cssi/SciSciGPT-SciSciNet huggingface dataset:
Inappropriate Practices in Fitness Testing and Reporting: Alternative Strategies

Fitness education is becoming an integrated component for many physical education programs. As such, many physical educators conduct health-related fitness tests on a regular basis. Some states even mandate certain types of physical fitness tests to be administered and reported annually or by semester. Yet, inappropriate practices have been observed in the field and in the laboratory when researchers examine teacher-reported fitness data. These practices include (1) doing only the minimum to meet the test criteria, (2) not testing students with disabilities through exemptions, (3) testing a few students on display while having others as audience, (4) compromising the tests by being too flexible or helpful, (5) testing without teaching, and (6) fabricating test results. When these practices show in the gymnasium or are found in reported fitness data, they invalidate testing efforts and objectives, and damage the image of all physical educators. This article describes these inappropriate practices and discu...
Unsupervised Learning on an Approximate Corpus

Unsupervised learning techniques can take advantage of large amounts of unannotated text, but the largest text corpus (the Web) is not easy to use in its full form. Instead, we have statistics about this corpus in the form of n-gram counts (Brants and Franz, 2006). While n-gram counts do not directly provide sentences, a distribution over sentences can be estimated from them in the same way that n-gram language models are estimated. We treat this distribution over sentences as an approximate corpus and show how unsupervised learning can be performed on such a corpus using variational inference. We compare hidden Markov model (HMM) training on exact and approximate corpora of various sizes, measuring speed and accuracy on unsupervised part-of-speech tagging.
Bayesian methods for finding sparse representations

Finding the sparsest or minimum e0-norm representation of a signal given a (possibly) overcomplete dictionary of basis vectors is an important problem in many application domains, including neuroelectromagnetic source localization, compressed sensing, sparse component analysis, feature selection, image restoration/compression, and neural coding. Unfortunately, the required optimization is typically NP-hard, and so approximate procedures that succeed with high probability are sought. Nearly all current approaches to this problem, including orthogonal matching pursuit (OMP), basis pursuit (BP) (or the LASSO), and minimum e p quasi-norm methods, can be viewed in Bayesian terms as performing standard MAP estimation using a fixed, sparsity-inducing prior. In contrast, we advocate empirical Bayesian approaches such as sparse Bayesian learning (SBL), which use a parameterized prior to encourage sparsity through a process called evidence maximization. We prove several results about the associated SBL cost function that elucidate its general behavior and provide solid theoretical justification for using it to find maximally sparse representations. Specifically, we show that the global SBL minimum is always achieved at the maximally sparse solution, unlike the BP cost function, while often possessing a more limited constellation of local minima than comparable MAP methods which share this property. We also derive conditions, dependent on the distribution of the nonzero model weights embedded in the optimal representation, such that SBL has no local minima. Finally, we demonstrate how a generalized form of SBL, out of a large class of latent-variable models, uniquely satisfies two minimal performance criteria directly linked to sparsity. These results lead to a deeper understanding of the connections between various Bayesian-inspired strategies and suggest new sparse learning algorithms. Several extensions of SBL are also considered for handling sparse representations that arise in spatio-temporal settings and in the context of covariance component estimation. Here we assume that a small set of common features underly the observed data collected over multiple instances. The theoretical properties of these SBL-based cost functions are examined and evaluated in the context of existing methods. The resulting algorithms display excellent performance on extremely large, ill-posed, and ill-conditioned problems in neuroimaging, suggesting a strong potential for impacting this field and others.
Variation in heritability of immune function in the tree swallow

Heritability is an important component of the ability of a trait to respond to natural selection; variation in heritability can lead to differences in how a trait responds to selection pressures. Here we test whether an important physiological trait, immune function, varies by comparing heritability estimates through cross-fostering brood manipulation at three wide-spread sites in the tree swallow (Tachycineta bicolor): Alaska, New York and Tennessee. In two of three sites, there was no additive genetic component to nestling immune response to the mitogen phytohaemagglutinin, while immune response had a heritable component in Tennessee. Bootstrapping revealed significant differences in estimated heritability. This conclusion was supported by mother–offspring regressions; in Tennessee breeding females mounting strong immune responses tended to have offspring with strong immune responses, while in New York and Alaska, there was no relationship between the immune responses of mothers and offspring. These results suggest that studies investigating the roles of common origin and rearing environment should consider yearly or spatial variation within a species.
THE DESIGN OF POTENTIAL RADIOPHARMACEUTICALS BASED ON STRUCTURE-ACTIVITY RELATIONSHIPS

Abstract The past 20 years have seen the codification of several sets of comprehensive structure-partitioning mechanisms. Radiopharmaceutical scientists nave sought and continued to seek rational guidelines to predict the in vivo localization of newly developed radioactive diagnostic agents. Several of these codification systems are discussed with illustrations of their application to new radiopharmaceutical design. The authors show how design principles which have long been applied in the development of therapeutic agents (e.g., Hansch correlations, lipohilicity, chirality, enzyme substrate mimicry, etc.) are proving useful in preparation of a new generation of radiodiagnostics. The special advantages and difficulties in the application of short-lived positron emitters as well as problems in animal evaluation of new radiopharmaceutical candidates are also discussed.
Representation Schemes and Conceptual Graphs

Metaphor is a complex subject and, like many difficult AI problems, can only be modelled by building on and extending already existing work in the field. For example, before even beginning to handle metaphoric input, a program would have to be able to parse a sentence syntactically. Yet, the implementation of a parser, which is a difficult and time-consuming task, is not really relevant to the task of handling metaphors. And parsing is just one of a myriad of capabilities needed before metaphor can even be considered. As we saw in the last chapter, representing knowledge involves a great many issues and requires a well developed ‘language’ which can capture relevant distinctions. For these reasons, my approach to metaphor and to knowledge representation is within the framework of, and as an extension to, an existing theory for processing natural language, namely, that of conceptual graphs.
Constrained-Action POMDPs for Multi-Agent Intelligent Knowledge Distribution

This paper addresses a fundamental question of multi-agent knowledge distribution: what information should be sent to whom and when, with the limited resources available to each agent? Intelligent Knowledge Distribution is a framework that answers these questions. Communication requirements for multi-agent systems can be rather high when an accurate picture of the environment and the state of other agents must be maintained. To reduce the impact of multi-agent coordination on systems, including communications, this paper introduces the concept of action-based constraints on partially observable Markov decision processes, rewards based upon the value of information driven by Kullback-Leibler Divergence, and probabilistic constraint satisfaction through discrete optimization and Markov chain Monte Carlo analysis. Intelligent Knowledge Distribution is driven by determining the information content an agent believes another agent will obtain by receiving certain information, along with the importance or relevance of that information to the system objective. To perform constraint analysis on an infinite-horizon policy, policies are represented as a Finite State Controller allowing Markov chain Monte Carlo analysis to determine a probabilistic level of guarantee that the constraints will be satisfied. The analysis of performance for an example mission presented in this paper shows the constrained controllers, during the highest constraint seen in simulations, can be constructed to meet minimal constraint guarantees (80%) while impacting the optimal value less than 50%, where the unconstrained optimal controller only satisfied the constraint 10% of the time.
Sarcopenia is a reliable predictor of outcomes following radical cystectomy for bladder cancer

Radical cystectomy (RC) with pelvic lymph node dissection, preceded by cisplatin-based neoadjuvant chemotherapy in appropriate patients, remains the gold-standard in the treatment of muscle invasive bladder cancer (MIBC) (1,2). RC is a complex operation performed in an elderly (and sometimes unhealthy) patient population, with significant complication rates (as high as 60%) and perioperative mortality rates (9%) reported at 90-days (3,4).
Toughness, Tenacity and Maximum Initial Strength of Rubber Modified Asphalt Binders

The toughness and tenacity test method, which was developed in the 1980s, is popular for evaluating a polymer-modified binder. Several states like Nevada require performing this test to evaluate non-modified binder samples, as well as other types of modified binders. In this regard, a toughness and tenacity test was performed on rubber-modified samples produced from virgin binder PG58-28, PG64-16 and AC-20. In order to take the rubber size, type and content into account, two rubber sizes, mesh #20 and #40, two rubber types, ambient and cryogenic, and three rubber contents, 10%, 15%, and 20% were produced and tested. The results then were compared with polymer-modified and terminally blended rubber-modified samples. The results show improvement in the amount of initial maximum strength, and a decline in the magnitude of elongation, toughness and tenacity for the rubber-modified binder, compared to other types of binders.
Effetto immunosoppressivo di prodotti batterici extracellulari.Effetto sulla malattia da adiuvante

Nel ratto, la risposta infiammatoria locale all’iniezione di adiuvante e la successiva comparsa della malattia da adiuvante sono state notevolmente soppresse mediante somministrazione di prodotti extracellulati di alcune specie batteriche. Ptodotti dellaS. typhimurium hanno causato profonda leucopenia, inibizione della risposta anticorpale circolante e soppressione della malattia da adiuvante. Prodotti delloStrep. pyogenes non hanno causato leucopenia ne inibizione della produzione di anticorpi circolanti, inducendo tuttavia una marcata inibizione della malattia da adiuvante. Prodotti delloStrep. pneumoniae hanno mostrato un effetto simile ma meno marcato, mentre prodotti delloStaph. aureus sono risultati del tutto inefficaci.
Cortical Vein Opacification for Risk Stratification in Anterior Circulation Endovascular Thrombectomy.

Abstract Introduction: There is continued interest in identifying factors that predict a favorable outcome after endovascular thrombectomy (EVT) for anterior circulation large vessel occlusion (ACLVO). We compared the predictive values of 2 different scoring systems for evaluating venous collateral circulation. Methods: A retrospective review of patients who underwent EVT for ACLVO at a single institution was performed. Those who underwent preprocedural computed tomography angiography (CTA) were selected. The Cortical Vein Opacification Score (COVES) and Prognostic Evaluation based on Cortical vein score difference In Stroke (PRECISE) score were calculated from each patient's CTA. Our primary outcome of interest was the Modified Rankin Scale (mRS) score at 90 days. Results: A total of 103 patients were included in the study (average age = 68.3 years, median National Institutes of Health Stroke Scale = 15). The mean time to reperfusion was 6.4 hours and Thrombolysis in Cerebral Infarction 2B or 3 reperfusion was achieved in 77.7% of cases. An unfavorable COVES score was significantly associated with an unfavorable (mRS 3-6) outcome (adjusted odds ratio [aOR]: 3.06; 95% confidence interval [CI] 1.15-8.13, P = .025), while an unfavorable PRECISE score was not (aOR: 1.02; 95% CI .37-2.80, P = .966). Based on the Receiver Operating Characteristic analysis, the COVES score had a sensitivity of 68.1%, specificity of 71.4%, and area under the curve (AUC) of .77. The PRECISE score had a sensitivity of 68.9%, specificity of 70.7%, and the AUC of .73. Conclusions: The COVES score, but not the PRECISE score, is associated with functional outcomes at 90 days after EVT for ACLVO.
Two New Alkylated Piperidine Alkaloids from Western Honey Mesquite: Prosopis glandulosa Torr. var. torreyana:

Prosopis glandulosa Torr. var. torreyana (L. Benson) M. C. Johnston root bark, collected in Texas, yielded two new alkylated piperidine alkaloids, namely 3-isocassine (1) and N-methyl-3-isocassine ...
Sexism, perceived discrimination, and system justification in the 2016 U.S. presidential election context:

The 2016 U.S. presidential election provided a pertinent context for investigating novel influences on system-related beliefs. We examined Trump and Clinton supporters’ sexist attitudes toward wome...
Accurate and efficient amino acid analysis for protein quantification using hydrophilic interaction chromatography coupled tandem mass spectrometry

Methods used to quantify protein from biological samples are often inaccurate with significant variability that requires care to minimize. The errors result from losses during protein preparation and purification and false detection of interfering compounds or elements. Amino acid analysis (AAA) involves a series of chromatographic techniques that can be used to measure protein levels, avoiding some difficulties and providing specific compositional information. However, unstable derivatives, that are toxic and can be costly, incomplete reactions, inadequate chromatographic separations, and the lack of a single hydrolysis method with sufficient recovery of all amino acids hinder precise protein quantitation using AAA. In this study, a hydrophilic interaction chromatography based method was used to separate all proteinogenic amino acids, including isobaric compounds leucine and isoleucine, prior to detection by multiple reaction monitoring with LC–MS/MS. Through inclusion of commercially available isotopically labeled (13C, 15N) amino acids as internal standards we adapted an isotopic dilution strategy for amino acid-based quantification of proteins. Three hydrolysis methods were tested with ubiquitin, bovine serum albumin, (BSA), and a soy protein biological reference material (SRM 3234; NIST) resulting in protein estimates that were 86–103%, 82–94%, and 90–99% accurate for the three protein samples respectively. The methane sulfonic acid hydrolysis approach provided the best recovery of labile amino acids including: cysteine, methionine and tryptophan that are challenging to accurately quantify. Accurate determination of protein quantity and amino acid composition in heterogeneous biological samples is non-trivial. Recent advances in chromatographic phases and LC–MS/MS based methods, along with the availability of isotopic standards can minimize difficulties in analysis and improve protein quantitation. A robust method is described for high-throughput protein quantification and amino acid compositional analysis. Since accurate measurement of protein quality and quantity are a requirement for many biological studies that relate to crop improvement or more generally, our understanding of metabolism in living systems, we envision this method will have broad applicability.
Don't throw out the sympatric speciation with the crater lake water: fine-scale investigation of introgression provides equivocal support for causal role of secondary gene flow in one of the clearest examples of sympatric speciation.

Author(s): Richards, Emilie; Poelstra, Jelmer; Martin, Christopher | Abstract: Genomic data has revealed complex histories of colonization and repeated gene flow previously unrecognized in some of the most celebrated examples of sympatric speciation and radiation. However, much of the evidence for secondary gene flow into these radiations comes from summary statistics calculated from sparse genomic sampling without knowledge of which specific genomic regions introgressed. This tells us little about how gene flow potentially influenced sympatric diversification. Here, we investigated whole genomes of Barombi Mbo crater lake cichlids for fine-scale patterns of introgression with neighboring riverine cichlid populations. We found evidence of secondary gene flow into the radiation scattered across l0.24% of the genome; however, from our analyses, it is not clear if the functional diversity in these regions contributed to the ecological, sexual, and morphological diversity found in the lake. Unlike similar studies, we found no obvious candidate genes for adaptive introgression and we cannot rule out that secondary gene flow was predominantly neutral with respect to the diversification process. We also found evidence for differential assortment of ancestral polymorphisms found in riverine populations between sympatric sister species, suggesting the presence of an ancestral hybrid swarm. Although the history of gene flow and colonization is more complicated than previously assumed, the lack of compelling evidence for secondary gene flows role in species diversification suggests that we should not yet rule out one of the most celebrated examples of sympatric speciation in nature without a more thorough investigation of the timing and functional role of each introgressed region.
Chinese Mathematics Revision in Accordance with the Teachings of Mao Tse-Tung.

FROM 1962 until the present, the Great Cultural Revolution has been transform ing the thoughts and lives of the citizens of the People's Republic of China. Con fucian wisdom has been replaced by the philosophy of Chairman Mao. Reports reaching the West indicate how diligent study of the "Little Red Book" has as sisted its readers in "increasing the speed of rotation of my cotton spinning machine from 9,000 r.p.m. to 13,000 r.p.m." or "be coming world table tennis champion" or even "curing the children at our school of short-sightedness."1 As Confucian teach ings formerly did, so now the doctrines of Maoism form the foundations of the Chinese educational system. The most vocif?rant attacks of the Cultural Revolu tion have been directed at education, with the result that every subject taught, even mathematics, is considered in the frame work of Mao's teachings. Mao Tse-tung, in May of 1966, issued a directive specifically aimed at educa tion. Its points included the following: 1. The period of schooling should be shortened. 2. Education should be "revolutionized" by eliminating all bourgeois influence. 3. Greater emphasis should be placed on practical work.2
Underwater backscatter networking

We present Piezo-Acoustic Backscatter (PAB), the first technology that enables backscatter networking in underwater environments. PAB relies on the piezoelectric effect to enable underwater communication and sensing at near-zero power. Its architecture is inspired by radio backscatter which works well in air but cannot work well underwater due to the exponential attenuation of radio signals in water. PAB nodes harvest energy from underwater acoustic signals using piezoelectric interfaces and communicate by modulating the piezoelectric impedance. Our design introduces innovations that enable concurrent multiple access through circuit-based frequency tuning of backscatter modulation and a MAC that exploits the properties of PAB nodes to deliver higher network throughput and decode network collisions. We built a prototype of our design using custom-designed, mechanically fabricated transducers and an end-to-end battery-free hardware implementation. We tested our nodes in large experimental water tanks at the MIT Sea Grant. Our results demonstrate single-link throughputs up to 3 kbps and power-up ranges up to 10 m. Finally, we show how our design can be used to measure acidity, temperature, and pressure. Looking ahead, the system can be used in ocean exploration, marine life sensing, and underwater climate change monitoring.
Optimal Standards of Proof in Patent Litigation: Infringement and Non-Obviousness

We build a model of innovation and patent adjudication under two forms of uncertainty; uncertainty regarding whether the original invention merits protection (non-obviousness), and uncertainty as to whether a particular competitor's product should be barred (infringement). We find that when it is practical to increase the rewards from innovation by extending patent length, the standards of proof for non-obviousness should be high. The intuition for this is that patent length should be set so that the increase in innovation from extending patent length is balanced by the increase in deadweight loss from extending monopoly pricing. In this situation, the ex-ante cost of failing to protect a good patent is minimal, but there is substantial deadweight loss from protecting a bad patent. In contrast, if non-infringing competing inventions substantially decrease the original inventor's profits, it might be desirable to have a very low standard of proof for infringement, since the deadweight loss from an incorrect finding of infringement is mostly balanced out by the increased ex-ante incentive to invent.
Thermal behavior of a structure characterized through three-dimensional temperature signatures for a temperature driven method of structural health monitoring

Structural Health Monitoring (SHM) seeks to evaluate the condition of a structure by instrumenting the structure with sensors and then using a combination of structural and data analysis. One unifying factor across all structures is the effect of temperature changes on the behavior of the structure. Temperature Driven - Structural Health Monitoring (TD-SHM) considers temperature as the driving force in structural behavior, and consequently the main input in SHM. Temperature as an input is related to strain and displacement as output to form three-dimensional temperature signatures for the structures. These signatures are descriptive of the thermal behavior, as well as sensitive to changes in structural condition. The two main benefits of TDSHM are the applicability to any structure that undergoes daily or seasonal temperature changes, and the possibility to measure temperature as an input for a complete input-output model. This work examines one type of three-dimensional signature: the relationship between changes in temperature with changes in strain and rotation or tilt on a beam-like concrete structure. The three-dimensional figure is fit with a surface to quantify the behavior, and changes in either the goodness of fit or in the fit itself are indicative of changes in structural behavior. These methods are validated using data from a real structure; Streicker Bridge on campus at Princeton University.
Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans

Abstract Coronavirus disease 2019 (COVID-19) has infected more than 1.3 million individuals all over the world and caused more than 106,000 deaths. One major hurdle in controlling the spreading of this disease is the inefficiency and shortage of medical tests. There have been increasing efforts on developing deep learning methods to diagnose COVID-19 based on CT scans. However, these works are difficult to reproduce and adopt since the CT data used in their studies are not publicly available. Besides, these works require a large number of CTs to train accurate diagnosis models, which are difficult to obtain. In this paper, we aim to address these two problems. We build a publicly-available dataset containing hundreds of CT scans positive for COVID-19 and develop sample-efficient deep learning methods that can achieve high diagnosis accuracy of COVID-19 from CT scans even when the number of training CT images are limited. Specifically, we propose a Self-Trans approach, which synergistically integrates contrastive self-supervised learning with transfer learning to learn powerful and unbiased feature representations for reducing the risk of overfitting. Extensive experiments demonstrate the superior performance of our proposed Self-Trans approach compared with several state-of-the-art baselines. Our approach achieves an F1 of 0.85 and an AUC of 0.94 in diagnosing COVID-19 from CT scans, even though the number of training CTs is just a few hundred.
Genetics of progression from MDS to secondary leukemia

Our understanding of the genetics of acute myeloid leukemia (AML) development from myelodysplastic syndrome (MDS) has advanced significantly as a result of next-generation sequencing technology. Although differences in cell biology and maturation exist between MDS and AML secondary to MDS, these 2 diseases are genetically related. MDS and secondary AML cells harbor mutations in many of the same genes and functional categories, including chromatin modification, DNA methylation, RNA splicing, cohesin complex, transcription factors, cell signaling, and DNA damage, confirming that they are a disease continuum. Differences in the frequency of mutated genes in MDS and secondary AML indicate that the order of mutation acquisition is not random during progression. In almost every case, disease progression is associated with clonal evolution, typically defined by the expansion or emergence of a subclone with a unique set of mutations. Monitoring tumor burden and clonal evolution using sequencing provides advantages over using the blast count, which underestimates tumor burden, and could allow for early detection of disease progression prior to clinical deterioration. In this review, we outline advances in the study of MDS to secondary AML progression, with a focus on the genetics of progression, and discuss the advantages of incorporating molecular genetic data in the diagnosis, classification, and monitoring of MDS to secondary AML progression. Because sequencing is becoming routine in the clinic, ongoing research is needed to define the optimal assay to use in different clinical situations and how the data can be used to improve outcomes for patients with MDS and secondary AML.
Inactivation of fission yeast Erh1 de-represses pho1 expression: evidence that Erh1 is a negative regulator of prt lncRNA termination

Fission yeast Erh1 exists in a complex with RNA-binding protein Mmi1. Deletion of erh1 up-regulates the phosphate homeostasis gene pho1, which is normally repressed by transcription in cis of a 5' flanking prt lncRNA. Here we present evidence that de-repression of pho1 by erh1Δ is achieved through precocious 3'-processing/termination of prt lncRNA synthesis, to wit: (i) erh1Δ does not affect the activity of the prt or pho1 promoters per se; (ii) de-repression by erh1Δ depends on CPF (cleavage and polyadenylation factor) subunits Ctf1, Dis2, Ssu72, Swd22, and Ppn1 and on termination factor Rhn1; (iii) de-repression requires synthesis by the Asp1 IPP kinase of inositol 1-pyrophosphates (1-IPPs); (iv) de-repression is effaced by mutating Thr4 of the RNA polymerase II CTD to alanine; and (v) erh1Δ exerts an additive effect on pho1 de-repression in combination with mutating CTD Ser7 to alanine and with deletion of the IPP pyrophosphatase Aps1. These findings point to Erh1 as an antagonist of lncRNA termination in the prt-pho1 axis. In contrast, in mmi1Δ cells there is a reduction in pho1 mRNA and increase in the formation of a prt-pho1 read-through transcript, consistent with Mmi1 being an agonist of prt termination. We envision that Erh1 acts as a brake on Mmi1's ability to promote CPF-dependent termination during prt lncRNA synthesis. Consistent with this idea, erh1Δ de-repression of pho1 was eliminated by mutating the Mmi1-binding sites in the prt lncRNA.
Spatial Parrondo games and an interacting particle system

Parrondo games with spatial dependence were introduced by Toral (2001) and have been studied extensively. In Toral's model $N$ players are arranged in a circle. The players play either game $A$ or game $B$. In game $A$, a randomly chosen player wins or loses one unit according to the toss of a fair coin. In game $B$, which depends on parameters $p_0,p_1,p_2\in[0,1]$, a randomly chosen player, player $x$ say, wins or loses one unit according to the toss of a $p_m$-coin, where $m\in\{0,1,2\}$ is the number of nearest neighbors of player $x$ who won their most recent game. In this paper, we replace game $A$ by a spatially dependent game, which we call game $A'$, introduced by Xie et al.~(2011). In game $A'$, two nearest neighbors are chosen at random, and one pays one unit to the other based on the toss of a fair coin. Game $A'$ is fair, so we say that the Parrondo effect occurs if game $B$ is losing or fair and the game $C'$, determined by a random or periodic sequence of games $A'$ and $B$, is winning. Here we give sufficient conditions for convergence as $N\to\infty$ of the mean profit per game played from game $C'$. This requires ergodicity of an associated interacting particle system (not necessarily a spin system), for which sufficient conditions are found using the basic inequality.
Student Attitudes Toward Campus Diversity at the United States Naval Academy: Evidence from Conjoint Survey Experiments

Although the value of diversity — in terms of race, ethnicity, gender, and socioeconomic status —to the U.S. military has been subject to debate, preferences for diversity at educational institutions for the military officers are rarely examined systematically. To address this, we investigate whether midshipmen at the U.S. Naval Academy favor prioritizing diversity in student admissions and faculty recruitment using conjoint analysis, a method suited for estimating attitudes on sensitive and politicized issues. The results show strong preferences in favor of applicants from disadvantaged socioeconomic backgrounds and moderate but still positive preferences for members of traditionally underrepresented racial/ethnic groups in both admissions and faculty recruitment. Midshipmen’s preferences with respect to gender are, however, less straightforward. In particular, we find a strong negative preference against gender non-binary applicants and candidates. Our findings suggest that midshipmen’s attitudes reflect both resolved and unresolved debates that resonate throughout the armed forces.
Self-Assembled BaTiO3-AuxAg1-x Low-Loss Hybrid Plasmonic Metamaterials with an Ordered "Nano-Domino-like" Microstructure.

Metallic plasmonic hybrid nanostructures have attracted enormous research interest due to the combined physical properties coming from different material components and the broad range of applications in nanophotonic and electronic devices. However, the high loss and narrow range of property tunability of the metallic hybrid materials have limited their practical applications. Here, a metallic alloy-based self-assembled plasmonic hybrid nanostructure, i.e., a BaTiO3-AuxAg1-x (BTO) vertically aligned nanocomposite, has been integrated by a templated growth method for low-loss plasmonic systems. Comprehensive microstructural characterizations including high-resolution scanning transmission electron microscopy (HRSTEM), energy-dispersive X-ray spectroscopy (EDS), and three-dimensional (3D) electron tomography demonstrate the formation of an ordered "nano-domino-like" morphology with Au0.4Ag0.6 nanopillars as cylindrical cores and BTO as square shells. By comparing with the BTO-Au hybrid thin film, the BTO-Au0.4Ag0.6 alloyed film exhibits much broader plasmon resonance, hyperbolic dispersion, low-loss, and thermally robust features in the UV-vis-NIR wavelength region. This study provides a feasible platform for a complex alloyed plasmonic hybrid material design with low-loss and highly tunable optical properties toward all-optical integrated devices.
Epitaxial Al-InAs Heterostructures as Platform for Josephson Junction Field-Effect Transistor Logic Devices

We fabricate Josephson junction field-effect transistors (JJ-FETs) using InAs quantum well heterostructure as the channel, epitaxial Al as superconducting electrodes, and scaled-down Al2O3 gate dielectrics. A systematic investigation of the gate voltage ( ${V}_{{G}}$ ) dependence of the critical current, normal state conductance, and characteristic voltage of the JJ-FETs coupled with capacitance measurements reveals different ${V}_{{G}}$ regimes in the proximity effect characterization of JJ-FETs. Self-consistent Poisson–Schrodinger simulations allow us to associate these ${V}_{{G}}$ regimes with the carriers populating one or more subbands at different vertical locations in the heterostructure. We also discuss the importance of oxide/channel interface quality and its impact on the practical implementation of JJ-FET Boolean logic gates with signal restoration.
Quantum magnetoconductivity characterization of interface disorder in indium-tin-oxide films on fused silica

Disorder arising from random locations of charged donors and acceptors introduces localization and diffusive motion that can lead to constructive electron interference and positive magnetoconductivity. At very low temperatures, 3D theory predicts that the magnetoconductivity is independent of temperature or material properties, as verified for many combinations of thin-films and substrates. Here, we find that this prediction is apparently violated if the film thickness d is less than about 300 nm. To investigate the origin of this apparent violation, the magnetoconductivity was measured at temperatures T = 15 – 150 K in ten, Sn-doped In2O3 films with d = 13 – 292 nm, grown by pulsed laser deposition on fused silica. We observe a very strong thickness dependence which we explain by introducing a theory that postulates a second source of disorder, namely, non-uniform interface-induced defects whose number decreases exponentially with the interface distance. This theory obeys the 3D limit for the thickest samples and yields a natural figure of merit for interface disorder. It can be applied to any degenerate semiconductor film on any semi-insulating substrate. Disorder in semiconductors may lead to quantum interference and positive magnetoconductivity, whose maximum value in 3D is independent of material properties. Here, an apparent violation of this upper bound, in Sn-doped In2O3 films on fused silica, is explained by a model that accounts for additional disorder close to the interface.
Superwoman, Racial Identity, and Teen Dating Violence Victimization among Young Black Women:

Young Black women consistently report the highest rates of teen dating violence (TDV) in the United States. They are also navigating a world in which they are facing historical marginalization and intersectional oppression. The Superwoman stereotypic role, in which Black women showcase strength and resist vulnerability, is often adapted in reaction to this normalized existence. Yet little research has examined how these constructs are related. In addition, research suggests that a positive racial identity may function as a psychological buffer against society's negative view of Black Americans and reduce involvement in violence. The current study examined the relationship between endorsement of a Superwoman role and TDV victimization among young Black women. A total of 481 Black women, aged 18-19, completed online survey measures assessing their racial identity beliefs, endorsement of racial stereotypes, and TDV experiences. The results of the path models showed that endorsement of a Superwoman role was associated with increased TDV victimization. Results also showed that racial centrality was inversely associated with TDV; the more the young women felt that being Black was a central part of their identity, the less they reported victimization. Findings suggest a need for attention to stereotype development and racial identity in the development of healthy romantic relationships for Black youth.
Enhanced Recovery After Surgery in the Urinary Diversion Population: Are Protocols Applied Differently in the Benign Indication Population?

Abstract Objective To retrospectively evaluate enhanced recovery after surgery (ERAS) protocol administration, hospital length of stay, 30-day readmission, and complication rates among cystectomy and/or urinary diversion patients with benign or malignant indication. Materials and methods Data was extracted retrospectively for cystectomy and/or urinary diversion performed at our institution from June 2016 to May 2019. Descriptive statistics, Chi squared, Wilcoxon rank-sum, binary logistic regression, and linear regression functions in R 4.0.4 (R Foundation), R Package “Tidverse” V1.3.0.9, and RStudio V1.44.1106 (RStudio, PBC) were used to analyze data. Results 102 patients met selection criteria with 36 and 66 patients in the benign and malignant indication cohorts, respectively. Significant differences between cohorts included BMI, age, opioid exposure, and spinal anomalies. The malignant cohort had higher ERAS completion rates for preoperative and intraoperative protocols (41% and 53% vs 14% and 19%). The mean ERAS item administration for benign and malignant indication patients differed significantly (2.9 vs 4.2, P Conclusion The benign urinary diversion/cystectomy population more frequently possesses characteristics adverse to ERAS protocol completion and in our study received fewer ERAS protocol items. This was associated with longer hospitalizations and higher postoperative complication rates. Population-specific ERAS protocols targeted at increasing ERAS completion could reduce morbidity.
Transparency considerations for describing statistical analyses in research.

Background Researchers who use the results of statistical analyses to draw conclusions about collected data must write a statistical analysis section in their manuscript. Describing statistical analyses in precise detail is as important as presenting the dosages of drugs and methodology of interventions. It is also essential for scientific accuracy and transparency in scientific research. Methods We evaluated the quality of the statistical analysis sections of clinical research articles published in the Korean Journal of Anesthesiology between February 2020 and February 2021. Using a Likert scale where 1, 2, and 3 represented "not described at all," "partially described," and "fully described," respectively, the following 6 items were assessed: 1) stating of the statistical analysis methods used, 2) rationale for and detailed description of the statistical analysis methods used, 3) parameters derived from the statistical analyses, 4) type and version of the statistical software package used, 5) significance level, and 6) sidedness of the test (one-sided vs. two-sided). The first 3 items evaluate issues directly related to the statistical analysis methods used and last 3 are indirectly related items. Results In all the included articles, the statistical analysis methods used were stated (score of 3). However, only 4 articles (12.9%) fully described the sidedness of the test (score of 3). Conclusions Authors tend not to describe the sidedness of statistical analysis tests in the methodology section of clinical research articles. It is essential that the sidedness be described in research studies.
Economics and Information Science

Information Science is rapidly evolving as a discipline, appropriating as it evolves useful theoretical and empirical hardware from related disciplines in the natural and social sciences. Some of the interfaces of these related disciplines with Information Science are not always clearly understood by information scientists with alien backgrounds. (Indeed, it has become increasingly difficult for one individual to achieve mastery of all these related disciplines.) One of the least widely understood interfaces is that of economics with Information Science. The economics-information science interface encompasses more than issues such as cost consciousness, or even “cost effectiveness”, in the design of information systems. The objective of this paper is to describe the basic structure of this interface (from the spective of a traditionally-trained economist) and to comment on some key issues central to future research.
Compiler optimizations for low power systems

Most current compiler optimizations focus on improving execution time. With the increasingly widespread use of embedded systems, however, power/energy consumption is also becoming an important issue. This is particularly true for battery-operated devices where power consumption has first class status along with performance and form factor.This paper makes the following contributions. First, we present two low-level (back-end) compiler optimizations for energy reduction. An important conclusion drawn from evaluating the impact of these optimizations is that compiling for power/energy is different from compiling for execution cycles. Second, we evaluate widely used state-of-the-art high-level compiler optimizations from a power consumption perspective. Further, we compare the relative impact of these high-level optimizations on both energy and performance metrics in order to identify any differences in optimizing for energy and performance. Finally, we cover a set of optimizations that are designed specifically for exploiting low power features supported by the hardware. In particular, we show how loop and data transformation can be used to exploit low-power mode control mechanisms available in some memory architectures.
The Importance of 3:1 Resonances in Stellar Pulsations

The 2:1 resonance between the fundamental and the second overtone modes has received a great deal of attention in the context of Cepheids. It was clearly shown that it causes the Hertzsprung bump progression and brings about the very characteristic observed variation of the Fourier phases with period (Buchler & Goupil, 1984, Ap.J., 279 , 394; Klapp, Goupil & Buchler, 1985, Ap.J., 296 , 514; Buchler & Kovacs, 1986, Ap.J., 303 , 749).
Novel insights in the role of peripheral corticotropin‐releasing factor and mast cells in stress‐induced visceral hypersensitivity

Visceral hypersensitivity is one of the hallmarks in irritable bowel syndrome (IBS) pathophysiology. Stress is well known to affect visceral sensitivity in humans and rodents, an effect which is associated in part with alterations of intestinal epithelial permeability in rodents. Although the pathophysiology of visceral hypersensitivity is still unclear, two key factors have been identified as playing a major role in its modulation, namely peripheral corticotropin-releasing factor (CRF) and mast cells. In a recent study in Neurogastroenterology and Motility, van den Wijngaard et al. demonstrate that the mast-cell dependent visceral hypersensitivity observed in maternally separated rats after an acute exposure to a psychological stress can be prevented but not reversed by the peripherally restricted CRF receptor antagonist, α-helical CRF9–41. They further show that the preventive effect of the CRF receptor antagonist is linked to a stabilization of mast cells and maintenance of the epithelial barrier at the colonic level. These data suggest that post stress mast cell activation and subsequent visceral hypersensitivity are not targeted by peripheral CRF receptor antagonists. These novel insights in the role of peripheral CRF in the modulation of stress-induced visceral hypersensitivity add to our growing understanding of the mechanisms that may lie at the origin of visceral pain disturbances following stress and will contribute to enhance the development of drugs that may have potential therapeutic benefits for IBS patients.
Image States on Single-Crystal Metal Surface

This chapter discusses the existing theories of image-state physics. It provides an overview of several topics, including the theories of image state-physics ranging from simple semi-classical models to those based on many-body approaches. Image state spectroscopy, which is useful in studying the interaction of an electron with a crystal surface, is important in the exploration of surface properties that lead to better understanding, for example, of two-dimensional surface confinement, epitaxial growth and surface structure. The relatively weak coupling between an external electron and the surface permits the observation of precise spectral features related to quasi-particle lifetimes and other many-body effects. The chapter also introduces three unoccupied-state spectroscopic techniques (such as nonlinear photoemission) and describes the measured values of the binding energy, lifetime, and effective mass of image-state systems along with a comparison of these measurements to theoretical calculations. Finally, the chapter discusses the use of image-state systems as probes of surface properties including the role of image-state spectroscopy in understanding two-dimensional surface confinement and in probing epitaxial growth and surface structure.
Filipino Children Exhibit Catch-Up Growth from Age 2 to 12 Years

Potential for catch-up growth among stunted children is thought to be limited after age 2 y, particularly when they remain in poor environments. We explored the extent to which there were improvements in height status from age 2 to 12 y in a cohort of >2, 000 children from the Cebu (The Philippines) Longitudinal Health and Nutrition Survey. At age 2 y, about 63% of sample children were stunted as defined by height-for-age (HAZ) -2 between ages 2 and 8.5 y. Similar factors predicted the improvement in linear growth from 8.5 to 12 y. These results suggest that there is a large potential for catch-up growth in children into the preadolescent years.
Assessment of Gap Junctional Intercellular Communication

Gap junctions are important plasma membrane organelles through which most cells in normal tissues communicate with each other. They exist in two neighboring cells and each cell contributes half of the structure. One gap junction consists of two hexameric connexons that dock with each other to create a channel. Six of the basic subunits referred to as connexins form a connexon. Less than one hundred to several thousand gap junction channels cluster together in the plane of the membrane. The gap junction channels serve as a regulated conduit for the intercellular exchange of small molecules. Maintenance of the integrity of gap junctional intercellular communication (GJIC) is important and required for normal electrical coupling, homeostasis, and embryogenesis. Aberrations of gap junctions have been related to human diseases such as cancer, cardiac arrhythmia, Charcot-Marie-tooth disease, and visceroatrial heterotaxia syndrome. This unit describes methods for measuring gap junctional intercellular communication using primary mouse hepatocytes as a model. Focus is only on functional evaluation based on dye coupling. Other methods, such as intracellular calcium waves and dual patch clamp, have been used to measure gap junctional communication, but these are not described in this unit.