulation of enzymes is inferred; (3) the system is re-optimized with the inferred regulation from which rate constants are determined from the metabolite concentrations and reaction fluxes; and finally (4) a full ODE-based, mass action simulation with rate parameters and allosteric regulation is obtained. From the last step, the power characteristics and resistance of each reaction can be determined. The method is applied to the central metabolism of Neurospora crassa and the flow of material through the three competing pathways of upper glycolysis, the non-oxidative pentose phosphate pathway, and the oxidative pentose phosphate pathway are evaluated as a function of the NADP/NADPH ratio. It is predicted that regulation of phosphofructokinase (PFK) and flow through the pentose phosphate pathway are essential for preventing an extreme level of fructose 1,6-bisphophate accumulation. Such an extreme level of fructose 1,6-bisphophate would otherwise result in a glassy cytoplasm with limited diffusion, dramatically decreasing the entropy and energy production rate and, consequently, biological competitiveness.
Third-Party Ownership Business Models and the Operational Performance of Solar Energy Systems

The nonresidential solar energy market has grown rapidly in the United States. Companies considering the adoption of solar energy have an important choice: whether to purchase the system (direct ownership, or DO) or opt for an agreement with a service provider that offers third-party ownership (TPO). Although this decision is financially very important, empirical research comparing the two models from an operational perspective has been scarce. These issues are particularly relevant considering that federal and state incentives are commonly used to stimulate adoption. This paper presents an empirical analysis of the role of TPO in the operational performance of nonresidential solar energy installations in California. Using a panel data estimation framework, and accounting for factors that influence TPO adoption, the analysis shows that TPO systems performed, on average, approximately 4% better than DO systems) in terms of their production yield. This performance improvement is consistent with better syste...
Experimental Issues in Coherent Quantum-State Manipulation of Trapped Atomic Ions

Methods for, and limitations to, the generation of entangled states of trapped atomic ions are examined. As much as possible, state manipulations are described in terms of quantum logic operations since the conditional dynamics implicit in quantum logic is central to the creation of entanglement. Keeping with current interest, some experimental issues in the proposal for trappedion quantum computation by J. I. Cirac and P. Zoller (University of Innsbruck) are discussed. Several possible decoherence mechanisms are examined and what may be the more important of these are identified. Some potential applications for entangled states of trapped-ions which lie outside the immediate realm of quantum computation are also discussed.
On anger, shock, fear, and trauma: therapeutic jurisprudence as a response to dignity denials in public policy.

Abstract This article asserts that when policymaking processes, outcomes, and implementations stoke fear, anxiety, and trauma, they often lead to denials of human dignity. It cited as prime examples the recent actions of America's current federal government concerning immigration and health care. As a response, I urge that therapeutic jurisprudence should inform both the processes of policymaking and the design of public policy, trained on whether human dignity, psychological health, and well-being are advanced or diminished. I also discuss three methodologies that will help to guide those who want to engage legislation in a TJ-informed manner. Although achieving this fundamental shift will not be easy, we have the raw analytical and intellectual tools to move wisely in this direction.
Use of a Systematic Consultation Process to Facilitate Nursing Research Projects: An Exemplar.

Purpose/objectives The purpose of this article is to describe the use of a well-established, 5-stage consultation process, to advise a research team on planning strategies to engage domestic violence shelters (DVSs) as community partners in their study. The research team is testing a health promotion intervention for teens living in shelters with their parent and needed to enlist shelters as sites to recruit teens and conduct the intervention. Consultation aims were to (a) identify highly promising strategies described in peer-reviewed literature for identifying, recruiting, and collaborating with community organizations in research and (b) identify DVSs that would potentially serve as effective community partners for the study. Methods A clinical nurse specialist and a public health master's degree student led the consultation. The consultation process included (a) a systematic review of 29 peer-reviewed articles about research or program evaluation studies that engaged community partners and (b) a comprehensive online search of information about DVSs. Outcomes Consultants identified 104 strategies used in studies to engage community partners and 10 specific DVSs most likely to effectively engage in the study. Conclusion Clinical nurse specialists are well situated to provide consultation to research teams and should follow well-established consultation processes and systematic data collection procedures.
Impact of scribing history and physical notes and procedure reports on endoscopist efficiency during routine procedures: a proof-of-concept study.

BACKGROUND Efficiency is an important aspect of endoscopic practice that has received limited study. We evaluated the impact of scribing electronic pre-procedure history and physical examinations, and electronic procedure reports on endoscopist efficiency. METHODS We used a stopwatch to measure the time between the procedures (scope out to scope in), pre-procedure patient assessment time, and procedure report generation time for 180 consecutive procedures performed by a single endoscopist with or without a scribe for recording history and physical and procedure reports. Schedulers were unaware of whether a scribe would be present. RESULTS Mean times for recording the pre-procedure history and physical and procedure reports were reduced by 34% (p = 0.001) and 71% (p < 0.0001), respectively, when scribes were used. The mean time saved by the endoscopist from scribing the history and the physical and procedure reports was 2.12 and 1.59 min, respectively. When both processes were scribed, the endoscopist spent 42% (p = 0.033) longer in the recovery area (absolute mean increase 1.01 min) compared with when no scribes were utilized. The total time saved per 6.5-h procedure block with both scribes averaged to 41.7 min. CONCLUSION The use of scribes to record history and physical examination notes and procedure reports saved enough endoscopist time to allow additional procedures or longer procedures, or to free the time for other tasks.
DEMOCRACY UNDONE. SYSTEMATIC MINORITY ADVANTAGE IN COMPETITIVE VOTE MARKETS

We study the competitive equilibrium of a market for votes where the choice is binary and it is known that a majority of the voters supports one of the two alternatives. Voters can trade votes for a numeraire before making a decision via majority rule. We identify a sufficient condition guaranteeing the existence of an ex ante equilibrium. In equilibrium, only the most intense voter on each side demands votes, and each demands enough votes to alone control a majority. The equilibrium strongly resembles an all-pay auction for decision power: it makes clear that votes are only a medium for the allocation of power. The probability of a minority victory is always higher than efficient and converges rapidly to one-half as the electorate increases, for any minority size. The numerical advantage of the majority becomes irrelevant: democracy is undone by the market.
Sensor-Based Reactive Navigation in Unknown Convex Sphere Worlds

We construct a sensor-based feedback law that provably solves the real-time collision-free robot navigation problem in a compact convex Euclidean subset cluttered with unknown but sufficiently sepa...
Inverse design of nanophotonic structures using complementary convex optimization

A computationally-fast inverse design method for nanophotonic structures is presented. The method is based on two complementary convex optimization problems which modify the dielectric structure and resonant field respectively. The design of one- and two-dimensional nanophotonic resonators is demonstrated and is shown to require minimal computational resources.
Decentralized Release of Self-Emerging Data using Smart Contracts

In the age of Big Data, releasing protected sensitive data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the recipient at the release time, even if the data sender goes offline. While straight-forward centralized approaches provide a basic solution to the problem, unfortunately they are limited to a single point of trust and involve a single point of control. This paper presents decentralized techniques for supporting self-emerging data using smart contracts in Ethereum blockchain networks. We design a credible and enforceable smart contract for supporting self-emerging data release. The smart contract employs a set of Ethereum peers to jointly follow the proposed timed-release service protocol allowing the participating peers to earn the remuneration paid by the service users. We model the problem as an extensive-form game with imperfect information to protect against possible adversarial attacks including some peers destroying the private data (drop attack) or secretly releasing the private data before the release time (release-ahead attack). We demonstrate the efficacy and attack-resilience of the proposed techniques through rigorous analysis and experimental evaluation. Our implementation and experimental evaluation on the Ethereum official test network demonstrate the low monetary cost and the low time overhead associated with the proposed approach and validate its guaranteed security properties.
The Early Years of the Financial Accounting Foundation and the Financial Accounting Standards Board, 1972 to 1980: The “Special Relationship” with the AICPA

ABSTRACT In this paper, the author documents the American Institute of Certified Public Accountants' “special relationship” with the Financial Accounting Foundation and the Financial Accounting Sta...
A Modified Dual-Wavelength Technique for Ku- and Ka-Band Radar Rain Retrieval

AbstractTo overcome a deficiency in the standard Ku- and Ka-band dual-wavelength radar technique, a modified version of the method is introduced. The deficiency arises from ambiguities in the estim...
The effects of menu costs on retail performance: Evidence from adoption of the electronic shelf label technology

We use the adoption of electronic shelf labels (ESLs) by an international grocery retailer in 2015 to identify the effects of physical menu costs (i.e., labor and material costs of price adjustment...
The MMap Strikes Back: Obfuscation and New Multilinear Maps Immune to CLT13 Zeroizing Attacks

All known multilinear map candidates have suffered from a class of attacks known as “zeroizing” attacks, which render them unusable for many applications. We provide a new construction of polynomial-degree multilinear maps and show that our scheme is provably immune to zeroizing attacks under a strengthening of the Branching Program Un-Annihilatability Assumption (Garg et al., TCC 2016-B).
Optimal Signaling Mechanisms in Unobservable Queues

In many systems with limited service capacity, customers must wait in a queue for service. When customers cannot observe the queue, how should a revenue-maximizing service provider convey informati...
Melt fracture revisited

In a previous paper the author and Demay advanced a model to explain the melt fracture instability observed when molten linear polymer melts are extruded in a capillary rheometer operating under the controlled condition that the inlet flow rate was held constant. The model postulated that the melts were a slightly compressible viscous fluid and allowed for slipping of the melt at the wall. The novel feature of that model was the use of an empirical switch law which governed the amount of wall slip. The model successfully accounted for the oscillatory behavior of the exit flow rate, typically referred to as the melt fracture instability, but did not simultaneously yield the fine scale spatial oscillations in the melt typically referred to as shark skin. In this note, a new model is advanced which simultaneously explains the melt fracture instability and shark skin phenomena. The model postulates that the polymer is a slightly compressible linearly viscous fluid but assumes no-slip boundary conditions at the capillary wall. In simple shear the shear stress τ and strain rate d are assumed to be related by d = F τ, where F ranges between F 2 and F 1 > F 2 . A strain-rate dependent yield function is introduced and this function governs whether F evolves towards F 2 or F 1 . This model accounts for the empirical observation that at high shears polymers align and slide more easily than at low shears, and explains both the melt fracture and shark skin phenomena.
Nanoscale self-healing mechanisms in shape memory ceramics

Shape memory ceramics, such as yttria-stabilized tetragonal zirconia (YSTZ), offer unique properties including ultra-high operating temperatures and high resistance to oxidation. However, they are susceptible to formation of defects during manufacturing and/or by mechanical deformation. To completely take advantage of their shape memory properties, it is necessary to fully understand the nano-structural evolution of defects under external stimuli. In this study, defect evolution behaviors in YSTZ nanopillars are investigated by atomistic simulations. Two characteristic orientations of $$\left[ {01\bar 1} \right]$$ and [001] are selected to represent the dominant deformation mechanisms of phase transformation and dislocation migration, respectively. Volume expansion associated with the tetragonal to monoclinic phase transformation is observed to promote healing of crack and void. Atom stress analyses reveal stress concentrations along the newly formed monoclinic phase bands. A critical crack width is identified, less than which the crack can be fully closed in compression. For [001]-oriented YSTZ nanopillars, dislocation migration leads to formations of an amorphous phase, which also assist the crack and void closure process. The revealed crack/void healing mechanisms may provide a path for mitigating internal defects that influences the mechanical properties and deformation mechanisms of shape memory ceramics.
Room-temperature ferromagnetism in epitaxial titanium nitride thin films

Abstract Localized charge injection by formation of vacancies provides an attractive platform for the development of multifunctional nanomaterials with direct implications in spintronics. However, further progress in spintronics critically depends on a deeper understanding of polaronic interactions between the localized charge states. This report is focused on TiN metallic system, which exhibits Pauli paramagnetism due to the absence of unpaired localized spin states. Here, nitrogen vacancies (VN) are used as a variable to tune the magnetic properties of epitaxial TiN thin films by thermal annealing in high-vacuum and N2 environment. Systematic introduction of VN generates robust magnetic ordering in vacuum-annealed TiN1-x films, with Curie temperature (TC) ∼700 K, and saturation magnetization (Ms) at absolute zero of 13.6 emu g−1. The signature spin-glass behavior below the irreversibility temperature (Tir ∼40 K) indicates the Ruderman-Kittel-Kasuya-Yosida (RKKY) coupling interactions between the unpaired localized spin-states. Through spatially resolved electron energy-loss spectroscopy, we have determined the generation of unpaired localized spins at Ti+2 polarons with ∼12 ± 2 at.% VN in TiN1-x films. Such a large concentration of VN results in increased spin stiffness and high TC. These findings open a definitive pathway for tuning the magnetic nature of metallic materials for spintronic applications.
A Sharp Bound on the $s$ -Energy and Its Applications to Averaging Systems

The $s$ -energy is a generating function of wide applicability in network-based dynamics. We derive an (essentially) optimal bound of $(3/\rho s)^{n-1}$ on the $s$ -energy of an $n$ -agent symmetric averaging system, for any positive real $s\leq 1$ , where $\rho$ is a lower bound on the nonzero weights. This is done by introducing the new dynamics of twist systems . We show how to use the new bound on the $s$ -energy to tighten the convergence rates of systems in opinion dynamics, flocking, and synchronization.
Police Candidate Selection: Assessing the Effectiveness of Pre-employment Polygraph Screening

The majority of law enforcement agencies in the USA use pre-employment polygraph screening as a pass/fail criterion for prospective applicants. However, the polygraph has a number of unresolved practical and theoretical issues that are pronounced in the pre-employment screening context. After reviewing the literature in 2003, the National Research Council concluded there is a strong risk that pre-employment polygraph screening may erroneously exclude a large number of otherwise suitable candidates. Meanwhile, police departments face increasing difficulties finding qualified candidates to hire, and are often unable to keep pace with force attrition due to retirements and other factors. In light of these facts, this study attempts to determine if the polygraph is an effective means of filtering undesirable candidates by comparing data on police officer arrests between states that mandate pre-employment polygraph screening for law enforcement personnel and those that forbid the practice as a matter of law. The results were both surprising and completely contrary to initial expectations. It was found that states using the polygraph have significantly fewer years of service at the time of arrest and more per-capita arrests than police agencies in states that forbid the practice. Based on these results and a review of the polygraph literature, this study concludes that sole reliance on polygraph results as a pass/fail criterion for police hiring is a misguided practice.
Real time Pattern Based Melodic Query for Music Continuation System

This paper presents a music continuation system using pattern matching to find patterns within a library of MIDI files using a realtime algorithm to build a system which can be used as interactive DJ system. This paper also looks at the influence of different kinds of pattern matching on MIDI file analysis. Many pattern-matching algorithms have been developed for text analysis, voice recognition and Bio-informatics but as the domain knowledge and nature of the problems are different these algorithms are not ideally suitable for real time MIDI processing for interactive music continuation system. By taking patterns in real-time, via MIDI keyboard, the system searches patterns within a corpus of MIDI files and continues playing from the user's musical input. Four different types of pattern matching are used in this system (i.e. exact pattern matching, reverse pattern matching, pattern matching with mismatch and combinatorial pattern matching in a single system). After computing the results of the four types of pattern matching of each MIDI file, the system compares the results and locates the highest pattern matching possibility MIDI file within the library.
A unifying framework for interpreting and predicting mutualistic systems

Coarse-grained rules are widely used in chemistry, physics and engineering. In biology, however, such rules are less common and under-appreciated. This gap can be attributed to the difficulty in establishing general rules to encompass the immense diversity and complexity of biological systems. Furthermore, even when a rule is established, it is often challenging to map it to mechanistic details and to quantify these details. Here we report a framework that addresses these challenges for mutualistic systems. We first deduce a general rule that predicts the various outcomes of mutualistic systems, including coexistence and productivity. We further develop a standardized machine-learning-based calibration procedure to use the rule without the need to fully elucidate or characterize their mechanistic underpinnings. Our approach consistently provides explanatory and predictive power with various simulated and experimental mutualistic systems. Our strategy can pave the way for establishing and implementing other simple rules for biological systems.
The super-alertness of central banks

This paper applies Kirzner’s theory of entrepreneurial alertness to central banking. As opposed to entrepreneurs operating within the market, central banks can operate outside the market by defining its structure and regulations. We label as “super-alertness” the particular type of Kirznerian alertness that central banks are required to have to successfully achieve stable monetary equilibrium.
Sum-of-Squares Meets Program Obfuscation, Revisited

We develop attacks on the security of variants of pseudo-random generators computed by quadratic polynomials. In particular we give a general condition for breaking the one-way property of mappings where every output is a quadratic polynomial (over the reals) of the input. As a corollary, we break the degree-2 candidates for security assumptions recently proposed for constructing indistinguishability obfuscation by Ananth, Jain and Sahai (ePrint 2018) and Agrawal (ePrint 2018). We present conjectures that would imply our attacks extend to a wider variety of instances, and in particular offer experimental evidence that they break assumption of Lin-Matt (ePrint 2018).
Scalable Compiler for the TERMES Distributed Assembly System

The TERMES system is a robot collective capable of autonomous construction of 3D user-specified structures . A key component of the framework is an off-line compiler which takes in a structure blueprint and generates a directed map, in turn permitting an arbitrary number of robots to perform decentralized construction in a provably correct manner. In past work, this compiler was limited to a non-optimized search approach which scaled poorly with the structure size. Here, we recast the process as a constraint satisfaction problem and present new scalable compiler schemes and the ability to quickly generate provably correct maps (or find that none exist) of structures with up to 1 million bricks. We compare the performance of the compilers on a range of structures, and show how the transition probability between locations in the structure may be altered to improve system efficiency. This work represents an important step towards collective robotic construction of real-world structures.
Structure of the SARS-CoV nsp12 polymerase bound to nsp7 and nsp8 co-factors.

Recent history is punctuated by the emergence of highly pathogenic coronaviruses such as SARS- and MERS-CoV into human circulation. Upon infecting host cells, coronaviruses assemble a multi-subunit RNA-synthesis complex of viral non-structural proteins (nsp) responsible for the replication and transcription of the viral genome. Here, we present the 3.1 A resolution structure of the SARS-CoV nsp12 polymerase bound to its essential co-factors, nsp7 and nsp8, using single particle cryo-electron microscopy. nsp12 possesses an architecture common to all viral polymerases as well as a large N-terminal extension containing a kinase-like fold and is bound by two nsp8 co-factors. This structure illuminates the assembly of the coronavirus core RNA-synthesis machinery, provides key insights into nsp12 polymerase catalysis and fidelity and acts as a template for the design of novel antiviral therapeutics. The pathogenic human coronaviruses SARS- and MERS-CoV can cause severe respiratory disease. Here the authors present the 3.1A cryo-EM structure of the SARS-CoV RNA polymerase nsp12 bound to its essential co-factors nsp7 and nsp8, which is of interest for antiviral drug development.
Jointly Optimizing Diversity and Relevance in Neural Response Generation

Although recent neural conversation models have shown great potential, they often generate bland and generic responses. While various approaches have been explored to diversify the output of the conversation model, the improvement often comes at the cost of decreased relevance. In this paper, we propose a SpaceFusion model to jointly optimize diversity and relevance that essentially fuses the latent space of a sequence-to-sequence model and that of an autoencoder model by leveraging novel regularization terms. As a result, our approach induces a latent space in which the distance and direction from the predicted response vector roughly match the relevance and diversity, respectively. This property also lends itself well to an intuitive visualization of the latent space. Both automatic and human evaluation results demonstrate that the proposed approach brings significant improvement compared to strong baselines in both diversity and relevance.
Enhancing second-harmonic generation using dipolar-parity modes in non-planar plasmonic nanocavities

There is an active demand to develop efficient nanoscale nonlinear sources for applications in photonic circuitry, quantum optics, and biosensing. To this end, plasmonic systems have been utilized to boost the nonlinear signal generation; however, high efficiencies of frequency conversion for realistic applications remain a challenge. Metal-insulator-metal (MIM) nanocavities are good candidates for strongly concentrating the fields at the nanoscale to enhance the optical nonlinearities; however, they typically suffer from the requirement to have a quadrupolar resonance at the emission wavelength. Here we introduce non-planar MIM nanocavities with a nonlinear spacer that can strongly enhance the second-harmonic generation (SHG), despite having fundamental and emission modes of the same parity. Our experimental and numerical results indicate that the enhancement is due to the non-planar design of the cavities and the bulk nonlinearity of the spacer layer.