cssi/SciSciGPT-SciSciNet huggingface dataset:
A Nonparametric Graphical Tests of Significance in Functional GLM

A new nonparametric graphical test of significance of a covariate in functional GLM is proposed. Our approach is especially interesting due to its functional graphical interpretation of the results. As such, it is able to find not only if the factor of interest is significant but also which functional domain is responsible for the potential rejection. In the case of functional multi-way main effect ANOVA or functional main effect ANCOVA models it is able to find which groups differ (and where they differ), in the case of functional factorial ANOVA or functional factorial ANCOVA models it is able to find which combination of levels (which interactions) differ (and where they differ). The described tests are extensions of global envelope tests in the GLM models. It applies Freedman-Lane algorithm for the permutation of functions, and as such, it approximately achieves the desired significance level.
An Alternative to Natural Monopoly

We consider a shared ownership arrangement among consumers/owners as a means to organize production with an underlying decreasing average cost function typical of natural monopolies. The resulting output allocation yields a lower deadweight loss than the monopoly allocation, and is, in some cases, efficient.
Reproducibility assessment of neuromelanin-sensitive magnetic resonance imaging protocols for region-of-interest and voxelwise analyses.

Abstract Neuromelanin-sensitive MRI (NM-MRI) provides a noninvasive measure of the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). NM-MRI has been validated as a measure of both dopamine neuron loss, with applications in neurodegenerative disease, and dopamine function, with applications in psychiatric disease. Furthermore, a voxelwise-analysis approach has been validated to resolve substructures, such as the ventral tegmental area (VTA), within midbrain dopaminergic nuclei thought to have distinct anatomical targets and functional roles. NM-MRI is thus a promising tool that could have diverse research and clinical applications to noninvasively interrogate in vivo the dopamine system in neuropsychiatric illness. Although a test-retest reliability study by Langley et al. using the standard NM-MRI protocol recently reported high reliability, a systematic and comprehensive investigation of the performance of the method for various acquisition parameters and preprocessing methods has not been conducted. In particular, most previous studies used relatively thick MRI slices (~3 ​mm), compared to the typical in-plane resolution (~0.5 ​mm) and to the height of the SN (~15 ​mm), to overcome technical limitations such as specific absorption rate and signal-to-noise ratio, at the cost of partial-volume effects. Here, we evaluated the effect of various acquisition and preprocessing parameters on the strength and test-retest reliability of the NM-MRI signal to determine optimized protocols for both region-of-interest (including whole SN-VTA complex and atlas-defined dopaminergic nuclei) and voxelwise measures. Namely, we determined a combination of parameters that optimizes the strength and reliability of the NM-MRI signal, including acquisition time, slice-thickness, spatial-normalization software, and degree of spatial smoothing. Using a newly developed, detailed acquisition protocol, across two scans separated by 13 days on average, we obtained intra-class correlation values indicating excellent reliability and high contrast, which could be achieved with a different set of parameters depending on the measures of interest and experimental constraints such as acquisition time. Based on this, we provide detailed guidelines covering acquisition through analysis and recommendations for performing NM-MRI experiments with high quality and reproducibility. This work provides a foundation for the optimization and standardization of NM-MRI, a promising MRI approach with growing applications throughout clinical and basic neuroscience.
Distributed multi-GNSS timing and localization for nanosatellites

Recent advances in distribution and miniaturization among spacecraft and expansion of global navigation satellite systems (GNSS) motivate the Distributed Multi-GNSS Timing and Localization system. The DiGiTaL system is intended to provide nanosatellite swarms with unprecedented centimeter-level relative navigation accuracy in real time and nanosecond-level time synchronization through the integration of a multiconstellation GNSS receiver, a chipscale atomic clock, and an intersatellite link. This paper describes DiGiTaL's hardware and software design, architecture, and navigation software in detail. The swarming spacecraft are grouped into subsets, where differential GNSS is performed by a precise orbit determination module with integer ambiguity resolution in real time. The resulting precise orbits are then exchanged and fused by a swarm determination module, creating full-swarm knowledge. Finally, the DiGiTaL architecture is integrated into CubeSat avionics and tested with key hardware in the loop using Stanford's GNSS navigation testbed. For the first time, this paper shows the capability to perform centimeter-level precise relative navigation using commercial-off-the-shelf CubeSat hardware for spacecraft swarms.
Symmetric elliptic functions, IRF models, and dynamic exclusion processes

We introduce stochastic Interaction-Round-a-Face (IRF) models that are related to representations of the elliptic quantum group $E_{\tau,\eta}(sl_2)$. For stochasic IRF models in a quadrant, we evaluate averages for a broad family of observables that can be viewed as higher analogs of $q$-moments of the height function for the stochastic (higher spin) six vertex models. In a certain limit, the stochastic IRF models degenerate to (1+1)d interacting particle systems that we call dynamic ASEP and SSEP; their jump rates depend on local values of the height function. For the step initial condition, we evaluate averages of observables for them as well, and use those to investigate one-point asymptotics of the dynamic SSEP. The construction and proofs are based on remarkable properties (branching and Pieri rules, Cauchy identities) of a (seemingly new) family of symmetric elliptic functions that arise as matrix elements in an infinite volume limit of the algebraic Bethe ansatz for $E_{\tau,\eta}(sl_2)$.
Hayek, Hicks, Radner and four equilibrium concepts: Perfect foresight, sequential, temporary, and rational expectations

Hayek was among the first to realize that for intertemporal equilibrium to obtain all agents must have correct expectations of future prices. Before comparing four categories of intertemporal, the paper explains Hayek’s distinction between correct expectations and perfect foresight. The four equilibrium concepts considered are: (1) Perfect foresight equilibrium of which the Arrow-Debreu-McKenzie (ADM) model of equilibrium with complete markets is an alternative version, (2) Radner’s sequential equilibrium with incomplete markets, (3) Hicks’s temporary equilibrium, as extended by Bliss; (4) the Muth rational-expectations equilibrium as extended by Lucas into macroeconomics. While Hayek’s understanding closely resembles Radner’s sequential equilibrium, described by Radner as an equilibrium of plans, prices, and price expectations, Hicks’s temporary equilibrium seems to have been the natural extension of Hayek’s approach. The now dominant Lucas rational-expectations equilibrium misconceives intertemporal equilibrium, suppressing Hayek’s insights thereby retreating to a sterile perfect-foresight equilibrium.
First-passage time approach to kinetic Monte Carlo simulations of metal (100) growth

A first-passage-time (FPT) approach to accelerate kinetic Monte Carlo (KMC) simulations of metal(100) epitaxial growth with fast edge diffusion is described. In our approach, the process of singly-bonded edge diffusion is replaced by a calculation of the first-passage time for an edge diffuser to be absorbed either by corner rounding or kink attachment, while the remaining activated processes are treated with regular KMC. To calculate the FPT two different methods were used. In the first more computationally efficient method, the mean FPT was calculated using an analytical expression, which takes into account the difference between the hopping rate for an atom along the edge and at a corner site. In the second method, the full FPT distribution is numerically calculated based on the eigenvectors and eigenvalues of the corresponding transition matrix. As a test of this approach we have studied three different models of multilayer growth, including two irreversible growth models as well as an effective-medium theory model of Cu/Cu(100) growth. By taking into account the interactions of edge diffusers with other atoms we have obtained very good agreement using both methods between our FPT KMC and regular KMC simulations. In addition, we find that our FPT approach can lead to a significant speed-up compared to regular KMC simulations.
Involvement of orexin/hypocretin in the expression of social play behaviour in juvenile rats.

Social play is a highly rewarding and motivated behaviour displayed by juveniles of many mammalian species. We hypothesized that the orexin/hypocretin (ORX) system is involved in the expression of ...
Incentivizing the Missing Middle: The Role of Economic Development Policy:

The shrinking middle class and increasing income polarization in the United States are issues of concern to policy makers and others. Economic development incentives are a key policy tool used at t...
Identification of Efficient Active Sites in Nitrogen-Doped Carbon Nanotubes for Oxygen Reduction Reaction

Nitrogen-doped carbon nanotubes (NCNTs) have demonstrated great promise as an electrocatalyst alternative to platinum for oxygen reduction reaction (ORR). However, there is much disagreement regard...
Pediatric Anxiety Disorders: A Cost of Illness Analysis

Few studies provide information about the clinical correlates of economic costs in pediatric anxiety disorders. This study uses baseline data from a randomized trial involving 209 children and adolescents with clinical anxiety to examine clinical and demographic correlates of direct and indirect costs. Measured costs included the direct costs of mental health services and the indirect costs resulting from children’s missed school and parents’ missed work. Validated measures of anxiety and depression severity and of internalizing and externalizing behaviors were reported by youth, their parents, and independent evaluators. Seventy-two percent of youth (n = 150) had positive costs. Among these youth, the mean annual total cost was $6405 (sd = $11,674), of which $5890 represented direct cost and $4658 represented indirect cost. Higher average costs were correlated with greater child anxiety and depression severity (p < 0.001). Most pediatric anxiety disorders result in substantial individual and family costs, and costs may increase rapidly with elevated anxiety severity and depressed mood.
Bivariate semialgebraic splines

Abstract Semialgebraic splines are bivariate splines over meshes whose edges are arcs of algebraic curves. They were first considered by Wang, Chui, and Stiller. We compute the dimension of the space of semialgebraic splines in two extreme cases. If the polynomials defining the edges span a three-dimensional space of polynomials, then we compute the dimensions from the dimensions for a corresponding rectilinear mesh. If the mesh is sufficiently generic, we give a formula for the dimension of the spline space valid in large degree and bound how large the degree must be for the formula to hold. We also study the dimension of the spline space in examples which do not satisfy either extreme. The results are derived using commutative and homological algebra.
Tunable contact resistance in transition metal dichalcogenide lateral heterojunctions

Contact resistance of semiconducting transition metal dichalcogenides has been shown to decrease in lateral heterojunctions formed with their metallic phases but its origins remain elusive. Here we combine first-principles and quantum transport calculations to rationalize the contact resistance of these structures in terms of phase, composition (${\mathrm{WTe}}_{2}, {\mathrm{MoTe}}_{2}, {\mathrm{WSe}}_{2}$, and ${\mathrm{MoSe}}_{2}$), and length of the channel. We find that charge injection in metallic 1T'-${\mathrm{WTe}}_{2}$/1T'-${\mathrm{MoTe}}_{2}$ junctions is nearly ideal as electrode Bloch states remain delocalized through the channel. Mixtures of 1T' selenides and tellurides depart from this scenario due to the momentum mismatch between states in the lead and channel. In semiconducting channels, the large Schottky barriers degrade the electrical contacts. Around band edges, contact resistance values are about an order of magnitude lower than those obtained experimentally suggesting that doping and phase-engineering could be employed to overcome this issue. We predict that transport regime in these junctions shifts from thermionic emission to tunneling for channels shorter than 3 nm at room temperature. We also discuss the presence of states at the metal/semiconductor interfaces. By underpinning mechanisms to control the contact resistance in heterogeneous two-dimensional materials, this work proves valuable towards the development of devices suitable for optoelectronics and phase-change materials applications.
A portable, low-cost device for precise control of specimen temperature under stereomicroscopes

To facilitate precise and convenient control of biological sample temperature, we developed a low-cost device that can be used independently or with any stereomicroscope. The purpose of the device is to control the thermal environment during experimental intervals in which a specimen must be manipulated outside of an incubator, e.g. for dissection or slide-mounting in preparation for imaging. Sample temperatures can be both cooled to below and heated to above room temperatures, and stably maintained at a precision of +/- 0.1˚C. To demonstrate the utility of this device, we report improved characterization of the penetrance of a short-acting temperature-sensitive allele in C. elegans embryos, and identification of the upper temperature threshold for embryonic viability for six Caenorhabditis species. By controlling the temperature environment even as a specimen is manipulated, this device offers consistency and flexibility, reduces environmental noise, and enables precision timing in experiments requiring temperature shifts.
Off-Grid Aware Channel and Covariance Estimation in mmWave Networks

The spectrum scarcity at sub-6 GHz spectrum has made millimeter-wave (mmWave) frequency band a key component of the next-generation wireless networks. While mmWave spectrum offers extremely large transmission bandwidths to accommodate ever-increasing data rates, unique characteristics of this new spectrum need special consideration to achieve the promised network throughput. In this work, we consider the off-grid targets (basis mismatch) problem for mmWave communications. The off-grid effect naturally appears in compressed sensing (CS) techniques adopting a discretization approach for representing the angular domain. This approach yields a finite set of discrete angle points, which are an approximation to the continuous angular space, and hence degrade the accuracy of related parameter estimation. In order to cope with the off-grid effect, we present a novel parameter-perturbation framework to efficiently estimate the channel and the covariance for mmWave networks. The proposed algorithms employ a smart perturbation mechanism in conjunction with a low-complexity greedy framework of simultaneous orthogonal matching pursuit (SOMP), and jointly solve for the off-grid parameters and weights. Numerical results show a significant performance improvement through our novel framework as a result of handling the off-grid effects, which is totally ignored in the conventional sparse mmWave channel or covariance estimation algorithms.
Plasmonic titanium nitride via atomic layer deposition: A low-temperature route

To integrate plasmonic devices into industry, it is essential to develop scalable and CMOS compatible plasmonic materials. In this work, we report high plasmonic quality titanium nitride (TiN) on c-plane sapphire grown by plasma-enhanced atomic layer deposition. TiN with low losses, high metallicity, and a plasma frequency below 500 nm was achieved at temperatures less than 500 °C by exploring the effects of chemisorption time, substrate temperature, and plasma exposure time on the material properties. A reduction in chemisorption time mitigates premature precursor decomposition at TS > 375 °C, and a trade-off between reduced impurity concentration and structural degradation caused by plasma bombardment is achieved for 25 s plasma exposure. 85 nm thick TiN films grown at a substrate temperature of 450 °C, compatible with CMOS processes, with 0.5 s chemisorption time and 25 s plasma exposure exhibited a high plasmonic figure of merit ( | e ′ / e ′ ′ |) of 2.8 and resistivity of 31 μ Ω cm. As a result of the improved quality, subwavelength apertures were fabricated in the TiN thin films and are shown to exhibit extraordinary transmission.
Structure–Property Study of Homoleptic Zinc(II) Complexes of Di(arylethynyl) Azadipyrromethene as Nonfullerene Acceptors for Organic Photovoltaics: Effect of the Aryl Group

Azadipyrromethene-based zinc(II) complexes were demonstrated to be promising molecular organic semiconductors for electronic applications due to their easy preparation, tunable structures and high ...
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples

Deep neural network (DNN) has demonstrated its success in multiple domains. However, DNN models are inherently vulnerable to adversarial examples, which are generated by adding adversarial perturbations to benign inputs to fool the DNN model to misclassify. In this paper, we present a cross-layer strategic ensemble framework and a suite of robust defense algorithms, which are attack-independent, and capable of auto-repairing and auto-verifying the target model being attacked. Our strategic ensemble approach makes three original contributions. First, we employ input-transformation diversity to design the input-layer strategic transformation ensemble algorithms. Second, we utilize model-disagreement diversity to develop the output-layer strategic model ensemble algorithms. Finally, we create an input-output cross-layer strategic ensemble defense that strengthens the defensibility by combining diverse input transformation based model ensembles with diverse output verification model ensembles. Evaluated over 10 attacks on ImageNet dataset, we show that our strategic ensemble defense algorithms can achieve high defense success rates and are more robust with high attack prevention success rates and low benign false negative rates, compared to existing representative defenses.
Effective bandwidths and performance bounds in high-speed communication systems

This paper is concerned with quality of service guarantees in an environment with bursty traffic streams, such as those in the emerging ATM-based broadband ISDN.4 For virtually any traffic stream, new performance bounds are obtained in terms of effective bandwidths and burstiness constraints. The new bounds are tighter than those previously available and are asymptotically achievable, potentially resulting in better performance when used in traffic management. Various performance measures are considered. It is shown that the effective bandwidth of a departing traffic is bounded by that of the incoming traffic. For traffic streams having independent increments and Markov-modulated processes, the bounds are further refined to a point close to the exact values in some cases. Computationally, evaluation of the bounds requires less effort than finding effective bandwidths and burstiness constraints. Finally, the bounds are applied to routing control to find the near-optimal probabilistic routing policy.
Overcoming High Nanopore Basecaller Error Rates for DNA Storage via Basecaller-Decoder Integration and Convolutional Codes

As magnetization and semiconductor based storage technologies approach their limits, bio-molecules, such as DNA, have been identified as promising media for future storage systems, due to their high storage density (petabytes/gram) and long-term durability (thousands of years). Furthermore, nanopore DNA sequencing enables high-throughput sequencing using devices as small as a USB thumb drive and thus is ideally suited for DNA storage applications. Due to the high insertion/deletion error rates associated with base-called nanopore reads, current approaches rely heavily on consensus among multiple reads and thus incur very high reading costs. We propose a novel approach which overcomes the high error rates in basecalled sequences by integrating a Viterbi error correction decoder with the basecaller, enabling the decoder to exploit the soft information available in the deep learning based basecaller pipeline. Using convolutional codes for error correction, we experimentally observed 3x lower reading costs than the state-of-the-art techniques at comparable writing costs.The code, data and Supplementary Material is available at https://github.com/shubhamchandak94/nanopore_dna_storage.
Collision avoidance and Drone surveillance using Thread protocol in V2V and V2I communications

According to the World Health Organizations (WHO) report nearly 1.25 million people die in road accidents every year. This creates a need for Advanced Driver Assist Systems (ADAS) which can ensure safe travel. To tackle the above challenge in existing the ADAS, Intra-vehicular communications (V2V) and vehicle to infrastructure communications (V2I) has been one of the predominant research topics nowadays due to the rapid growth of automobile industries and ideology of producing autonomous cars in the near future. The key feature of V2V communication is vehicle to vehicle collision detection by transmitting information like vehicle speed and position of a vehicle to other vehicles in the same location using wireless sensor networks (WSN). On the other hand, Unmanned Aerial Vehicle (UAV) systems are growing at a rapid rate in various aspects of life including dispatch of medicines and undergo video surveillance during an emergency due to less air traffic. This paper demonstrates the practice of integrating V2V communication with Thread, one of the low power WSN for data transmission, to initiate adaptive cruise control in a vehicle during a crisis. Also, UAV systems are employed as a part of V2I system to provide aerial view video surveillance if any accident occurs.
E-books in the University of California Libraries

ABSTRACT In response to the acquisition of various e-book packages by individual campuses, the University of California Libraries' Collection Development Committee charged a task force in June 2007 to develop principles to integrate the acquisition of e-books into existing system-wide collection development activities. Based on the work of the task force to date, this article will discuss the current state of e-book implementation on the University of California campuses as well as the draft “Principles for Acquiring and Licensing E-book Packages and Services” developed by the task force.
12 – The District of Columbia’s Initial Success as a State Regulator on AUES

Publisher Summary This chapter highlights the success that can be obtained through hard work even though a state may have little first-hand experience with a complex military site. The validation of the major premise in the District of Columbia's report—that more hazardous material was buried in Spring Valley—forced the Corps and the EPA to begin a halting partnership effort with the District's Environmental Health Administration to design an appropriate cleanup plan for Spring Valley. The District of Columbia was the remedial project manager for Spring Valley from 1998 until their removal from the partnering team in March 2003. Due to the rotation of government workers, it is important for residents and regulators to set forth an accurate picture of reality at some point in the site cleanup history, pointing out the lies and falsehoods. Throughout many reports and speeches, the Corps has maintained that there were only small quantities of munitions and chemicals on hand. The study also explores an example of how listening to a simple observation by a reporter (actually, a magazine writer) led to the discovery of a major problem area and undoubtedly kept a lot of kids from falling prey to Lewisite contamination.
Chapter 13 – Cerro Prieto Power Station, Baja California Norte, Mexico

Publisher Summary Mexico was among the earliest countries to operate a commercial geothermal power plant at a liquid-dominated resource, commissioning its first single-flash plant in 1973. Currently, Mexico is the world's third largest generator of electricity from geothermal energy with a total installed capacity of 953 MW. Las Tres Virgenes is about half-way down the Baja California peninsula in a volcanic complex, and generates 10 MW from two 5 MW units. Cerro Prieto, the focus of this chapter, lies south of California's Imperial Valley, just over the border from the United States, and has an installed capacity of 720 MW. Reservoir models have been constructed based on this wealth of information. One numerical model was developed to assess the possibility of adding an 80 MW plant to the then-existing three plants using wells to the east of those that were supplying CP-III. The power units at Cerro Prieto were developed sequentially over a period of 27 years starting with CP-I Unit 1 in 1973 and culminating in 2000 with the installation of the four-unit, 100 MW plant at CP-IV. Plans are now underway to move the flash station from next to the evaporation pond, and to have two of them situated closer to the CP-II and CP-III well fields in order to use the waste brine as well as excess low-pressure steam from those plants to bring Unit 5 back to its rated output.
Decentralized Fuzzy Control of Multiple Nonholonomic Vehicles

This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on a simple 8-bit microcontroller, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the noisy direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: forward, behind, left, and right; and the distance into three values: near, far, and gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and an attractive force towards the goal. A fuzzy inference system is used to obtain control values from a small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.
Long-distance quantum communication with neutral atoms

The architecture proposed by Duan, Lukin, Cirac, and Zoller (DLCZ) for long-distance quantum communication with atomic ensembles is analyzed. Its fidelity and throughput in entanglement distribution, entanglement swapping, and quantum teleportation is derived within a framework that accounts for multiple excitations in the ensembles as well as loss and asymmetries in the channel. The DLCZ performance metrics that are obtained are compared to the corresponding results for the trapped-atom quantum communication architecture that has been proposed by a team from the Massachusetts Institute of Technology and Northwestern University (MIT and NU). Both systems are found to be capable of high-fidelity entanglement distribution. However, the DLCZ scheme only provides conditional teleportation and repeater operation, whereas the MIT-NU architecture affords full Bell-state measurements on its trapped atoms. Moreover, it is shown that achieving unity conditional fidelity in DLCZ teleportation and repeater operation requires ideal photon-number resolving detectors. The maximum conditional fidelities for DLCZ teleportation and repeater operation that can be realized with nonresolving detectors are 1/2 and 2/3, respectively.
Main Rotor Broadband Noise Study in the DNW

An acoustics test of a 2/5 scale model BO-105 helicopter main rotor was conducted in the Duits-Nederlandse Windtunnel (DNW). A range of operating conditions was tested from hover to moderately high flight speeds for various climb and descent rates at different thrust settings. Diagnostic tests including rotor speed and blade geometry changes were made to better isolate and study particular broadband self noise sources. Acoustic data in the form of acoustic pressure time histories and power spectra are used to demonstrate the regions of importance of the different broadband noise sources and their sensitivity to operating conditions. To help interpret the data, comparisons are made to predictions of rotor broadband noise. The predictions are based on self noise data previously obtained from isolated airfoil sections and the use of the NASA ROTONET program to define rotor performance and to sum contributions of noise from individual blade segments. An important result herein is the identification and articulation of a previously unheralded rotor broadband noise source. This source is blade-turbulent wake interaction (BWI) noise which dominates the spectra in the mid-frequencies for off-peak blade-vortex interaction (BVI) noise flight conditions.
HOW DO FARMERS WHO ADOPT MULTIPLE CONSERVATION PRACTICES DIFFER FROM THEIR NEIGHBORS

Wind erosion is a serious environmental problem in the inland Pacific Northwest, US. In addition to on-farm damage to soil and crop quality, it causes off-farm damage, including human respiratory illness, traffic accidents and diminished recreational values. Three key practices for effectively controlling wind erosion in eastern Washington are reduced tillage, continuous spring cropping and vegetative wind strips. Although these are effective in controlling wind erosion, their adoption by farmers in the region has been slow. Technology adoption theory has been classified into three paradigms: income, utility and innovation-adoption. This study on adoption of wind erosion control practices draws from all three paradigms. However, unlike most past research, this study distinguishes between single-practice adopters and multiple-practice adopters, and compares single-practice adopters with zero-practice adopters. Data were obtained from a random sample survey of 266 farmers in six semi-arid counties in a region of east-central Washington State prone to wind erosion. Statistical results revealed: (1) that adopters of multiple conservation practices contrast more sharply with non-adopters than do adopters of a single conservation practice; and (2) adopters of a single practice differ more from zero-practice adopters than they do from all other farmers (including adopters of other practices). More specifically, this study recognizes heterogeneity among 'adopters' in erosion control, and suggests that there may be some hierarchy among adopters in strength of innovation. It also supports earlier findings by sociologists that early adopters have more financial resources or larger farms and that education may aid adoption. Adopters were more aware of an erosion control educational program. Multiple-practice adopters are a distinct identifiable group, who may play a key role as innovators who can influence neighbors to adopt effective conservation practices. These individuals also possess unique information on the comparative cost, yields and technical challenges of alternative conservation practices that could be used on farms with similar soil and climatic conditions. Knowledge of the attributes associated with innovative multiple-practice adopters may permit soil conservation policymakers and field staff to target educational programs more accurately during the early stages of technology dissemination. Conservation-practice dissemination strategies may benefit by including innovative farmers in leadership roles in the initial stage of conservation education programs.
Chapter 4 – Batch Reactor

The batch reactor is widely used in industry and is the preferred reactor in laboratories and in pharmaceutical industries. The performance of a batch reactor can be analyzed via material and energy balances. The reactor is initially loaded with substrates; and there is no addition or withdrawal until the end of the reaction. The temperature and concentrations change with time, which are governed by differential equations derived from materials and energy balances. The solutions for these differential equations require a numerical integrator, for which the ODExLIMS routine is introduced for use with Microsoft Excel. For simple kinetics, methods of solution are introduced, with some solutions listed for reactions with simple kinetics. Batch reactor sizing depends on the productivity requirement, that is, processing efficiency as well as the quality requirement, the cost of raw materials, and the value of the product(s). Examples are given on how these problems can be solved in a concise manner. For more complicated reactions based on complex raw materials, a relative time, or H-Factor, concept is introduced for ease of process control and performance characterization. Maximizing productivity in a batch reactor system, as well as reactor sizing based on the time curve of concentration, can be as easy as drawing a pinch line.
An Accessible Method for Screening Aerosol Filtration Identifies Poor-Performing Commercial Masks and Respirators

Background: The COVID-19 pandemic has presented an acute need for masks, specifically N95 respirators to be used by healthcare workers contacting COVID-19 patie
Disappearance of periodic X-ray minima in AM Her

Optical, soft X-ray, and medium energy X-ray measurements taken during an unusual high state of AM Her are reported. The X-ray and secondary optical minima disappeared from the light curve. The X-ray flux varied perodically. In each X-ray band, the flux during the expected phase of minimum was approximately the same as the average during the rest of the cycle. The optical and medium energy X-ray fluxes were at all-time highs; however, the soft X-ray flux was low by a factor of 3 compared to the nominal high state. This change in the ratio of medium to soft X-ray flux is difficult to fit into the standard scenario for AM Her, where soft X-rays are interpreted as reprocessed optical and medium energy X-ray flux. The peculiar light curve of AM Her was probably caused by a small shift in the position of the accretion column with respect to the rotation axis, so that the normal grazing eclipse of the accretion column did not take place.
Introducing an Optimization- and explicit Runge-Kutta- based Approach to Perform Dynamic Flux Balance Analysis

In this work we introduce the generalized Optimization- and explicit Runge-Kutta-based Approach (ORKA) to perform dynamic Flux Balance Analysis (dFBA), which is numerically more accurate and computationally tractable than existing approaches. ORKA is applied to a four-tissue (leaf, root, seed, and stem) model of Arabidopsis thaliana, p-ath773, uniquely capturing the core-metabolism of several stages of growth from seedling to senescence at hourly intervals. Model p-ath773 has been designed to show broad agreement with published plant-scale properties such as mass, maintenance, and senescence, yet leaving reaction-level behavior unconstrainted. Hence, it serves as a framework to study the reaction-level behavior necessary for observed plant-scale behavior. Two such case studies of reaction-level behavior include the lifecycle progression of sulfur metabolism and the diurnal flow of water throughout the plant. Specifically, p-ath773 shows how transpiration drives water flow through the plant and how water produced by leaf tissue metabolism may contribute significantly to transpired water. Investigation of sulfur metabolism elucidates frequent cross-compartment exchange of a standing pool of amino acids which is used to regulate the proton flow. Overall, p-ath773 and ORKA serve as scaffolds for dFBA-based lifecycle modeling of plants and other systems to further broaden the scope of in silico metabolic investigation.
Somatic genetic aberrations in benign breast disease and the risk of subsequent breast cancer.

It is largely unknown how the development of breast cancer (BC) is transduced by somatic genetic alterations in the benign breast. Since benign breast disease is an established risk factor for BC, we established a case-control study of women with a history of benign breast biopsy (BBB). Cases developed BC at least one year after BBB and controls did not develop BC over an average of 17 years following BBB. 135 cases were matched to 69 controls by age and type of benign change: non-proliferative or proliferation without atypia (PDWA). Whole-exome sequencing (WES) was performed for the BBB. Germline DNA (available from n = 26 participants) was utilized to develop a mutation-calling pipeline, to allow differentiation of somatic from germline variants. Among the 204 subjects, two known mutational signatures were identified, along with a currently uncatalogued signature that was significantly associated with triple negative BC (TNBC) (p = 0.007). The uncatalogued mutational signature was validated in 109 TNBCs from TCGA (p = 0.001). Compared to non-proliferative samples, PDWA harbors more abundant mutations at PIK3CA pH1047R (p < 0.001). Among the 26 BBB whose somatic copy number variation could be assessed, deletion of MLH3 is significantly associated with the mismatch repair mutational signature (p < 0.001). Matched BBB-cancer pairs were available for ten cases; several mutations were shared between BBB and cancers. This initial study of WES of BBB shows its potential for the identification of genetic alterations that portend breast oncogenesis. In future larger studies, robust personalized breast cancer risk indicators leading to novel interception paradigms can be assessed.
TiFL: A Tier-based Federated Learning System

Federated Learning (FL) enables learning a shared model acrossmany clients without violating the privacy requirements. One of the key attributes in FL is the heterogeneity that exists in both resource and data due to the differences in computation and communication capacity, as well as the quantity and content of data among different clients. We conduct a case study to show that heterogeneity in resource and data has a significant impact on training time and model accuracy in conventional FL systems. To this end, we propose TiFL, a Tier-based Federated Learning System, which divides clients into tiers based on their training performance and selects clients from the same tier in each training round to mitigate the straggler problem caused by heterogeneity in resource anddata quantity. To further tame the heterogeneity caused by non-IID (Independent and Identical Distribution) data and resources, TiFL employs an adaptive tier selection approach to update the tiering on-the-fly based on the observed training performance and accuracy. We prototype TiFL in a FL testbed following Google's FL architecture and evaluate it using the state-of-the-art FL benchmarks. Experimental evaluation shows that TiFL outperforms the conventional FL in various heterogeneous conditions. With the proposed adaptive tier selection policy, we demonstrate that TiFL achieves much faster training performance while achieving the same or better test accuracy across the board.
Effects of State Law Limiting Postoperative Opioid Prescription in Patients after Cesarean Delivery

Background The impact of the Florida State law House Bill 21 (HB 21) restricting the duration of opioid prescriptions for acute pain in patients after cesarean delivery is unknown. Our objective was to assess the association of the passage of Florida State law HB 21 with trends in discharge opioid prescription practices following cesarean delivery, necessity for additional opioid prescriptions, and emergency department visits at a large tertiary care center. Methods This was a retrospective cohort study conducted at a large, public hospital. The 2 cohorts represented the period before and after implementation of the law. Using a confounder-adjusted segmented regression analysis of an interrupted time series, we evaluated the association between HB 21 and trends in the proportions of patients receiving opioids on discharge, duration of opioid prescriptions, total opioid dose prescribed, and daily opioid dose prescribed. We also compared the need for additional opioid prescriptions within 30 days of discharge and the prevalence of emergency department visits within 7 days after discharge. Results Eight months after implementation of HB 21, the mean duration of opioid prescriptions decreased by 2.9 days (95% confidence interval [CI], 5.2-0.5) and the mean total opioid dose decreased by 20.1 morphine milligram equivalents (MME; 95% CI, 4-36.3). However, there was no change in the proportion of patients receiving discharge opioids (95% CI of difference, -0.1 to 0.16) or in the mean daily opioid dose (mean difference, 5.3 MME; 95% CI, -13 to 2.4). After implementation of the law, there were no changes in the proportion of patients who required additional opioid prescriptions (2.1% vs 2.3%; 95% CI of difference, -1.2 to 1.5) or in the prevalence of emergency department visits (2.4% vs 2.2%; 95% CI of difference, -1.6 to 1.1). Conclusions Implementation of Florida Law HB 21 was associated with a lower total prescribed opioid dose and a shorter duration of therapy at the time of hospital discharge following cesarean delivery. These reductions were not associated with the need for additional opioid prescriptions or emergency department visits.
The Lost Generation? Labor Market Outcomes for Post Great Recession Entrants

I study cohort patterns in the labor market outcomes of recent college graduates, examining changes surrounding the Great Recession. Recession entrants have lower wages and employment than those of earlier cohorts; more recent cohorts’ employment is even lower, but the newest entrants’ wages have risen. I relate these changes to "scarring" effects of initial conditions. I demonstrate that adverse early conditions permanently reduce new entrants’ employment probabilities. I also replicate earlier results of medium-term scarring effects on wages that fade out by the early 30s. But scarring cannot account for the employment collapse for recent cohorts. There was a dramatic negative structural break in college graduates’ employment rates, beginning around the 2005 entry cohort, that shows no sign of abating.
Self-Assembly of a Chiral Cubic Three-Connected Net from the High Symmetry Molecules C60 and SnI4

The design of new chiral materials usually requires stereoselective organic synthesis to create molecules with chiral centers. Less commonly, achiral molecules can self-assemble into chiral materia...
The two-phase approximation for black hole collisions: is it robust?

Recently, Abrahams and Cook devised a method of estimating the total radiated energy resulting from collisions of distant black holes by applying Newtonian evolution to the holes up to the point where a common apparent horizon forms around the two black holes and subsequently applying Schwarzschild perturbation techniques. Despite the crudeness of their method, their results for the case of head-on collisions were surprisingly accurate. Here we take advantage of the simple radiated energy formula devised in the close-slow approximation for black hole collisions to test how strongly the Abrahams - Cook result depends on the choice of moment when the method of evolution switches over from Newtonian to general relativistic evolution. We find that their result is robust, not depending strongly on this choice.
An Overview of Academic Tax Accounting Research Drawing on U.S. Multinational Taxation

Author(s): Shevlin, Terrence | Abstract: Economics-based tax research in accounting draws heavily on the Scholes and Wolfson framework. The framework develops a global approach to tax planning where all parties, all taxes, and all costs are to be considered in effective tax planning. Effective tax planning is distinct from tax minimization as the goal of the former is to maximize the after-tax rate of return. The first empirical applications of the framework followed the passage of the Tax Reform Act of 1986. Taxation of multinationals has long been of interest to accounting (and other) researchers and continues to be of interest. The Tax Cuts and Jobs Act of 2017 changed many tax laws including how the U.S. taxes U.S. multinationals. Research examining the ramifications of this latest Tax Act is already well under way.
Spherical contours, IR divergences and the geometry of Feynman parameter integrands at one loop

Spherical contours introduced in [1] translate the concept of “discontinuity across a branch cut” to Feynman parameter space. In this paper, we further explore spherical contours and connect them to the computation of leading IR divergences of 1 loop graphs directly in Feynman parameter space. These spherical contours can be used to develop a Feynman parameter space analog of “Leading Singularities” of loop integrands which allows us to develop a method of determining Feynman parameter integrands without the need to sum over Feynman diagrams in momentum space. Finally, we explore some interesting features of Feynman parameter integrands in $$ \mathcal{N} $$ = 4 SYM.
Compile-time Parallelization of Subscripted Subscript Patterns

An increasing number of scientific applications are making use of irregular data access patterns. An important class of such patterns involve subscripted subscripts, wherein an array value appears in the index expression of another array. Even though the information required to parallelize loops with such patterns is available in the class of programs that we analyze, present compiler techniques fall short of analyzing that information. In this paper we present a study of subscripted subscripts, the properties that define the subscript arrays, and an algorithm based on symbolic range aggregation, that will help prove the presence of some of the properties of the subscript array in the program. We show that, in an important class of programs, the algorithm can boost the performance from essentially sequential execution to close to fully parallel.
Realization and connectivity of the graphs of origami flat foldings

We investigate the graphs formed from the vertices and creases of an origami pattern that can be folded flat along all of its creases. As we show, this is possible for a tree if and only if the internal vertices of the tree all have even degree greater than two. However, we prove that (for unbounded sheets of paper, with a vertex at infinity representing a shared endpoint of all creased rays) the graph of a folding pattern must be 2-vertex-connected and 4-edge-connected.