cssi/SciSciGPT-SciSciNet huggingface dataset:
Spectral and Energy Efficiency in Cognitive Radio Systems With Unslotted Primary Users and Sensing Uncertainty

This paper studies energy efficiency (EE) and average throughput maximization for cognitive radio systems in the presence of unslotted primary users. It is assumed that primary user activity follows an ON–OFF alternating renewal process. Secondary users first sense the channel possibly with errors in the form of miss detections and false alarms, and then, start the data transmission only if no primary user activity is detected. The secondary user transmission is subject to constraints on collision duration ratio, which is defined as the ratio of average collision duration to transmission duration. In this setting, the optimal power control policy which maximizes the EE of the secondary users or maximizes the average throughput while satisfying a minimum required EE under average/peak transmit power and average interference power constraints is derived. Subsequently, low-complexity algorithms for jointly determining the optimal power level and frame duration are proposed. The impact of probabilities of detection and false alarm, transmit and interference power constraints on the EE, average throughput of the secondary users, optimal transmission power, and the collisions with primary user transmissions are evaluated. In addition, some important properties of the collision duration ratio are investigated. The tradeoff between the EE and average throughput under imperfect sensing decisions and different primary user traffic are further analyzed.
Model-agnostic meta-learning for fast adaptation of deep networks

We propose an algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a variety of different learning problems, including classification, regression, and reinforcement learning. The goal of meta-learning is to train a model on a variety of learning tasks, such that it can solve new learning tasks using only a small number of training samples. In our approach, the parameters of the model are explicitly trained such that a small number of gradient steps with a small amount of training data from a new task will produce good generalization performance on that task. In effect, our method trains the model to be easy to fine-tune. We demonstrate that this approach leads to state-of-the-art performance on two few-shot image classification benchmarks, produces good results on few-shot regression, and accelerates fine-tuning for policy gradient reinforcement learning with neural network policies.
A Fokker-Planck reaction model for the epitaxial growth and shape transition of quantum dots.

We construct a Fokker–Planck reaction (FPR) model to investigate the dynamics of the coupled epitaxial growth and shape transition process of an array of quantum dots (QDs). The FPR model is based ...
Effect of compressibility on plasma-based transition control for a wing with leading-edge excrescence

Compressibility effects were numerically investigated for use of plasma-based flow control, which was applied to delay transition generated by excrescence on the leading edge of a wing. The wing airfoil section incorporates a geometry that is representative of modern reconnaissance air vehicles, and has an appreciable region of laminar flow at design conditions. Modification of the leading edge can be caused by the accumulation of debris, insect impacts, microscopic ice crystal formation, damage, or structural fatigue, resulting in premature transition and an increase in drag. A dielectric barrier discharge DBD plasma actuator, located downstream of the excrescence, was employed to delay transition, mitigate the effects of turbulence, decrease drag, and increase energy efficiency. Solutions were obtained for several Mach numbers, up to the transonic range. The effect of compressibility on transitional behaviour was explored, and the effectiveness of plasma-based control to delay transition with increasing Mach number was determined.
High-speed nonpolar InGaN/GaN LEDs for visible-light communication

High-speed nonpolar InGaN/GaN LEDs on free-standing GaN substrates with a peak emission wavelength between 455–465 nm were fabricated. A large frequency modulation bandwidth of 524 MHz and an output power of 1.5 mW are obtained.
Fast causal inference with non-random missingness by test-wise deletion

Many real datasets contain values missing not at random (MNAR). In this scenario, investigators often perform list-wise deletion, or delete samples with any missing values, before applying causal discovery algorithms. List-wise deletion is a sound and general strategy when paired with algorithms such as FCI and RFCI, but the deletion procedure also eliminates otherwise good samples that contain only a few missing values. In this report, we show that we can more efficiently utilize the observed values with test-wise deletion while still maintaining algorithmic soundness. Here, test-wise deletion refers to the process of list-wise deleting samples only among the variables required for each conditional independence (CI) test used in constraint-based searches. Test-wise deletion therefore often saves more samples than list-wise deletion for each CI test, especially when we have a sparse underlying graph. Our theoretical results show that test-wise deletion is sound under the justifiable assumption that none of the missingness mechanisms causally affect each other in the underlying causal graph. We also find that FCI and RFCI with test-wise deletion outperform their list-wise deletion and imputation counterparts on average when MNAR holds in both synthetic and real data.
Systematic, appropriate, and cost-effective application of security technologies in U.S. public schools to reduce crime, violence, and drugs

As problems of violence and crime become more prevalent in our schools, more and more school districts will elect to use security technologies to control these problems. While the desired change in student and community attitudes will require significant systemic change through intense US social programs, security technologies can greatly augment school staff today by providing services similar to having extra adults present. Technologies such as cameras, sensors, drug detection, biometric and personnel identification, lighting, barriers, weapon and explosives detection, anti- graffiti methods, and duress alarms can all be effective, given they are used in appropriate applications, with realistic expectations and an understanding of limitations. Similar to a high-risk government facility, schools must consider a systems approach to security, which includes the use of personnel and procedures as well as security technologies, such that the synergy created by all these elements together contributes more tot he general 'order maintenance' of the facility than could be achieved by separate measures not integrated or related.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Including surface ligand effects in continuum elastic models of nanocrystal vibrations

The measured low frequency vibrational energies of some quantum dots (QDs) deviate from the predictions of traditional elastic continuum models. Recent experiments have revealed that these deviations can be tuned by changing the ligands that passivate the QD surface. This observation has led to speculation that these deviations are due to a mass-loading effect of the surface ligands. In this article, we address this speculation by formulating a continuum elastic theory that includes the dynamical loading by elastic surface ligands. We demonstrate that this model is capable of accurately reproducing the l = 0 phonon energy across a variety of different QD samples, including cores with different ligand identities and epitaxially grown CdSe/CdS core/shell heterostructures. We highlight that our model performs well even in the small QD regime, where traditional elastic continuum models are especially prone to failure. Furthermore, we show that our model combined with Raman measurements can be used to infer the elastic properties of surface bound ligands, such as sound velocities and elastic moduli, that are otherwise challenging to measure.
High seismic attenuation at a mid-ocean ridge reveals the distribution of deep melt.

At most mid-ocean ridges, a wide region of decompression melting must be reconciled with a narrow neovolcanic zone and the establishment of full oceanic crustal thickness close to the rift axis. Two competing paradigms have been proposed to explain melt focusing: narrow mantle upwelling due to dynamic effects related to in situ melt or wide mantle upwelling with lateral melt transport in inclined channels. Measurements of seismic attenuation provide a tool for identifying and characterizing the presence of melt and thermal heterogeneity in the upper mantle. We use a unique data set of teleseismic body waves recorded on the Cascadia Initiative's Amphibious Array to simultaneously measure seismic attenuation and velocity across an entire oceanic microplate. We observe maximal differential attenuation and the largest delays ([Formula: see text] s and δTS ~ 2 s) in a narrow zone <50 km from the Juan de Fuca and Gorda ridge axes, with values that are not consistent with laboratory estimates of temperature or water effects. The implied seismic quality factor (Qs ≤ 25) is among the lowest observed worldwide. Models harnessing experimentally derived anelastic scaling relationships require a 150-km-deep subridge region containing up to 2% in situ melt. The low viscosity and low density associated with this deep, narrow melt column provide the conditions for dynamic mantle upwelling, explaining a suite of geophysical observations at ridges, including electrical conductivity and shear velocity anomalies.
Speed Mentoring: An Innovative Method to Meet the Needs of the Young Surgeon

Objective Speed mentoring has recently been used by several medical organizations as a strategy to establish mentoring relationships, which are felt to be critically important in the development of the surgeon. This study assesses a surgical speed-mentoring program at the 2015 American College of Surgeons (ACS) Clinical Congress. Design A steering committee designed the speed-mentoring program to match 60 ACS Resident and Associate Society mentees with a mix of junior and senior leadership of ACS. Each mentee met with 5 mentors for 10 minutes each during the 1 hour session. After participation in the activity, surveys were provided to assess the event. The survey included forced-choice questions using Likert-scales as well as open-ended questions. Mentor and mentee responses were compared using Medcalc software using comparison of means and comparison of proportion, with p Setting The study was undertaken at the 2015 ACS Clinical Congress. Participants A total of 60 mentors and 49 mentees participated in the inaugural ACS Speed-Mentoring activity. The postactivity survey was completed by 54 mentors (90%) and 39 mentees (79.5%). Results There was a high level of satisfaction with the activity, with 100% of mentors and mentees stating that they would recommend the activity to a colleague. There was overall high satisfaction with the organization of the session by both the mentors and the mentees although the mentors were more likely to feel that they needed more time for each interaction. More mentees (93%) than mentors (68.5%) felt they were likely to develop a mentoring relationship with one of their matches outside of the organized session. Conclusions We demonstrated that a speed-mentoring event at a national surgical meeting offers an effective platform for mentoring and is mutually beneficial to both mentors and mentees. Data collected here will be used to modify and improve the design of future speed-mentoring sessions.
Treatment of Severe Nephrotic Syndrome With Meclofenamate: An Uncontrolled Pilot Study

The effect of meclofenamate on urinary protein excretion, level of serum albumin, and renal function was studied prospectively in 30 patients with corticosteroid-resistant severe nephrotic syndrome: 16 with focal segmental glomerulosclerosis, 12 with membranous glomerulopathy, and 2 with minimal-lesion nephropathy. Seventeen patients had a 40% or more reduction in urinary protein excretion ("responders"), and the decrease continued during long-term treatment. Meclofenamate therapy was discontinued after 2 months in eight "nonresponders" and in five other patients because of side effects (progressive increase in the level of serum creatinine in two, diarrhea in two, and pruritus in one). In responders, we recorded the following findings (mean ± SD): urinary protein excretion decreased from 13.0 ± 5.2 g/24 h to 7.2 ± 3.5 g/24 h in 2 to 4 weeks and continued to decrease to 4.1 ± 1.4 g/24 h at the time of the last follow-up study (median duration, 12 months; range, 6 to 36 months; P P P 2 versus 64.1 ± 25.5 ml/min per 1.7 m 2 ). Of the eight nonresponders, two had a subsequent decrease in renal function and four had deterioration to end-stage renal failure during the course of the study. Thus, meclofenamate may be beneficial in the treatment of severe nephrotic syndrome in some patients with membranous glomerulopathy or focal segmental glomerulosclerosis.
Model Predictive Control of Dual-Mode Operations Z-Source Inverter: Islanded and Grid-Connected

This paper presents model predictive control of dual-mode Z-source inverters (ZSIs) with capability to operate in islanded and grid-connected mode. The transition from islanded to grid-connected mode and vice versa can cause significant deviation in voltage and current due to mismatch in phase, frequency, and amplitude of voltages. The proposed controller offers seamless transition between the two modes of operations. The main predictive controller objectives are direct decoupled power control in grid-connected mode and load voltage regulation in islanded mode. The proposed direct decoupled active and reactive power control in grid-connected mode enables the dual-mode ZSI to behave as a power conditioning unit for ancillary services such as reactive power compensation. The proposed controller features simplicity, seamless transition between modes of operations, fast dynamic response, and small tracking error under steady-state condition of controller objectives. The operation of the proposed system is verified experimentally.
Oiling accelerates loss of salt marshes, southeastern Louisiana

The 2010 BP Deepwater Horizon (DWH) oil spill damaged thousands of km2 of intertidal marsh along shorelines that had been experiencing elevated rates of erosion for decades. Yet, the contribution of marsh oiling to landscape-scale degradation and subsequent land loss has been difficult to quantify. Here, we applied advanced remote sensing techniques to map changes in marsh land cover and open water before and after oiling. We segmented the marsh shorelines into non-oiled and oiled reaches and calculated the land loss rates for each 10% increase in oil cover (e.g. 0% to >70%), to determine if land loss rates for each reach oiling category were significantly different before and after oiling. Finally, we calculated background land-loss rates to separate natural and oil-related erosion and land loss. Oiling caused significant increases in land losses, particularly along reaches of heavy oiling (>20% oil cover). For reaches with ≥20% oiling, land loss rates increased abruptly during the 2010-2013 period, and the loss rates during this period are significantly different from both the pre-oiling (p < 0.0001) and 2013-2016 post-oiling periods (p < 0.0001). The pre-oiling and 2013-2016 post-oiling periods exhibit no significant differences in land loss rates across oiled and non-oiled reaches (p = 0.557). We conclude that oiling increased land loss by more than 50%, but that land loss rates returned to background levels within 3-6 years after oiling, suggesting that oiling results in a large but temporary increase in land loss rates along the shoreline.
Risk Management for Hedge Funds: Introduction and Overview

Although risk management has been a well-plowed field in financial modeling for more than two decades, traditional risk management tools such as mean–variance analysis, beta, and Value-at-Risk do not capture many of the risk exposures of hedge-fund investments. In this article, I review several unique aspects of risk management for hedge funds—survivorship bias, dynamic risk analytics, liquidity, and nonlinearities—and provide examples that illustrate their potential importance to hedge-fund managers and investors. I propose a research agenda for developing a new set of risk analytics specifically designed for hedge-fund investments, with the ultimate goal of creating risk transparency without compromising the proprietary nature of hedge-fund investment strategies.
Market Imperfections, Macroeconomic Conditions, and Capital Structure Dynamics: A Cross-Country Study

This article investigates how “systematic” adjustment costs proxied by market imperfections, and macroeconomic conditions affect capital structure dynamics in a cross-country setting. We document s...
What is the best planar cavity for maximizing coherent exciton-photon coupling

We compare alternative planar cavity structures for strong exciton-photon coupling with the conventional distributed Bragg reflector (DBR) and three unconventional types of cavity mirrors—air/GaAs DBR, Tamm-plasmon mirror, and sub-wavelength grating mirror. We design and optimize the planar cavities built with each type of mirror at one side or both sides for the maximum vacuum field strength. We discuss the trade-off between performance and fabrication difficulty for each cavity structure. We show that cavities with sub-wavelength grating mirrors allow simultaneously the strongest field and high cavity quality. The optimization principles and techniques developed in this work will guide the cavity design for research and applications of matter-light coupled semiconductors, especially new material systems that require greater flexibility in the choice of cavity materials and cavity fabrication procedures.
Solving the inverse problem for coarse-mode aerosol particle morphology with digital holography.

Coarse mode atmospheric aerosol particles are abundant in agricultural, desert, and urban environments. Accurate characterisation of these particles’ morphology is an important need in scientific and applied contexts, especially to advance our understanding for how such aerosols influence solar radiative forcing of the atmosphere. Elastic light scattering is a standard method to study aerosol particles in a contact-free manner, wherein measured scattering patterns are interpreted to infer particle morphology. Due in part to the absence of wave-phase information in these measurements, the inference is not unique, a difficulty generally known as the inverse problem. An alternative approach is digital holography where wave-phase information is encoded in the measurements. We show that digital holography and spatial filtering can solve the inverse problem for free-flowing aerosol particles in the sense that a measured scattering pattern can be uniquely associated with the particle size, shape, and orientation producing it.
Multitaper and multisegment spectral estimation of line-edge roughness

Line-edge roughness (LER) has important impacts on the quality of semiconductor device performance, and power spectrum estimates are useful tools in characterizing it. These estimates are often obtained by taking measurements of many lines and averaging a classical power spectrum estimate from each one. While this approach reduces the uncertainty of the estimates, there are disadvantages to the collection of many measurements. We propose techniques with widespread application in other fields that simultaneously reduce data requirements and the uncertainty of LER power spectrum estimates over current approaches at the price of computational complexity. Multitaper spectral analysis uses an orthogonal collection of data windowing functions or tapers to obtain a set of approximately statistically independent spectrum estimates. The Welch overlapped segment averaging is an earlier approach to reduce the uncertainty of power spectrum estimates. There are known techniques to evaluate the uncertainty of power spectrum estimates. We simulate random rough lines using the Thorsos method.
Counterthreat of attack to deter aggression

Abstract A crisis begins when a potential aggressor makes a threat of attack against a target state, creating a stalemate. The potential aggressor’s military technology improves over time, but its true military capability or intention is unknown. I show that the more sensitive the target state is to the danger of potential aggression, the greater the chance that the potential aggressor backs down and the lesser the risk of war. By committing to attacking sooner, the target state can increase security from aggression. My analysis provides a security rationale for counterthreatening to attack to prevent the realization of an aggressor attack.
Activation of planarian TRPA1 by reactive oxygen species reveals a conserved mechanism for animal nociception

All animals must detect noxious stimuli to initiate protective behavior, but the evolutionary origin of nociceptive systems is not well understood. Here we show that noxious heat and irritant chemicals elicit robust escape behaviors in the planarian Schmidtea mediterranea and that the conserved ion channel TRPA1 is required for these responses. TRPA1-mutant Drosophila flies are also defective in noxious-heat responses. We find that either planarian or human TRPA1 can restore noxious-heat avoidance to TRPA1-mutant Drosophila, although neither is directly activated by heat. Instead, our data suggest that TRPA1 activation is mediated by H2O2 and reactive oxygen species, early markers of tissue damage rapidly produced as a result of heat exposure. Together, our data reveal a core function for TRPA1 in noxious heat transduction, demonstrate its conservation from planarians to humans, and imply that animal nociceptive systems may share a common ancestry, tracing back to a progenitor that lived more than 500 million years ago. Animals must detect noxious stimuli to initiate protective behavior, but the evolutionary origin of nociceptive systems is poorly understood. The authors reveal a core function for TRPA1 in noxious heat transduction based on sensing H2O2 and ROS and demonstrate its conservation from planarians to humans.
Deposit-lending synergies and bank profitability

Banks accept deposits and often lend via commitments. It has been shown that there are synergies between transaction deposits and loan commitments; and that the volatility of bank stock returns declines when these two liquidity risks are taken together. We examine whether such deposit-lending synergies reflect on U.S. commercial bank profitability levels, and whether the synergies impact bank profitability levels differently around financial crises. Our results from panel regressions show that the deposit-lending synergies translate to increased profitability only for small publicly traded banks. However, pre-crisis deposit-lending synergies do not appear to lead to higher profitability during or after the crises.
An approximation algorithm for minimum-cost vertex-connectivity problems

We present an approximation algorithm for solving graph problems in which a low-cost set of edges must be selected that has certain vertex-connectivity properties. In the survivable network design problem, a valuerij for each pair of verticesi andj is given, and a minimum-cost set of edges such that there arerij vertex-disjoint paths between verticesi andj must be found. In the case for whichrijź{0, 1, 2} for alli, j, we can find a solution of cost no more than three times the optimal cost in polynomial time. In the case in whichrij=k for alli, j, we can find a solution of cost no more than 2H(k) times optimal, where $$\mathcal{H}(n) = 1 + \tfrac{1}{2} + \cdot \cdot \cdot + \tfrac{1}{n}$$ . No approximation algorithms were previously known for these problems. Our algorithms rely on a primal-dual approach which has recently led to approximation algorithms for many edge-connectivity problems.
Defect Tolerance: Fundamental Limits and Examples

This paper addresses the problem of adding redundancy to a collection of physical objects so that the overall system is more robust to failures. In contrast to its information counterpart, which can exploit parity to protect multiple information symbols from a single erasure, physical redundancy can only be realized through duplication and substitution of objects. We propose a bipartite graph model for designing defect-tolerant systems, in which the defective objects are replaced by the judiciously connected redundant objects. The fundamental limits of this model are characterized under various asymptotic settings and both asymptotic and finite-size systems that approach these limits are constructed. Among other results, we show that the simple modular redundancy is in general suboptimal. As we develop, this combinatorial problem of defect tolerant system design has a natural interpretation as one of graph coloring, and the analysis is significantly different from that traditionally used in information redundancy for error-control codes.
Physician Intervention to Positive Depression Screens Among Adolescents in Primary Care.

Abstract Purpose The objective of this study was to determine the effectiveness of computer-based screening and physician feedback to guide adolescent depression management within primary care. Methods We conducted a prospective cohort study within two clinics of the computer-based depression screening and physician feedback algorithm among youth aged 12–20 years between October 2014 and October 2015 in Marion County (Indianapolis), Indiana. Results Our sample included 2,038 youth (51% female; 60% black; mean age = 14.6 years [standard deviation = 2.1]). Over 20% of youth screened positive for depression on the Patient Health Questionnaire-2 and 303 youth (14.8%) screened positive on the Patient Health Questionnaire-9 (PHQ-9). The most common follow-up action by physicians was a referral to mental health services (34.2% mild, 46.8% moderate, and 72.2% severe range). Almost 11% of youth in the moderate range and 22.7% of youth in the severe range were already prescribed a selective serotonin reuptake inhibitor. When predicting mental health service referral, significant predictors in the multivariate analysis included clinic site (40.2% vs. 73.9%; p p p p Conclusions When a computer-based decision support system algorithm focused on adolescent depression was implemented in two primary care clinics, a majority of physicians utilized screening results to guide clinical care.
Emerging research institutions' technology transfer supply chain networks' sustainability: Budget resource planning tool development

Emerging Research Institutions (ERIs) can benefit from patent licensing revenues from the transfer of patented technologies into the commercial marketplace because these added revenues can help research institutions become more sustainable financially. However, many ERIs struggle to succeed in technology transfer. This study describes the development of a university technology transfer supply chain network sustainability tool that private and public ERIs can use to become more self-reliant financially. Historically black colleges and universities (HBCUs) are ERIs and are used as a case study. HBCUs lag behind their peer non-HBCUs because historically they have been under-served and were originally established largely as teaching and blue-collar trade schools. Some doctoral HBCUs desire to strengthen their research activities. Systems dynamics is the process of combining the theory, method, and philosophy necessary to analyze the behavior of a system in order to provide a common foundation that can be applied whenever it is desired to understand and influence how things change over time. Applying the systems dynamics approach, a budget resource planning tool was developed using a linear programming optimization technique. This study illustrates that classic industrial uses of linear programming optimization techniques can uniquely be used to optimize budget resource planning for sustainable HBCU supply chain networks and other emerging research institutions. This study contributes to the improved execution of technology transfer projects through better budget resource planning.
Applying Natural Language Processing Capabilities in Computerized Textual Analysis to Measure Organizational Culture

We build on and extend methodological developments in computerized textual analysis and apply it for developing and validating a measure for the widely used concept of organizational culture. Altho...
What is going on in underage drinking? Reflections on Finnish European school survey project on alcohol and other drugs data 1999-2015.

Introduction and aims As alcohol use has decreased among Finnish adolescents, we aim to assess: (i) time trends in alcohol use, heavy episodic drinking (HED) and potential explanatory variables among adolescents; (ii) the relationship between trends of explanatory variables and trends in alcohol use and HED; and (iii) which of the explanatory variables can account for the temporal change in alcohol use and HED. Design and methods The analyses are based on European School Survey Project on Alcohol and Other Drugs data collected from 15- to 16-year-old Finnish adolescents in 1999, 2003, 2007, 2011 and 2015. Results The decline in alcohol use and HED among underage youth in Finland is associated with at least three factors: (i) obtaining alcohol has become more difficult; (ii) parents know better than before where their children spend their Friday nights; and (iii) the risk attached to going out with friends on drinking has decreased. Discussion and conclusions Formal policy measures and adults' attitudes have probably affected the availability of alcohol for adolescents, and thus they partly explain the decline in youth drinking. This decline coincides with the introduction of new digital technologies, new forms of interaction within families and peer groups, and more conscientious teenagers. All these changes are not necessarily causes of the decline but are part of a similar broader change in adolescents' lives.
Die Another Day: Zeroing in on Targeted Dumping – Did the AB Hit the Mark in US–Washing Machines?

In US–Washing Machines, the WTO Appellate Body (AB) extended the prohibition of zeroing to the so-called exceptional (or W-T) methodology, where the dumping margin is established by comparing the weighted average normal value to export price of specific transactions. Given that the exceptional method was the only method under which the AB had not definitively rejected zeroing, this dispute may have hammered the last nail in the coffin of zeroing. Or, maybe not. The AB did not address a key issue, namely: What is the evidentiary standard that an investigating authority must meet in order to have legitimate recourse to W-T? In addition, the AB's suggested approach to aggregating dumping amounts across targeted and non-targeted groups may produce zeroing-like outcomes even if the authority does not resort to zeroing. It seems inevitable that future disputes will be required to address these issues, since history shows that at least some investigating authorities are gearing towards using this methodology ad nauseam. The AB has left zeroing to die another day.
Germline pharmacogenomics of DPYD*9A (c.85T>C) variant in patients with gastrointestinal malignancies treated with fluoropyrimidines.

598Background: The correlation between DPYD*9A (c.85T > C) genotype and dihydropyrimidine dehydrogenase (DPD) deficiency clinical phenotype is controversial. Reference laboratories either did not p...
Repeat Migration in the Age of the “Unauthorized Permanent Resident”: A Quantitative Assessment of Migration Intentions Postdeportation:

Drawing on postdeportation surveys (N = 1,109) with Mexican migrants, we examine the impact of immigration enforcement programs and various social factors on repeat migration intentions. Our multivariate analyses suggest immigrants with strong personal ties to the United States have higher relative odds of intending to cross the border again, even when controlling modes of removal from the United States. Our findings highlight the inevitable failure of immigration policy and enforcement programs when placed against the powerful pull of family and home. These findings shed greater insight on the complex nature of unauthorized migration in an era of increased securitization and deportation.
Typed closure conversion for the calculus of constructions

Dependently typed languages such as Coq are used to specify and verify the full functional correctness of source programs. Type-preserving compilation can be used to preserve these specifications and proofs of correctness through compilation into the generated target-language programs. Unfortunately, type-preserving compilation of dependent types is hard. In essence, the problem is that dependent type systems are designed around high-level compositional abstractions to decide type checking, but compilation interferes with the type-system rules for reasoning about run-time terms. We develop a type-preserving closure-conversion translation from the Calculus of Constructions (CC) with strong dependent pairs (Σ types)—a subset of the core language of Coq—to a type-safe, dependently typed compiler intermediate language named CC-CC. The central challenge in this work is how to translate the source type-system rules for reasoning about functions into target type-system rules for reasoning about closures. To justify these rules, we prove soundness of CC-CC by giving a model in CC. In addition to type preservation, we prove correctness of separate compilation.
Hypoxia Signaling Pathway in Stem Cell Regulation: Good and Evil

This review summarizes the role of hypoxia and hypoxia-inducible factors (HIFs) in the regulation of stem cell biology, specifically focusing on maintenance, differentiation, and stress responses in the context of several stem cell systems. Stem cells for different lineages/tissues reside in distinct niches, and are exposed to diverse oxygen concentrations. Recent studies have revealed the importance of the hypoxia signaling pathway for stem cell functions. Hypoxia and HIFs contribute to maintenance of embryonic stem cells, generation of induced pluripotent stem cells, functionality of hematopoietic stem cells, and survival of leukemia stem cells. Harvest and collection of mouse bone marrow and human cord blood cells in ambient air results in fewer hematopoietic stem cells recovered due to the phenomenon of Extra PHysiologic Oxygen Shock/Stress (EPHOSS). Oxygen is an important factor in the stem cell microenvironment. Hypoxia signaling and HIFs play important roles in modeling cellular metabolism in both stem cells and niches to regulate stem cell biology, and represent an additional dimension that allows stem cells to maintain an undifferentiated status and multilineage differentiation potential.
Designing Optimal Binary Rating Systems

Modern online platforms rely on effective rating systems to learn about items. We consider the optimal design of rating systems that collect binary feedback after transactions. We make three contributions. First, we formalize the performance of a rating system as the speed with which it recovers the true underlying ranking on items (in a large deviations sense), accounting for both items' underlying match rates and the platform's preferences. Second, we provide an efficient algorithm to compute the binary feedback system that yields the highest such performance. Finally, we show how this theoretical perspective can be used to empirically design an implementable, approximately optimal rating system, and validate our approach using real-world experimental data collected on Amazon Mechanical Turk.
Changing practice patterns for cytotechnologists: a comparative analysis of data from the 2009 and 2015 ASCP BOC Practice Analysis Surveys.

Background The American Society for Clinical Pathology (ASCP) Board of Certification (BOC) surveys US certified cytotechnologists (CTs) at approximately 5-year intervals to gain information about current practice patterns. Although the purpose of this survey is to inform valid content development for the BOC CT examination, comparative longitudinal analysis of the survey data provides information about changes in cytotechnology practice. Materials and Methods BOC Practice Analysis Survey data for 2009 and 2015 were examined, comparing survey demographics and performance of laboratory tasks. The 2015 survey added tasks not previously surveyed and considered them emerging when performed by a majority of respondents. Results Two hundred thirty-five participants completed the survey in 2015 and 151 in 2009. Respondents reported an overall decrease in performing conventional Papanicolaou tests (−25.3%). Respondents reported increases in morphologic tasks such cytology–histology correlation (17.5%), cell-block interpretation (17.5%), and preliminary interpretation of histochemical stains (e.g., mucin and Grocott's methenamine silver stain) (16.7%), as well as quality assurance tasks. Majority-performed, newly surveyed tasks included touch prep preparation (57.8%) and interpretation (59.2%) and ancillary test triage (59.6%). Molecular tasks such as tumor identification (6.8%) and preparation of cytology specimens for oncology molecular testing (9.4%) did not meet majority-reporting thresholds. Conclusions Although performance of the Papanicolaou test is declining, CTs report increases in additional morphologic as well as other laboratory tasks. Emerging tasks (2015) focus on FNA specimens. Knowledge of cytology practice patterns will help guide development of education and training resources toward maintaining an appropriately trained workforce.
Acoustically targeted chemogenetics for the non-invasive control of neural circuits

Neurological and psychiatric disorders are often characterized by dysfunctional neural circuits in specific regions of the brain. Existing treatment strategies, including the use of drugs and implantable brain stimulators, aim to modulate the activity of these circuits. However, they are not cell-type-specific, lack spatial targeting or require invasive procedures. Here, we report a cell-type-specific and non-invasive approach based on acoustically targeted chemogenetics that enables the modulation of neural circuits with spatiotemporal specificity. The approach uses ultrasound waves to transiently open the blood–brain barrier and transduce neurons at specific locations in the brain with virally encoded engineered G-protein-coupled receptors. The engineered neurons subsequently respond to systemically administered designer compounds to activate or inhibit their activity. In a mouse model of memory formation, the approach can modify and subsequently activate or inhibit excitatory neurons within the hippocampus, with selective control over individual brain regions. This technology overcomes some of the key limitations associated with conventional brain therapies.
A Domain Decomposition Approach for Local Mesh Refinement in Space and Time

We present an adaptive space-time mesh refinement approach based a domain decomposition approach (Singh and Wheeler, 2018) that allows different time-step sizes and mesh refinements in different subdomains. Our numerical experiments indicate that non-linear solvers fail to converge, to the desired tolerance, due to large non-linear residuals in a smaller subdomain. We exploit this feature to identify subdomains where smaller time-step sizes are necessary while using large time-step sizes in the rest of the reservoir domain. The three key components of our approach are: (1) a space-time, enhanced velocity, domain decomposition approach that allows different mesh refinements and time-step sizes in different subdomains while preserving local mass conservation, (2) a residual based error estimator to identify or mark regions (or subdomains) that pose non-linear convergence issues, and (3) a fully coupled monolithic solver is also presented that solves the coarse and fine subdomain problems, both in space and time, simultaneously. This solution scheme is fully implicit and is therefore unconditionally stable. The proposed space-time domain decomposition approach, with smaller time-step sizes in a subdomain and large time-step sizes everywhere else, circumvents the non-linear convergence issue without adding computational costs. Additionally, a space-time monolithic solver renders a massively parallel, time concurrent framework for solving flow and transport problems in subsurface porous media. Since the proposed approach is similar to the widely used finite difference scheme, it can be easily integrated in any existing legacy reservoir simulator.
The Next-Generation Very Large Array: a technical overview

The next-generation Very Large Array (ngVLA) is an astronomical observatory planned to operate at centimeter wavelengths (25 to 0.26 centimeters, corresponding to a frequency range extending from 1.2 GHz to 116 GHz). The observatory will be a synthesis radio telescope constituted of approximately 214 reflector antennas each of 18 meters diameter, operating in a phased or interferometric mode. We provide an overview of the current system design of the ngVLA. The concepts for major system elements such as the antenna, receiving electronics, and central signal processing are presented. We also describe the major development activities that are presently underway to advance the design.
Multiple prebiotic metals mediate translation

Today, Mg2+ is an essential cofactor with diverse structural and functional roles in life’s oldest macromolecular machine, the translation system. We tested whether ancient Earth conditions (low O2, high Fe2+, and high Mn2+) can revert the ribosome to a functional ancestral state. First, SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) was used to compare the effect of Mg2+, Fe2+, and Mn2+ on the tertiary structure of rRNA. Then, we used in vitro translation reactions to test whether Fe2+ or Mn2+ could mediate protein production, and quantified ribosomal metal content. We found that (i) Mg2+, Fe2+, and Mn2+ had strikingly similar effects on rRNA folding; (ii) Fe2+ and Mn2+ can replace Mg2+ as the dominant divalent cation during translation of mRNA to functional protein; and (iii) Fe and Mn associate extensively with the ribosome. Given that the translation system originated and matured when Fe2+ and Mn2+ were abundant, these findings suggest that Fe2+ and Mn2+ played a role in early ribosomal evolution.
ETF liquidation determinants

Abstract The exchange-traded fund (ETF) market has dramatically increased in size and influence. With this growth, there has been an increase in the number of liquidations. We find that the decision to liquidate an ETF is primarily based on ETF characteristics; however, we observe additional considerations related to fund family and investment objective characteristics. Failures are more likely to occur when an ETF is small and when it is launched by a struggling family or into a struggling investment objective. We find fund, family, and market characteristics at the time of creation greatly impact an ETF’s likelihood of survival. Furthermore, we observe few, but significant, differences between the decision to close an ETF and the decision to close an actively managed mutual fund. Whereas ETFs show relatively greater dependence on the well-being of their investment objective, mutual funds show a greater dependence on their fund specific performance.
Amplitude Quantization for Type-2 Codebook Based CSI Feedback in New Radio System

In 3GPP new radio system, two types of codebook, namely Type-l and Type-2 codebook, have been standardized for the channel state information (CSI) feedback in the support of advanced MIMO operation. Both types of codebook are constructed from 2-D DFT based grid of beams, and enable the CSI feedback of beam selection as well as PSK based co-phase combining between two polarizations. Moreover, Type-2 codebook based CSI feedback reports the wideband and subband amplitude information of the selected beams. As a result, it is envisioned that more accurate CSI shall be obtained from the Type-2 codebook based CSI feedback so that better precoded MIMO transmission can be employed by the network. To reduce the CSI feedback signaling, 1 bit based subband amplitude with only two quantization levels is supported in combination to 3 bits based wideband amplitude feedback. Typically, wideband amplitude shall be calculated as the linear average amplitude of the beam over all subbands. However, due to the coarse subband amplitude quantization, it has been observed in case of joint wideband and subband amplitude feedback, the average based wideband amplitude can lead to a large amplitude quantization errors. In this paper, we study two methods for joint wideband and subband amplitude calculations. Specifically, both optimal and sub-optimal methods are proposed. The optimal method can achieve the minimum amplitude quantization errors at the cost of a relatively large computation complexity. And by virtue of a derived scaling factor, the sub-optimal method exhibits clearly smaller quantization error than the conventional linear average based method especially for the channel with large frequency selectivity.
Multivariate information transmission

A multivariate analysis based on transmitted information is presented. It is shown that sample transmitted information provides a simple method for measuring and testing association in multi-dimensional contingency tables. Relations with analysis of variance are pointed out, and statistical tests are described.
Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction

There have been several recent attempts to improve the accuracy of grammar induction systems by bounding the recursive complexity of the induction model. Modern depth-bounded grammar inducers have been shown to be more accurate than early unbounded PCFG inducers, but this technique has never been compared against unbounded induction within the same system, in part because most previous depth-bounding models are built around sequence models, the complexity of which grows exponentially with the maximum allowed depth. The present work instead applies depth bounds within a chart-based Bayesian PCFG inducer, where bounding can be switched on and off, and then samples trees with or without bounding. Results show that depth-bounding is indeed significantly effective in limiting the search space of the inducer and thereby increasing accuracy of resulting parsing model, independent of the contribution of modern Bayesian induction techniques. Moreover, parsing results on English, Chinese and German show that this bounded model is able to produce parse trees more accurately than or competitively with state-of-the-art constituency grammar induction models.
Interconnect and substrate modeling and analysis: an overview

Accurate models for on-chip metal interconnect, silicon substrate, and packaging have become necessary for accurate simulation of high-performance ULSI circuits and high-speed RF designs. An overview of the hierarchy of techniques used to model and simulate these structures is given. While not an exhaustive summary, the purpose of the paper is to give the designer fundamental and practical understanding of principles used in modeling and analysis. The range of techniques from three-dimensional (3-D) modeling to quasi-3-D to transmission lines are analyzed, and their importance and impact are described. A modeling strategy that can include various kinds of modeling techniques and nonlinear devices in one simulation is also described.