cssi/SciSciGPT-SciSciNet huggingface dataset:
Lossless Compression of Binary Trees With Correlated Vertex Names

Compression schemes for advanced data structures have become a central modern challenge. Information theory has traditionally dealt with conventional data such as text, images, or video. In contrast, most data available today is multitype and context-dependent. To meet this challenge, we have recently initiated a systematic study of advanced data structures such as unlabeled graphs. In this paper, we continue this program by considering trees with statistically correlated vertex names. Trees come in many forms, but here we deal with binary plane trees (where order of subtrees matters) and their non-plane version (where order of subtrees doesn’t matter). Furthermore, we assume that each name is generated by a known memoryless source (horizontal independence), but a symbol of a vertex name depends in a Markovian sense on the corresponding symbol of the parent vertex name (vertical Markovian dependency). Such a model is closely connected to models of phylogenetic trees. While in general, the problem of multimodal compression and associated analysis can be extremely complicated, we find that in this natural setting, both the entropy analysis and optimal compression are analytically tractable. We evaluate the entropy for both types of trees. For the plane case, with or without vertex names, we find that a simple two-stage compression scheme is both efficient and optimal. We then present efficient and optimal compression algorithms for the more complicated non-plane case.
Inhibition of early response genes prevents changes in global joint metabolomic profiles in mouse post-traumatic osteoarthritis.

Summary Objective Although joint injury itself damages joint tissues, a substantial amount of secondary damage is mediated by the cellular responses to the injury. Cellular responses include the production and activation of proteases (MMPs, ADAMTSs, Cathepsins), and the production of inflammatory cytokines. The trajectory of cellular responses is driven by the transcriptional activation of early response genes, which requires Cdk9-dependent RNA Polymerase II phosphorylation. Our objective was to determine whether inhibition of cdk9-dependent early response gene activation affects changes in the joint metabolome. Design To model post-traumatic osteoarthritis, we subjected mice to non-invasive Anterior Cruciate Ligament (ACL)-rupture joint injury. Following injury, mice were treated with flavopiridol – a potent and selective inhibitor of Cdk9 kinase activity – to inhibit Cdk9-dependent transcriptional activation, or vehicle control. Global joint metabolomics were analyzed 1 h after injury. Results We found that injury induced metabolomic changes, including increases in Vitamin D3 metabolism, anandamide, and others. Inhibition of primary response gene activation immediately after injury largely prevented the global changes in the metabolomics profiles. Cluster analysis of joint metabolomes identified groups of injury-induced and drug-responsive metabolites. Conclusions Metabolomic profiling provides an instantaneous snapshot of biochemical activity representing cellular responses. We identified two sets of metabolites that change acutely after joint injury: those that require transcription of primary response genes, and those that do not. These data demonstrate the potential for inhibition of early response genes to alter the trajectory of cell-mediated degenerative changes following joint injury, which may offer novel targets for cell-mediated secondary joint damage.
Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models

Changes in computation and automated data collection have greatly increased interest in statistical models of dynamic networks. Many of the models employed for inference on large-scale dynamic netw...
Free Pseudodistance Growth Rates for Spatially Coupled LDPC Codes over the BEC

The minimum pseudoweight is an important parameter related to the decoding performance of LDPC codes with iterative message-passing decoding. In this paper, we consider ensembles of periodically time-varying spatially coupled LDPC (SC-LDPC) codes and the pseudocodewords arising from their finite graph covers of a fixed degree. We show that for certain (J,K)-regular SC-LDPC code ensembles and a fixed cover degree, the typical minimum pseudoweight of the unterminated (and associated tail-biting/terminated) SC-LDPC code ensembles grows linearly with the constraint (block) length as the constraint (block) length tends to infinity. We prove that one can bound the the free pseudodistance growth rate over a BEC from below (respectively, above) using the associated tail-biting (terminated) SC-LDPC code ensemble and show empirically that these bounds coincide for a sufficiently large period, which gives the exact free pseudodistance growth rate for the SC-LDPC ensemble considered.
T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method

We consider T-optimal experiment design problems for discriminating multi-factor polynomial regression models where the design space is defined by polynomial inequalities and the regression parameters are constrained to given convex sets. Our proposed optimality criterion is formulated as a convex optimization problem with a moment cone constraint. When the regression models have one factor, an exact semidefinite representation of the moment cone constraint can be applied to obtain an equivalent semidefinite program. When there are two or more factors in the models, we apply a moment relaxation technique and approximate the moment cone constraint by a hierarchy of semidefinite-representable outer approximations. When the relaxation hierarchy converges, an optimal discrimination design can be recovered from the optimal moment matrix, and its optimality can be additionally confirmed by an equivalence theorem. The methodology is illustrated with several examples.
Teaching For Justice: Introducing Translanguaging in an Undergraduate TESOL Course

This study investigates how introducing translanguaging as a way to affirm language and culture impacted students’ understandings of learning and teaching in a TESOL certificate course offered at a university in the northeast of the United States. As researchers, teachers, and students committed to justice, we explored the impact of introducing translanguaging in a course that was originally designed as a Sheltered English Immersion (SEI) course through collaborative, qualitative approaches of thematic analysis and macro- and micro-level analyses of power based on our unique individual experiences in the classroom. We found across our analysis that introducing translanguaging provided opportunities to shift assumptions and that, overall, students demonstrated critical sociocultural understandings of language that are foundational in teaching for justice. Ultimately, while we recognize the need for more explicit discussion about the purpose and pedagogy of translanguaging, the shifts towards teaching and embracing multilingual and multicultural realities through translanguaging which the study identified can contribute to the field of language education by demonstrating how teachers might open up possibilities in teaching for justice.
Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

Flight timetabling can greatly impact an airline’s operating profit, yet data-driven or model-based solutions to support it remain limited. Timetabling optimization is significantly complicated by ...
Medical Care of the Homeless: An American and International Issue

Homeless persons die significantly younger than their housed counterparts. In many cases, relatively straightforward primary care issues escalate into life-threatening, expensive emergencies. Poor health outcomes driven by negative interactions between comorbid symptoms meet the definition of a health syndemic in this population. Successful primary care of patients struggling with homelessness may result in long-term lifesaving measures along with decreased expenditure to hospital systems. This primary prevention requires patience, creativity, and acknowledgment that the source of many confounders may lay outside the control of these patients.
Towards a CAN IDS Based on a Neural Network Data Field Predictor

Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provides a lightweight and reliable broadcast protocol but is bereft of security features. As evidenced by many recent research works, CAN exploits are possible both remotely and with direct access, fueling a growing CAN intrusion detection system (IDS) body of research. A challenge for pioneering vehicle-agnostic IDSs is that passenger vehicles' CAN message encodings are proprietary, defined and held secret by original equipment manufacturers (OEMs). Targeting detection of next-generation attacks, in which messages are sent from the expected ECU at the expected time but with malicious content, researchers are now seeking to leverage "CAN data models'', which predict future CAN messages and use prediction error to identify anomalous, hopefully malicious CAN messages. Yet, current works model CAN signals post-translation, i.e., after applying OEM-donated or reverse-engineered translations from raw data. We present initial IDS results testing deep neural networks used to predict CAN data at the bit level, targeting IDS capabilities that avoiding reverse engineering proprietary encodings. Our results suggest the method is promising for data with signals exhibiting dependence on previous or concurrent inputs.
Simulation Study of the Capacitance and Charging Mechanisms of Ionic Liquid Mixtures near Carbon Electrodes

The performance of electric double-layer capacitors is strongly influenced by the choice of electrolyte, and electrolytes comprised of ionic liquid mixtures have shown promise for enabling high ene...
Ali Reza Sheikholeslami, 1941–2018

Ali Reza Sheikholeslami, a noted scholar of Middle Eastern and Iranian history and politics died at his home in Oxford, England, on 9 January 2018. He was 76.I first met Reza when we were both stud...
An accelerated elimination technique for the solution of perturbed Hamiltonian systems

A new technique is developed for the formal solution of non-degenerate or degenerate Hamiltonian systems under periodic perturbation through continually accelerated elimination of the periodic terms. Special features of the method are the ability to eliminate both short-period and longperiod variables simultaneously and the attainment of [formal] ‘quadratic convergence’ for non-degenerate systems and nearly quadratic convergence in degenerate cases. The technique utilizes Lie transforms and is based on an approach due to Kolmogorov and Arnol'd.
Continuous shear stress alters metabolism, mass-transport, and growth in electroactive biofilms independent of surface substrate transport

Electroactive bacteria such as Geobacter sulfurreducens and Shewanella onedensis produce electrical current during their respiration; this has been exploited in bioelectrochemical systems. These bacteria form thicker biofilms and stay more active than soluble-respiring bacteria biofilms because their electron acceptor is always accessible. In bioelectrochemical systems such as microbial fuel cells, corrosion-resistant metals uptake current from the bacteria, producing power. While beneficial for engineering applications, collecting current using corrosion resistant metals induces pH stress in the biofilm, unlike the naturally occurring process where a reduced metal combines with protons released during respiration. To reduce pH stress, some bioelectrochemical systems use forced convection to enhance mass transport of both nutrients and byproducts; however, biofilms’ small pore size limits convective transport, thus, reducing pH stress in these systems remains a challenge. Understanding how convection is necessary but not sufficient for maintaining biofilm health requires decoupling mass transport from momentum transport (i.e. fluidic shear stress). In this study we use a rotating disc electrode to emulate a practical bioelectrochemical system, while decoupling mass transport from shear stress. This is the first study to isolate the metabolic and structural changes in electroactive biofilms due to shear stress. We find that increased shear stress reduces biofilm development time while increasing its metabolic rate. Furthermore, we find biofilm health is negatively affected by higher metabolic rates over long-term growth due to the biofilm’s memory of the fluid flow conditions during the initial biofilm development phases. These results not only provide guidelines for improving performance of bioelectrochemical systems, but also reveal features of biofilm behavior. Results of this study suggest that optimized reactors may initiate operation at high shear to decrease development time before decreasing shear for steady-state operation. Furthermore, this biofilm memory discovered will help explain the presence of channels within biofilms observed in other studies.
Big Data Goes Small: Real-Time Spectrum-Driven Embedded Wireless Networking Through Deep Learning in the RF Loop

The explosion of 5G networks and the Internet of Things will result in an exceptionally crowded RF environment, where techniques such as spectrum sharing and dynamic spectrum access will become essential components of the wireless communication process. In this vision, wireless devices must be able to (i) learn to autonomously extract knowledge from the spectrum on-the-fly; and (ii) react in real time to the inferred spectrum knowledge by appropriately changing communication parameters, including frequency band, symbol modulation, coding rate, among others. Traditional CPU-based machine learning suffers from high latency, and requires application-specific and computationally-intensive feature extraction/selection algorithms. Conversely, deep learning allows the analysis of massive amount of unprocessed spectrum data without ad-hoc feature extraction. So far, deep learning has been used for offline wireless spectrum analysis only. Therefore, additional research is needed to design systems that bring deep learning algorithms directly on the device’s hardware and tightly intertwined with the RF components to enable real-time spectrum-driven decision-making at the physical layer. In this paper, we present RFLearn, the first system enabling spectrum knowledge extraction from unprocessed I/Q samples by deep learning directly in the RF loop. RFLearn provides (i) a complete hardware/software architecture where the CPU, radio transceiver and learning/actuation circuits are tightly connected for maximum performance; and (ii) a learning circuit design framework where the latency vs. hardware resource consumption trade-off can explored. We implement and evaluate the performance of RFLearn on custom software-defined radio built on a system-on-chip (SoC) ZYNQ-7000 device mounting AD9361 radio transceivers and VERT2450 antennas. We showcase the capabilities of RFLearn by applying it to solving the fundamental problems of modulation and OFDM parameter recognition. Experimental results reveal that RFLearn decreases latency and power by about 17x and 15x with respect to a software-based solution, with a comparatively low hardware resource consumption.
Training Variational Autoencoders with Buffered Stochastic Variational Inference

The recognition network in deep latent variable models such as variational autoencoders (VAEs) relies on amortized inference for efficient posterior approximation that can scale up to large datasets. However, this technique has also been demonstrated to select suboptimal variational parameters, often resulting in considerable additional error called the amortization gap. To close the amortization gap and improve the training of the generative model, recent works have introduced an additional refinement step that applies stochastic variational inference (SVI) to improve upon the variational parameters returned by the amortized inference model. In this paper, we propose the Buffered Stochastic Variational Inference (BSVI), a new refinement procedure that makes use of SVI’s sequence of intermediate variational proposal distributions and their corresponding importance weights to construct a new generalized importance-weighted lower bound. We demonstrate empirically that training the variational autoencoders with BSVI consistently out-performs SVI, yielding an improved training procedure for VAEs.
A Higher-Order Kolmogorov-Smirnov Test

We present an extension of the Kolmogorov-Smirnov (KS) two-sample test, which can be more sensitive to differences in the tails. Our test statistic is an integral probability metric (IPM) defined over a higher-order total variation ball, recovering the original KS test as its simplest case. We give an exact representer result for our IPM, which generalizes the fact that the original KS test statistic can be expressed in equivalent variational and CDF forms. For small enough orders (k <= 5), we develop a linear-time algorithm for computing our higher-order KS test statistic; for all others (k >= 6), we give a nearly linear-time approximation. We derive the asymptotic null distribution for our test, and show that our nearly linear-time approximation shares the same asymptotic null. Lastly, we complement our theory with numerical studies.
DeepRadioID: Real-Time Channel-Resilient Optimization of Deep Learning-based Radio Fingerprinting Algorithms

Radio fingerprinting provides a reliable and energy-efficient IoT authentication strategy by leveraging the unique hardware-level imperfections imposed on the received wireless signal by the transmitter's radio circuitry. Most of existing approaches utilize hand-tailored protocol-specific feature extraction techniques, which can identify devices operating under a pre-defined wireless protocol only. Conversely, by mapping inputs onto a very large feature space, deep learning algorithms can be trained to fingerprint large populations of devices operating under any wireless standard.One of the most crucial challenges in radio fingerprinting is to counteract the action of the wireless channel, which decreases fingerprinting accuracy significantly by disrupting hardware impairments. On the other hand, due to their sheer size, deep learning algorithms are hardly re-trainable in real-time. Another aspect that is yet to be investigated is whether an adversary can successfully impersonate another device's fingerprint. To address these key issues, this paper proposes DeepRadioID, a system to optimize the accuracy of deep-learning-based radio fingerprinting algorithms without retraining the underlying deep learning model. The key intuition is that through the application of a carefully-optimized digital finite input response filter (FIR) at the transmitter's side, we can apply tiny modifications to the waveform to strengthen its fingerprint according to the current channel conditions. We mathematically formulate the Waveform Optimization Problem (WOP) as the problem of finding, for a given trained neural network, the optimum FIR to be used by the transmitter to improve its fingerprinting accuracy.We extensively evaluate DeepRadioID on a experimental testbed of 20 nominally-identical software-defined radios, as well as on two datasets made up by 500 ADS-B devices and by 500 WiFi devices provided by the DARPA RFMLS program. Experimental results show that DeepRadioID (i) increases fingerprinting accuracy by about 35%, 50% and 58% on the three scenarios considered; (ii) decreases an adversary's accuracy by about 54% when trying to imitate other device's fingerprints by using their filters; (iii) achieves 27% improvement over the state of the art on a 100-device dataset.
Aberrant DNA methylation as a diagnostic biomarker of diabetic embryopathy

Maternal diabetes is a known teratogen that can cause a wide spectrum of birth defects, collectively referred to as diabetic embryopathy (DE). However, the pathogenic mechanisms underlying DE remain uncertain and there are no definitive tests to establish the diagnosis. Here, we explore the potential of DNA methylation as a diagnostic biomarker for DE and to inform disease pathogenesis. Bisulfite sequencing was used to identify gene regions with differential methylation between DE neonates and healthy infants born with or without prenatal exposure to maternal diabetes, and to investigate the role of allele-specific methylation at implicated sites. We identified a methylation signature consisting of 237 differentially methylated loci that distinguished infants with DE from control infants. These loci were found proximal to genes associated with Mendelian syndromes that overlap the DE phenotype (e.g., CACNA1C, TRIO, ANKRD11) or genes known to influence embryonic development (e.g., BRAX1, RASA3). Further, we identified allele-specific methylation (ASM) at 11 of these loci, within which 61.5% of ASM single-nucleotide variants are known expression quantitative trait loci (eQTLs). Our study suggests a role for aberrant DNA methylation and cis-sequence variation in the pathogenesis of DE and highlights the diagnostic potential of DNA methylation for teratogenic birth defects.
The relationship between adrenal incidentalomas and mortality risk

To determine all-cause mortality risk in patients with and without adrenal incidentaloma. Retrospective cohort study of patients with CT abdomen performed within 24 h of emergency room presentation at an academic medical center from January 1, 2005, to December 31, 2009, without history of adrenal disease, adrenal lab testing, or cancer. Incidentaloma cohort identified by database query of imaging reports followed by manual review and matched to no-nodule controls at 3:1 on age ± 1 year and exam date ± 3 months. Mortality ascertained by in-hospital deaths and National Death Index query. Survival analysis performed with Kaplan-Meier curves and Cox proportional hazards models. Among 42,575 adults with abdominal CT exams, 969 adrenal incidentaloma patients and 2907 no-nodule controls were identified. All 3876 individuals entered survival analysis with 31,182 person-years at risk (median follow-up 8.9 years [IQR, 6.9–10.7]). All-cause mortality was significantly higher among those with adrenal incidentalomas (353/969, 36.4%) compared with those without (919/2907, 31.6%; mortality difference 7.6 per 1000 person-years; multivariable-adjusted hazard ratio [aHR] 1.14; 95% CI, 1.003–1.29). Exploratory analyses, limited by missing covariates, found that adrenal incidentalomas were associated with significantly increased incidence of malignancy (aHR 1.61; 95% CI, 1.22–2.12), diabetes (aHR 1.43; 95% CI, 1.18–1.71), heart failure (aHR 1.32; 95% CI, 1.07–1.63), peripheral vascular disease (aHR 1.28; 95% CI, 1.95–1.56), renal disease (aHR 1.21; 95% CI, 1.01–1.44), and chronic pulmonary disease (aHR 1.22; 95% CI, 1.01–1.46) compared with controls. Adrenal incidentalomas are associated with increased mortality and may represent a clinically valuable biomarker. • Adrenal incidentalomas are associated with increased mortality. • Adrenal incidentaloma size is not predictive of mortality. • On exploratory analyses, adrenal incidentalomas are associated with chronic illnesses.
Friendly directors and the cost of regulatory compliance

Abstract We present evidence that, following the passage of the Sarbanes-Oxley Act, firms responded to the increased requirement for outside director monitoring by substituting insiders with outside directors who have social or professional connections to their CEOs. This substitution was most significant in firms that have higher outside director monitoring costs – small, young firms, firms outside the S&P 1500 index, and firms with low analyst scrutiny. The addition of these “friendly” directors did not reduce firm performance, suggesting that it may have been an efficient response by firms aimed at lowering the additional monitoring costs imposed by the new regulations. Our findings suggest that, as with many other aspects of board composition, the determinants and consequences of appointing friendly directors vary with the costs and benefits of outside director monitoring.
Dynamic response and validation of a flexible matrix composite

Testing and predicting the dynamic response of flexible matrix composites in impact loading condition face two primary challenges: (i) experimentally, existing techniques using existing instruments...
The truth behind the myth of the Folk theorem

Abstract We study the problem of computing an ϵ-Nash equilibrium in repeated games. Earlier work by Borgs et al. (2010) suggests that this problem is intractable. We show that if we make a slight change to their model—modeling the players as polynomial-time Turing machines that maintain state—and make a standard cryptographic assumption (that public-key cryptography can carried out), the problem can actually be solved in polynomial time. Our algorithm works not only for games with a finite number of players, but also for constant-degree graphical games (where, roughly speaking, which players' actions a given player's utility depends on are characterized by a graph, typically of bounded degree). As Nash equilibrium is a weak solution concept for extensive-form games, we additionally define and study an appropriate notion of subgame-perfect equilibrium for computationally bounded players, and show how to efficiently find such an equilibrium in repeated games (again, assuming public-key cryptography).
Mitigation Techniques for Attacks on 1-Dimensional Databases that Support Range Queries

In recent years, a number of attacks have been developed that can reconstruct encrypted one-dimensional databases that support range queries under the persistent passive adversary model. These attacks allow an (honest but curious) adversary (such as the cloud provider) to find the order of the elements in the database and, in some cases, to even reconstruct the database itself.
Synthesis of heterocycles via ligand-free palladium catalyzed reductive Heck cyclization

Abstract Synthesis of five and six membered heterocycles, indolines, 2,3-dihydrobenzofurans, chromans, isochromans, 1,2,3,4-tetrahydroquinolines, and 1,2,3,4-tetrahydroisoquinolines, in 70–99% yield by a ligand-free palladium catalyzed reductive Heck cyclization of phenyl bromides and chlorides, under mild conditions, is reported. Water was found to be essential for these reactions.
The Poly(heptatellurium) Dication: A New Twist

A new form of polyheptatellurium dication, {[Te7][AsF6]2}∞, has been synthesized at room temperature and structurally characterized by single-crystal X-ray crystallography. The new infinite polymeric chain consists of six-membered rings bridged through a tellurium atom. Its structure is discussed and compared to those of other tellurium cation systems, including another polyheptatellurium dication, {[Te7][WOBr5]2}∞, and the previously reported “{[Te6][AsF6]2”.
Development of one-pot synthesis of α-hydroxy α-trifluoromethyl amides

Abstract An efficient one-pot-three-step method has been developed to assemble readily available aryl or heteroaryl halides, methyl trifluoropyruvate, and amines into biologically important α-hydroxy α-trifluoromethyl amides without isolation of any intermediates.
Transcriptional network analysis on brains reveals a potential regulatory role of PPP1R3F in autism spectrum disorders

This study aims at identifying master regulators of transcriptional networks in autism spectrum disorders (ASDs). With two sets of independent RNA-Seq data generated on cerebellum from patients with ASDs and control subjects (N = 39 and 45 for set 1, N = 24 and 38 for set 2, respectively), we carried out a network deconvolution of transcriptomic data, followed by virtual protein activity analysis. We identified PPP1R3F (Protein Phosphatase 1 Regulatory Subunit 3F) as a candidate master regulator affecting a large body of downstream genes that are associated with the disease phenotype. Pathway analysis on the identified targets of PPP1R3F in both datasets indicated alteration of endocytosis pathway. Despite a limited sample size, our study represents one of the first applications of network deconvolution approach to brain transcriptomic data to generate hypotheses that may be further validated by large-scale studies.
In situ characterization of the adsorption of cinchona chiral modifiers on platinum surfaces

Abstract The adsorption of cinchona chiral modifiers on platinum surfaces has been characterized with surface-sensitive techniques. The uptakes of quinoline and lepidine, models for the aromatic moiety of the cinchona, were first studied on Pt(1 1 1) single crystal surfaces and under ultrahigh vacuum by reflection–absorption infrared spectroscopy (RAIRS). Adsorption at low (∼100 K) temperatures is molecular and without any preference for a distinct molecular geometry. Temperature programmed desorption (TPD) experiments indicated extensive dehydrogenation starting at about 250 K, and infrared data obtained at room temperature corroborated the conversion of some of the aromatic CH bonds to a more aliphatic environment. An in situ RAIRS characterization of the adsorption of cinchonidine from carbon tetrachloride solutions onto a polycrystalline platinum substrate proved that in hydrogen-treated solvents the decomposition of the adsorbate is inhibited, so that the cinchona retains its molecular character on the surface at room temperature. Three adsorption regimes were identified depending on the concentration of cinchonidine in solution, namely, no observable adsorption at low concentrations, bonding via a flat-lying quinoline moiety in the intermediate concentration range, and a tilted adsorption geometry near saturation. The optimum activity and enantioselectivity reported previously in catalytic processes for intermediate concentrations can then be associated with the orientation of the aromatic ring parallel to the surface plane. In a separate study, it was determined that hydrogen plays a unique role in cinchonidine adsorption, initially conditioning the surface for the uptake (presumably by reduction and removal of surface contaminants), and later hydrogenating the quinoline fragment of the modifier and facilitating its desorption. Finally, different solvents were shown to behave differently in these systems. Specifically, adsorbed cinchonidine remains on the platinum surface after flushing with non-polar solutions such as cyclohexane, but can be easily removed by more polar solvents such as dichloromethane. This behavior correlates well with both the solubility of cinchonidine and the performance of the cinchona/platinum catalyst as a function of the nature of the solvent.
N = 2 super Yang-Mills and subgroups of SL(2,Z)

We discuss SL(2,Z) subgroups appropriate for the study of N = 2 super Yang-Mills with Nf = 2n flavors. Hyperelliptic curves describing such theories should have coefficients that are modular forms of these subgroups. In particular, uniqueness arguments are sufficient to construct the SU(3) curve, up to two numerical constants, which can be fixed by making some assumptions about strong coupling behavior. We also discuss the situation for higher groups. We also include a derivation of the closed form β-function for the SU(2) and SU(3) theories without matter, and the massless theories with Nf = n.
Improved syntheses of methyl (14E)- and (14Z)-dehydrocrepenynate: key intermediates in plant and fungal polyacetylene biosynthesis

Abstract Efficient syntheses of the (14E)- and (14Z)-isomers of methyl dehydrocrepenynate have been achieved. The key steps involve Pd-catalyzed cross-coupling reactions furnishing the CC double bonds between C14 and C15, followed by Wittig reactions to construct the (Z)-alkene at C9. High overall yields and stereoselectivities were achieved for both isomers.
Reductive cleavage of 2-methyleneoxetanes with lithium and 4,4′-di-tert-butylbiphenyl

Abstract 3,3-Dimethyl-2-methylene-4-phenyloxetane (5) undergoes reductive cleavage with lithium and 4,4′-di-tert-butylbiphenyl (DTBB) to give an intermediate dianion, which reacts regioselectively with aldehydes and ketones to give aldol adducts in modest yields. Alternatively, the enolate can be trapped with TMSCl to give the corresponding silyl enol ether.
An Unexpected Phosphine-Catalyzed [3 + 2] Annulation. Synthesis of Highly Functionalized Cyclopentenes

An unexpected phosphine-catalyzed [3 + 2] annulation from electron-deficient allenes and substituted alkylidenemalononitriles was realized in which the allylic moiety of the substituted alkylidenemalononitriles served as the three carbon unit of the cyclopentenes instead of the electron-deficient allenes.
A new entry to the isogeissoschizoid skeleton.

The tetracyclic isogeissoschizoid skeleton has been prepared by a novel route that involves the ozonolysis and double reductive amination of a cyclopentene, a nickel-catalyzed cyclization, and a late-stage Fischer indole synthesis.
Elucidating interplay of speed and accuracy in biological error correction.

One of the most fascinating features of biological systems is the ability to sustain high accuracy of all major cellular processes despite the stochastic nature of underlying chemical processes. It is widely believed that such low error values are the result of the error-correcting mechanism known as kinetic proofreading. However, it is usually argued that enhancing the accuracy should result in slowing down the process, leading to the so-called speed–accuracy trade-off. We developed a discrete-state stochastic framework that allowed us to investigate the mechanisms of the proofreading using the method of first-passage processes. With this framework, we simultaneously analyzed the speed and accuracy of the two fundamental biological processes, DNA replication and tRNA selection during the translation. The results indicate that these systems tend to optimize speed rather than accuracy, as long as the error level is tolerable. Interestingly, for these processes, certain kinetic parameters lay in the suboptimal region where their perturbations can improve both speed and accuracy. Additional constraints due to the energetic cost of proofreading also play a role in the error correcting process. Our theoretical findings provide a microscopic picture of how complex biological processes are able to function so fast with high accuracy.
Cation−Cation Interactions between Uranyl Cations in a Polar Open-Framework Uranyl Periodate

Novel open-framework alkali metal uranyl periodates, having the formula A[(UO2)3(HIO6)(OH)(O)(H2O)]·1.5H2O (A = Li, Na, K, Rb, Cs), have been prepared through mild hydrothermal synthesis. These isostructural compounds contain distorted UO7 pentagonal bipyramids that are linked through a uranyl (UO22+) to uranyl cation−cation interaction. This interaction arises from a single axial uranyl oxygen coordinating at an equatorial site of an adjacent uranyl unit. These uranium oxide polyhedra are further bound by IO6 distorted octahedra creating an open-framework structure whose channels contain the alkali metal cations.
Temporal dependence of shifts in mu opioid receptor mobility at the cell surface after agonist binding observed by single-particle tracking

Agonist binding to the mu opioid receptor (MOR) results in conformational changes that allow recruitment of G-proteins, activation of downstream effectors and eventual desensitization and internalization, all of which could affect receptor mobility. The present study employed single particle tracking (SPT) of quantum dot labeled FLAG-tagged MORs to examine shifts in MOR mobility after agonist binding. FLAG-MORs on the plasma membrane were in both mobile and immobile states under basal conditions. Activation of FLAG-MORs with DAMGO caused an acute increase in the fraction of mobile MORs, and free portions of mobile tracks were partially dependent on interactions with G-proteins. In contrast, 10-minute exposure to DAMGO or morphine increased the fraction of immobile FLAG-MORs. While the decrease in mobility with prolonged DAMGO exposure corresponded to an increase in colocalization with clathrin, the increase in colocalization was present in both mobile and immobile FLAG-MORs. Thus, no single mobility state of the receptor accounted for colocalization with clathrin. These findings demonstrate that SPT can be used to track agonist-dependent changes in MOR mobility over time, but that the mobility states observed likely arise from a diverse set of interactions and will be most informative when examined in concert with particular downstream effectors.
Synthesis of chiral phosphine ligands with aromatic backbones and their applications in asymmetric catalysis

Abstract A general strategy for the synthesis of new chiral phosphine ligands has been discovered. A common feature of these ligands is that they contain rigid aromatic backbones which can be used to restrict conformational flexibility. The bite angle of P-M-P can be changed systematically depending on the aromatic backbone. Many asymmetric reactions can potentially be catalyzed by transition metal complexes of these ligands. Moderate selectivity has been realized in the reaction between 1,3-diphenyl-2-propenyl acetate and dimethyl malonate using palladium complexes of these ligands.
Cycloadditions of N-sulfonyl nitrones generated by lewis acid catalyzed rearrangement of oxaziridines.

We have developed cycloaddition reactions of novel, electron-deficient N-nosyl nitrones that arise from the titanium(IV)-catalyzed rearrangement of the corresponding N-nosyl oxaziridines. A diverse range of styrenes and oxaziridines react smoothly in this transformation, producing structurally varied N-nosyl isoxazolidines in good yields and with excellent diastereoselectivity. Importantly, the nosyl protecting group can be easily removed under mild conditions without concomitant cleavage of the sensitive isoxazolidine nitrogen-oxygen bond, allowing efficient access to N-unsubstituted isoxazolidines for further synthetic manipulation and biological evaluation.
Ternary and quaternary uranium and thorium chalcogenides

A survey of the structural chemistry of ternary and quaternary uranium (U) and thorium (Th) chalcogenides is presented. Specific attention is paid to the coordination environments of U and Th in a variety of classical and nonclassical structure types. The problems of defining the oxidation state of U from U-Q (Q = S, Se, Te) bond lengths and magnetic susceptibility data are also discussed.
How do research faculty in the biosciences evaluate paper authorship criteria

Authorship of peer-reviewed journal articles and abstracts has become the primary currency and reward unit in academia. Such a reward is crucial for students and postdocs who are often under-compensated and thus highly value authorship as an incentive. While numerous scientific and publishing organizations have written guidelines for determining author qualifications and author order, there remains much ambiguity when it comes to how these criteria are weighed by research faculty. Here, we sought to provide some initial insight on how faculty view the relative importance of 11 criteria for scientific authorship. We distributed an online survey to 564 biomedical engineering, biology, and bioengineering faculty members at 10 research institutions across the United States. The response rate was approximately 18%, resulting in a final sample of 102 respondents. Results revealed an agreement on some criteria, such as time spent conducting experiments, but there was a lack of agreement regarding the role of funding procurement. This study provides quantitative assessments of how faculty members in the biosciences evaluate authorship criteria. We discuss the implications of these findings for researchers, especially new graduate students, to help navigate the discrepancy between official policies for authorship and the contributions that faculty truly value.
A Study of Essentially Free Carbocations Derived via Diazonium and Oxo Diazonium Ions in the Liquid Phase

Nitrogen- and nitrous oxide-separated ion pairs containing 4-substituted benzyl cations and carboxylate or tosylate anions were prepared by thermolysis of N-nitroso- and N-nitroamides, acidification of phenyldiazomethane, and nitrosation of N-benzyl-O-benzoylhydroxylamine. The cations were generated in benzene/toluene and benzene/anisole mixtures and were found to partition between the counterion and the solvent and between the aromatic cosolvent and benzene. A familial relationship among the methods was observed. As the cation became more reactive, the yield of solvent-derived products (SDPs) rose and the ratio of rate constants for its reaction with toluene versus benzene, kT/kB, fell. The yield of SDP also rose as the temperature was decreased and as N2 was replaced by N2O; however, kT/kB remained unchanged. Inert diluents had no effect on kT/kB but decreased hydrocarbon yield by 40% on 2-fold dilution. In the presence of reactive diluents that are converted into secondary alkylating agents, both the %...
Low temperature specific heat of CePt2-derived compounds

Alloying Ir or Rh on the Pt-sites in antiferromagnetic CePt2 results in a decrease of TN. For x>0.25 in Ce(Pt1−xMx)2 (M = Ir, Rh) no magnetic order is detected, but CT increases with decreasing temperature below 10 K. The electronic part of the specific heat at temperatures higher than 10 K, γHT, shows a maximum dependent on the concentration x. The dilution of Ce in (CexPt1 − x)Pt2 also results in a suppression of the magnetic order and an enhanced γHT. In the latter case the enhanced γHT can be explained by a transfer of degrees of freedom from the magnetic ordering to the screening process.
Kinetics of Cyclopropylcarbinyl Radical Ring Openings Measured Directly by Laser Flash Photolysis

The kinetics of ring openings of cyclopropylcarbinyl radicals containing reporter groups were measured directly by laser flash photolysis (LFP) methods. The reporter groups are aryl-substituted cyclopropanes at the position of the radical center in the incipient product, and the initial ring-opening reaction gives an aryl-substituted cyclopropylcarbinyl radical that opens “instantly” on the nanosecond time scale to give benzylic and diphenylalkyl radical products that are detected by UV spectroscopy. Three reporter group designs have been studied. The most useful design is that in substituted (trans-2-(2,2-diphenylcyclopropyl)cyclopropyl)methyl radicals (7). The important synthetic intermediate for production of this series is N-methoxy-N-methyl-trans-2-(2,2-diphenyl-1R*-cyclopropyl)-1S*,2R*-cyclopropanecarboxamide (15a) which has been prepared diastereomerically pure. The syntheses of 15a and a series of PTOC ester radical precursors derived from 15a are described. Laser photolysis (355 nm) of PTOC ester...
Global Well-posedness for the Logarithmically Energy-Supercritical Nonlinear Wave Equation with Partial Symmetry

We establish global well-posedness and scattering results for the logarithmically energy-supercritical nonlinear wave equation, under the assumption that the initial data satisfies a partial symmetry condition. These results generalize and extend work of Tao in the radially symmetric setting. The techniques involved include weighted versions of Morawetz and Strichartz estimates, with weights adapted to the partial symmetry assumptions. In an appendix, we establish a corresponding quantitative result for the energy-critical problem.
Identifying antimicrobial peptides using word embedding with deep recurrent neural networks.

Motivation Antibiotic resistance constitutes a major public health crisis, and finding new sources of antimicrobial drugs is crucial to solving it. Bacteriocins, which are bacterially produced antimicrobial peptide products, are candidates for broadening the available choices of antimicrobials. However, the discovery of new bacteriocins by genomic mining is hampered by their sequences' low complexity and high variance, which frustrates sequence similarity-based searches. Results Here we use word embeddings of protein sequences to represent bacteriocins, and apply a word embedding method that accounts for amino acid order in protein sequences, to predict novel bacteriocins from protein sequences without using sequence similarity. Our method predicts, with a high probability, six yet unknown putative bacteriocins in Lactobacillus. Generalized, the representation of sequences with word embeddings preserving sequence order information can be applied to peptide and protein classification problems for which sequence similarity cannot be used. Availability and implementation Data and source code for this project are freely available at: https://github.com/nafizh/NeuBI. Supplementary information Supplementary data are available at Bioinformatics online.
Suzuki-Miyaura cross-coupling of lithium n-alkylborates

The palladium-catalyzed cross-coupling of lithium n-alkylborates, generated in situ via addition of sec-butyl lithium to boronate esters, proceeds in moderate to good yields with a wide variety of electrophiles.
Density functional studies of catalytic alkane dehydrogenation by an iridium pincer complex with and without a hydrogen acceptor

Abstract Density functional calculations have been applied to models of both transfer and acceptorless alkane dehydrogenation for the iridium(III) pincer complex, ( R PCP )IrH2 ( R PCP  η 3 -C6H3(CH2PR2)2-1,3). The iridium pincer complex is the first efficient homogeneous catalyst that does not require photons or sacrificial hydrogen acceptors to drive the reaction, although with the latter the transfer reaction can accomplished under mild conditions. There are four essential steps for the catalytic cycle in both transfer and acceptorless reactions: oxidative addition of alkane, reductive elimination, β-hydrogen (β-H) transfer, and loss of olefin. The transfer reaction can utilize a hydrogen acceptor to produce a 14-electron intermediate, ( R PCP )Ir(I), and the acceptorless reaction can produce an 18-electron intermediate, ( R PCP )Ir(V)(H)3(alkyl) species. Because the critical barriers are well-balanced in the Ir(V) catalytic cycle for acceptorless alkane dehydrogenation, no transition state (TS) is higher in energy than the products and no intermediate is lower in energy than the reactant. This balance could explain why pincer complexes are more efficient catalysts for alkane dehydrogenation than the corresponding Cp–Ir(III) complex. Entropy contributions, which play a larger role at high temperature, open new pathways for the acceptorless reaction. Free energies of activation suggest that the dynamics of the acceptorless reaction might be sampling the entire range of pathways and Ir oxidation states from Ir(I) to Ir(V).
PROTOTYPE SANDIA OCTAHEDRAL MOLECULAR SIEVE (SOMS) NA2NB2O6.H2O: SYNTHESIS, STRUCTURE AND THERMODYNAMIC STABILITY

A new microporous phase Na2Nb2O6·H2O, which transforms to NaNbO3 perovskite on heating, has been synthesized by the hydrothermal method. Rietveld analysis of powder synchrotron X-ray diffraction data reveals that the structure comprises a framework of [NbO6] and [NaO6] octahedra with other Na+ being located in the channels (space group C2/c; a = 17.0511(9) A; b = 5.0293(2) A; c = 16.4921(9) A; β =113.942(2)°). This phase belongs to the recently synthesized Sandia octahedral molecular sieves (SOMS) family, Na2Nb2-xMxO6-x(OH)x·H2O (M = Ti, Zr) and is the archetype for the substituted structures. Using drop-solution calorimetry into molten 3Na2O·4MoO3 at 974 K, the enthalpies of formation of Na2Nb2O6·H2O from the constituent oxides and from the elements have been determined to be −295.4 ± 4.8 and −2895.5 ± 6.4 kJ/mol, respectively. From the drop-solution calorimetric data for Na2Nb2O6·H2O and its dehydrated perovskite phase, the enthalpy of the dehydration reaction, Na2Nb2O6·H2O → 2NaNbO3 + H2O, has been der...
A mild, one-pot synthesis of disubstituted benzimidazoles from 2-nitroanilines

Abstract A one-pot synthesis of disubstituted benzimidazoles from 2-nitroanilines is described. Hydrogenation of N-substituted 2-nitroanilines with palladium on carbon as catalyst in the presence of trimethyl orthoformate and catalytic pyridinium p -toluenesulfonate (PPTS) at room temperature provided good to excellent yields of the corresponding disubstituted benzimidazoles.