cssi/SciSciGPT-SciSciNet huggingface dataset:
100 research ideas: extending the frontiers of research in corporate finance

Abstract Where can one systematically find research ideas? I propose a scheme to classify and broadly generalize the sources of inspiration for research topics, with emphasis on corporate finance. In the process, I propose 100 new research topics awaiting the brave and persistent.
Structural and electronic investigations of PbTa4O11 and BiTa7O19 constructed from α-U3O8 types of layers

Abstract The PbTa4O11 and BiTa7O19 phases were prepared by ion-exchange and solid-state methods, respectively, and their structures were characterized by neutron time-of-flight diffraction and Rietveld refinement methods (PbTa4O11, R 3 (No. 146), a=6.23700(2) A, c=36.8613(1) A; BiTa7O19, P 6 ¯ c 2 (No. 188), a=6.2197(2) A, c=20.02981(9) A). Their structures are comprised of layers of TaO6 octahedra surrounded by three 7-coordinate Pb(II) cations or two 8-coordinate Bi(III) cations. These layers alternate down the c-axis with α-U3O8 types of single and double TaO7 pentagonal bipyramid layers. In contrast to earlier studies, both phases are found to crystallize in noncentrosymmetric structures. Symmetry-lowering structural distortions within PbTa4O11, i.e. R 3 ¯ c →R3, are found to be a result of the displacement of the Ta atoms within the TaO7 and TaO6 polyhedra, towards the apical and facial oxygen atoms, respectively. In BiTa7O19, relatively lower reaction temperatures leads to an ordering of the Bi/Ta cations within a lower-symmetry structure, i.e., P63/mcm→ P 6 ¯ c 2 . In the absence of Bi/Ta site disorder, the Ta–O–Ta bond angles decrease and the Ta–O bond distances increase within the TaO7 double layers. Scanning electron microscopy images reveal two particle morphologies for PbTa4O11, hexagonal rods and finer irregularly-shaped particles, while BiTa7O19 forms as aggregates of irregularly-shaped particles. Electronic-structure calculations confirm the highest-energy valence band states are comprised of O 2p-orbitals and the respective Pb 6s-orbital and Bi 6s-orbital contributions. The lowest-energy conduction band states are composed of Ta 5d-orbital contributions that are delocalized over the TaO6 octahedra and layers of TaO7 pentagonal bipyramids. The symmetry-lowering distortions in the PbTa4O11 structure, and the resulting effects on its electronic structure, lead to its relatively higher photocatalytic activity compared to similar structures without these distortions.
Structures of ordered tungsten- or molybdenum-containing quaternary perovskite oxides

The room temperature crystal structures of six A{sub 2}MMoO{sub 6} and A{sub 2}MWO{sub 6} ordered double perovskites were determined from X-ray and neutron powder diffraction data. Ba{sub 2}MgWO{sub 6} and Ba{sub 2}CaMoO{sub 6} both adopt cubic symmetry (space group Fm3-bar m, tilt system a{sup 0}a{sup 0}a{sup 0}). Ba{sub 2}CaWO{sub 6} has nearly the same tolerance factor (t=0.972) as Ba{sub 2}CaMoO{sub 6} (t=0.974), yet it surprisingly crystallizes with I4/m symmetry indicative of out-of-phase rotations of the MO{sub 6} octahedra about the c-axis (a{sup 0}a{sup 0}c{sup -}). Sr{sub 2}ZnMoO{sub 6} (t=0.979) also adopts I4/m symmetry; whereas, Sr{sub 2}ZnWO{sub 6} (t=0.976) crystallizes with monoclinic symmetry (P2{sub 1}/n) with out-of-phase octahedral tilting distortions about the a- and b-axes, and in-phase tilting about the c-axis (a{sup -}a{sup -}c{sup +}). Ca{sub 2}CaWO{sub 6} (t=0.867) also has P2{sub 1}/n symmetry with large tilting distortions about all three crystallographic axes and distorted CaO{sub 6} octahedra. Analysis of 93 double perovskites and their crystal structures showed that while the type and magnitude of the octahedral tilting distortions are controlled primarily by the tolerance factor, the identity of the A-cation acts as the secondary structure directing factor. When A=Ba{sup 2+} the boundary between cubic and tetragonal symmetries falls near t=0.97,more » whereas when A=Sr{sup 2+} this boundary falls somewhere between t=1.018 and t=0.992. - Graphical abstract: A survey of the tolerance factor of 41 Mo/W- and 52 Nb/Ta-containing quaternary perovskites plotted as a function of the difference between the two six-coordinate M-cation ionic radii. Compounds with cubic symmetry are represented by diamonds, those with tetragonal symmetry are represented by squares, those with I2/m monoclinic symmetry are represented by Multiplication-Sign , and those with P2{sub 1}/n monoclinic symmetry are represented by triangles. White symbols represent compositions where A=Ba{sup 2+}, gray symbols represent compositions where A=Sr{sup 2+}, and black symbols represent where A=Ca{sup 2+}. The filled circle represents rhombohedral Ba{sub 2}BiTaO{sub 6} (t=0.961; space group-R3-bar ; tilt system-a{sup -}a{sup -}a{sup -}). References for the compounds included in this figure are listed in the Supporting Information File. Black-Small-Square Highlights: Black-Right-Pointing-Pointer Reports the structures of six double perovskites containing either Mo{sup 6+} or W{sup 6+}. Black-Right-Pointing-Pointer Compounds with similar tolerance factors (t) exhibited different symmetries. Black-Right-Pointing-Pointer This effect was observed in Sr{sub 2}ZnMO{sub 6} and Ba{sub 2}CaMO{sub 6} (M=Mo or W). Black-Right-Pointing-Pointer Contains a structural survey of 93 double perovskites. Black-Right-Pointing-Pointer Octahedral tilting distortions are controlled by t and the nature of the A-cation.« less
Robo1 and 2 Repellent Receptors Cooperate to Guide Facial Neuron Cell Migration and Axon Projections in the Embryonic Mouse Hindbrain

Abstract The facial nerve is necessary for our ability to eat, speak, and make facial expressions. Both the axons and cell bodies of the facial nerve undergo a complex embryonic developmental pattern involving migration of the cell bodies caudally and tangentially through rhombomeres, and simultaneously the axons projecting to exit the hindbrain to form the facial nerve. Our goal in this study was to test the functions of the chemorepulsive receptors Robo1 and Robo2 in facial neuron migration and axon projection by analyzing genetically marked motor neurons in double-mutant mouse embryos through the migration time course, E10.0–E13.5. In Robo1/2 double mutants, axon projection and cell body migration errors were more severe than in single mutants. Most axons did not make it to their motor exit point, and instead projected into and longitudinally within the floor plate. Surprisingly, some facial neurons had multiple axons exiting and projecting into the floor plate. At the same time, a subset of mutant facial cell bodies failed to migrate caudally, and instead either streamed dorsally toward the exit point or shifted into the floor plate. We conclude that Robo1 and Robo2 have redundant functions to guide multiple aspects of the complex cell migration of the facial nucleus, as well as regulating axon trajectories and suppressing formation of ectopic axons.
Decreased grey matter volume in mTBI patients with post-traumatic headache compared to headache-free mTBI patients and healthy controls: A longitudinal MRI study

Traumatic brain injury (TBI) occurs in 1.7 million people annually and many patients go on to develop persistent disorders including post-traumatic headache (PTH). PTH is considered chronic if it continues past 3 months. In this study we aimed to identify changes in cerebral grey matter volume (GMV) associated with PTH in mild TBI patients. 50 mTBI patients (31 Non-PTH; 19 PTH) underwent MRI scans: within 10 days post-injury, 1 month, 6 months and 18 months. PTH was assessed at visit 4 by a post-TBI headache questionnaire. Healthy controls (n = 21) were scanned twice 6 months apart. Compared to non-PTH, PTH patients had decreased GMV across two large clusters described as the right anterior-parietal (p = 0.012) and left temporal-opercular (p = 0.027). Compared to healthy controls non-PTH patients had decreased GMV in the left thalamus (p = 0.047); PTH patients had decreased GMV in several extensive clusters: left temporal-opercular (p = 0.003), temporal-parietal (p = 0.041), superior frontal gyrus (p = 0.008) and right middle frontal/superior frontal gyrus (0.004) and anterior-parietal (p = 0.003). Differences between PTH and non-PTH patients were most striking at early time points. These early changes may be associated with an increased risk of PTH. Patients with these changes should be monitored for chronic PTH.
Higher Nuclearity Rhenium Halide Clusters That Contain Re–Re Multiple Bonds

The discovery that the rhenium chloride cluster Re3Cl9 and its chloro-anion [Re3Cl12]3- contain a triangular cluster of Re atoms and Re–Re bond orders of two was first reported in 1963. This led very quickly to the report by F. A. Cotton of the first species with a metal–metal quadruple bond, namely, the [Re2Cl8]2- anion. While the field of dinuclear multiple bond chemistry has undergone explosive growth in the last 40 years, that involving the chemistry of higher nuclearity clusters with metal–metal multiple bonds is much more limited. One of the relatively few exceptions is encountered with the aforementioned rhenium halides that contain the triangular [Re3]9+ core. In the present review, the synthesis, structures and reactivity of these halide clusters and those of higher nuclearity that contain Re–Re multiple bonds are surveyed. This article provides a comprehensive review of the literature covering the 40 year period 1963–2003.
α-Azido acids in heterocyclic synthesis

Abstract 2-Aminobenzophenones and acetophenones were N-acylated with α-azido carboxylic acids to give the corresponding anilides. Reductive cyclization provided 3-substituted-2H-1,4-benzodiazepin-2-ones in good (46–99%) yields.
Trans-Selective Conversions of γ-Hydroxy-α,β-Alkynoic Esters to γ-Hydroxy-α,β-Alkenoic Esters

γ-Hydroxy-α,β-acetylenic esters are used as precursors to prepare γ-hydroxy-α,β-alkenoic esters by means of trans-selective additions of two hydrogen atoms or one hydrogen atom and one iodine atom across the triple bonds. These methods allow for the preparation of β-substituted and α,β-disubstituted alkenoic esters in highly stereoselective manners.
SequencEnG: an interactive knowledge base of sequencing techniques

Summary Next-generation sequencing (NGS) techniques are revolutionizing biomedical research by providing powerful methods for generating genomic and epigenomic profiles. The rapid progress is posing an acute challenge to students and researchers to stay acquainted with the numerous available methods. We have developed an interactive online educational resource called Sequencing Techniques Engine for Genomics (SequencEnG) to provide a tree-structured knowledge base of 66 different sequencing techniques and step-by-step NGS data analysis pipelines comparing popular tools. SequencEnG is designed to facilitate barrier-free learning of current NGS techniques and provides a user-friendly interface for searching through experimental and analysis methods. Availability and implementation SequencEnG is part of the project Knowledge Engine for Genomics (KnowEnG) and is freely available at http://education.knoweng.org/sequenceng/.
Balance between allylic C-H activation and cyclopropanation in the reactions of donor/acceptor-substituted rhodium carbenoids with trans-alkenes.

Rhodium(II)-catalyzed reactions of aryldiazoacetates with (E)-aryl-substituted alkenes generate C−H insertion products and/or cyclopropanes. The product distribution is influenced by the nature of the donor group on the carbenoid, the structure of the (E)-aryl-substituted alkenes, and the rhodium catalyst.
Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions

Genome-scale metabolic models provide a valuable context for analyzing data from diverse high-throughput experimental techniques. Models can quantify the activities of diverse pathways and cellular functions. Since some metabolic reactions are only catalyzed in specific environments, several algorithms exist that build context-specific models. However, these methods make differing assumptions that influence the content and associated predictive capacity of resulting models, such that model content varies more due to methods used than cell types. Here we overcome this problem with a novel framework for inferring the metabolic functions of a cell before model construction. For this, we curated a list of metabolic tasks and developed a framework to infer the activity of these functionalities from transcriptomic data. We protected the data-inferred tasks during the implementation of diverse context-specific model extraction algorithms for 44 cancer cell lines. We show that the protection of data-inferred metabolic tasks decreases the variability of models across extraction methods. Furthermore, resulting models better capture the actual biological variability across cell lines. This study highlights the potential of using biological knowledge, inferred from omics data, to obtain a better consensus between existing extraction algorithms. It further provides guidelines for the development of the next-generation of data contextualization methods.
Tethered homing gene drives: A new design for spatially restricted population replacement and suppression

Optimism regarding potential epidemiological and conservation applications of modern gene drives is tempered by concern about the possibility of unintended spread of engineered organisms beyond the target population. In response, several novel gene drive approaches have been proposed that can, under certain conditions, locally alter characteristics of a population. One challenge for these gene drives is the difficulty of achieving high levels of localized population suppression without very large releases in the face of gene flow. We present a new gene drive system, tethered homing (TH), with improved capacity for both localization and population suppression. The TH drive is based on driving a payload gene using a homing construct that is anchored to a spatially restricted gene drive. We use a proof-of-concept mathematical model to show the dynamics of a TH drive that uses engineered underdominance as an anchor. This system is composed of a split homing drive and a two-locus engineered underdominance drive linked to one part of the split drive (the Cas endonuclease). We use simple population genetic simulations to show that the tethered homing technique can offer improved localized spread of costly transgenic payload genes. Additionally, the TH system offers the ability to gradually adjust the genetic load in a population after the initial alteration, with minimal additional release effort. We discuss potential solutions for improving localization and the feasibility of creating TH drive systems. Further research with models that include additional biological details will be needed to better understand how TH drives would behave in natural populations, but the preliminary results shown here suggest that tethered homing drives can be a useful addition to the repertoire of localized gene drives.
Unsaturation of ketones, nitriles and lactams with methyl phenylsulfinate

Abstract An improved synthesis of methyl phenylsulfinate 2 by treatment of diphenyl disulfide with bromine in the presence of methanol has been developed. Use of this reagent in the preparation of α,β-unsaturated ketones, nitriles and lactams is described.
High Helicities of Lys-Containing, Ala-Rich Peptides Are Primarily Attributable to a Large, Context-Dependent Lys Stabilization

Peptides 1K, YKGGGAAAAAAAAKAAAAAAAAAGGGK-NH2; 2K, YKGGGAAAAAKAAAAAKAAAAAAGGGK-NH2; and 3K, YKGGGAAAAKAAAAKAAAAKAAAGGGK-NH2 have been prepared by solid-phase synthesis, purified, and characterized by amino acid analysis, MALDI mass spectrometry, and ultracentrifugation. Their circular dichroism (CD) spectra of unaggregated solutions are reported for measurements in 0.01 M NaCl at 2, 25, and 60 °C and at 2 °C in aqueous guanidinium hydrochloride (0−3 M) and aqueous trifluoroethanol (TFE, 0−15 mol %). The CD spectra exhibit a helical signature in 0.01 M NaCl or in water−TFE at 2 °C, and the intensities of the mean residue ellipticities at the minimums of 222 nm in 0.01 M NaCl are (1K) −9100, (2K) −18 100, and (3K) −19 900 deg cm-1 dmol-1. These ellipticities are accurately modeled using a Lifson−Roig algorithm by the helical propensities previously reported by Renold et al. (Renold, P.; Tsang, K.-Y.; Shimizu, L. S.; Kemp, D. S. J. Am. Chem. Soc. 1996, 118, 12234−12235.) but not by those of Doig and Baldwin (...
State-aware detection of sensory stimuli in the cortex of the awake mouse

Cortical responses to sensory inputs vary across repeated presentations of identical stimuli, but how this trial-to-trial variability impacts detection of sensory inputs is not fully understood. Using multi-channel local field potential (LFP) recordings in primary somatosensory cortex (S1) of the awake mouse, we optimized a data-driven cortical state classifier to predict single-trial sensory-evoked responses, based on features of the spontaneous, ongoing LFP recorded across cortical layers. Our findings show that, by utilizing an ongoing prediction of the sensory response generated by this state classifier, an ideal observer improves overall detection accuracy and generates robust detection of sensory inputs across various states of ongoing cortical activity in the awake brain, which could have implications for variability in the performance of detection tasks across brain states.
Enantioselective organocatalytic Michael addition reactions between N-heterocycles and nitroolefins.

A method for Michael addition of N-heterocycles to nitroolefins has been developed. The process is promoted by a cinchona alkaloid derivative to give Michael adducts in moderate to high enantioselectivities.
Development of a multi-locus CRISPR gene drive system in budding yeast

The discovery of CRISPR/Cas gene editing has allowed for major advances in many biomedical disciplines and basic research. One arrangement of this biotechnology, a nuclease-based gene drive, can rapidly deliver a genetic element through a given population and studies in fungi and metazoans have demonstrated the success of such a system. This methodology has the potential to control biological populations and contribute to eradication of insect-borne diseases, agricultural pests, and invasive species. However, there remain challenges in the design, optimization, and implementation of gene drives including concerns regarding biosafety, containment, and control/inhibition. Given the numerous gene drive arrangements possible, there is a growing need for more advanced designs. In this study, we use budding yeast to develop an artificial multi-locus gene drive system. Our minimal setup requires only a single copy of S. pyogenes Cas9 and three guide RNAs to propagate three gene drives. We demonstrate how this system could be used for targeted allele replacement of native genes and to suppress NHEJ repair systems by modifying DNA Ligase IV. A multi-locus gene drive configuration provides an expanded suite of options for complex attributes including pathway redundancy, combatting evolved resistance, and safeguards for control, inhibition, or reversal of drive action.
Highly Stereoselective Syntheses of syn- and anti-1,2-Amino Alcohols

The reduction of N-protected amino ketones can be carried stereoselectively to produce either the syn- or anti-amino alcohol diastereomer. Carbamate-protected amino ketones can be reduced predictably and selectively to anti-amino alcohols with LiAlH(O-t-Bu)3 in ethanol at -78 degrees C. N-Trityl-protected amino ketones can be reduced selectively to syn-amino alcohols with LiAlH(O-t-Bu)3 in THF at -5 degrees C.
Synthesis of Methylene-Expanded 2‘,3‘-Dideoxyribonucleosides

A method for the preparation of methylene-expanded 2‘,3‘-dideoxyribonucleosides is reported. The very inexpensive starting material levoglucosenone 8 was converted into the known mixture of alcohols 12ab which were converted into the required silyl ether alcohol 26 in six steps via either of two routes. The first involved a one-step acetylation and opening of the anhydro sugar bridge to give the triacetates 20ab which were reduced with triethylsilane and silyl triflate to afford the diacetates 21ab, both of which gave 26 after further functional group conversions. The second route entailed a simple acetylation of 12ab followed by reduction with triethylsilane and silyl triflate to give the monoacetates 19ab, both converted via straightforward chemistry into 26. Mesylation of the alcohol of 26 furnished the mesylate 27. Alkylation of adenine with the mesylate 27 afforded the silyl ether 28 which was deprotected to give the desired modified dideoxy nucleoside 7a. Alkylation of 2,6-diaminopurine 38 with the ...
qwLSH: Cache-conscious Indexing for Processing Similarity Search Query Workloads in High-Dimensional Spaces

Similarity search queries in high-dimensional spaces are an important type of queries in many domains such as image processing, machine learning, etc. %Since exact similarity search indexing techniques suffer from the well-knowncurse of dimensionality in high-dimensional spaces, approximate search techniques are often utilized instead. Locality Sensitive Hashing (LSH) has been shown to be an effective approximate search method for solving similarity search queries in high-dimensional spaces. Often, queries in real-world settings arrive as part of a query workload. LSH and its variants are particularly designed to solve single queries effectively. They suffer from one major drawback while executing query workloads: they do not take into consideration important data characteristics for effective cache utilization while designing the index structures. In this paper, we presentqwLSH, an index structure %for efficiently processing similarity search query workloads in high-dimensional spaces. We that intelligently divides a given cache during processing of a query workload by using novel cost models. Experimental results show that, given a query workload,qwLSH is able to perform faster than existing techniques due to its unique cost models and strategies to reduce cache misses. %We further present different caching strategies for efficiently processing similarity search query workloads. We evaluate our proposed unique design and cost models ofqwLSH on real datasets against state-of-the-art LSH-based techniques.
aBayesQR: A Bayesian Method for Reconstruction of Viral Populations Characterized by Low Diversity.

RNA viruses replicate with high mutation rates, creating closely related viral populations. The heterogeneous virus populations, referred to as viral quasispecies, rapidly adapt to environmental changes thus adversely affecting efficiency of antiviral drugs and vaccines. Therefore, studying the underlying genetic heterogeneity of viral populations plays a significant role in the development of effective therapeutic treatments. Recent high-throughput sequencing technologies have provided invaluable opportunity for uncovering the structure of quasispecies populations. However, accurate reconstruction of viral quasispecies remains difficult due to limited read-lengths and presence of sequencing errors. The problem is particularly challenging when the strains in a population are highly similar, i.e., the sequences are characterized by low mutual genetic distances, and further exacerbated if some of those strains are relatively rare; this is the setting where state-of-the-art methods struggle. In this paper, we present a novel viral quasispecies reconstruction algorithm, aBayesQR, that employs a maximum-likelihood framework to infer individual sequences in a mixture from high-throughput sequencing data. The search for the most likely quasispecies is conducted on long contigs that our method constructs from the set of short reads via agglomerative hierarchical clustering; operating on contigs rather than short reads enables identification of close strains in a population and provides computational tractability of the Bayesian method. Results on both simulated and real HIV-1 data demonstrate that the proposed algorithm generally outperforms state-of-the-art methods; aBayesQR particularly stands out when reconstructing a set of closely related viral strains (e.g., quasispecies characterized by low diversity).
Tandem Histone-Binding Domains Enhance the Activity of a Synthetic Chromatin Effector.

Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than DNA sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. We have previously reported the development and validation of the “polycomb-based transcription factor” (PcTF), a fusion protein that recognizes histone modifications through a protein–protein interaction between its polycomb chromodomain (PCD) motif and trimethylated lysine 27 of histone H3 (H3K27me3) at genomic sites. We demonstrated that PcTF activates genes at methyl-histone-enriched loci in cancer-derived cell lines. However, PcTF induces modest activation of a methyl-histone associated reporter compared to a DNA-binding activator. Therefore, we modified PcTF to enha...
α,β-Differentiated tandem diamination of cinnamic esters using N,N-dichloro-2-nitrobenzenesulfonamide and acetonitrile as the nitrogen sources

Tandem diamination of cinnamic esters provides a new approach to anti alkyl Nα-(2-Ns), Nβ-Ac diaminophenylpropionates. The new reaction proceeds to completion within 3 hours at room temperature using N,N-dichloro-2-nitrobenzenesulfonamide (2-NsNCl2) as the nitrogen source in acetonitrile, which is also involved in the reaction process. Seven diamine derivatives have been obtained with good yields and stereoselectivity.
Organocatalytic anti‐Mannich Reactions with Dihydroxyacetone and Acyclic Dihydroxyacetone Derivatives: A Facile Route to Amino Sugars

The first primary amine-containing amino acid-catalyzed anti-Mannich reactions of dihydroxyacetone and acyclic dihydroxyacetone derivatives with a variety of imines have been developed. This approach complements proline-based strategies in the preparation of amino sugars.
Intermolecular Applications of o‐Quinone Methides (o‐QMs) Anionically Generated at Low Temperatures: Kinetic Conditions

There existmany fundamental andphilosophical truths in theuniverse.Among these is the notion that the value of an item is determined by its inherent characteristics and its surrounding environment. For example, a fishing pole near the sea is a useful tool, but when relocated to the desert its usefulness decreases. o-Quinone methides (o-QMs) are highly reactive species with short lifetimes because of the thermodynamic drive to undergo rearomatization. However, the above philosophical truth applies to these highly electrophilic intermediates. In the absence of stabilizing residues, these transient species prove so reactive that the setting in which they are produced dictates the range and scope of their subsequent application. Figure 4.1 shows some of the accepted canonical representation for o-QMs. These depictions should give readers some appreciation regarding the reactivity of o-QMs and impart some credence to the notion that the olefin geometry in an o-QM is fluxional, being determined by the energy difference between competing steric effects (R2 and R1) versus (R2 and O).
Copper-Catalyzed Negishi Coupling of Diarylzinc Reagents with Aryl Iodides

We report an efficient copper(I) iodide catalyzed cross-coupling­ of diarylzinc reagents with aryl iodides. The reaction proceeds under ligand-free conditions at low catalyst loading (5 mol%) and tolerates a variety of functional groups.
Synthetic Strategy toward γ-Keto Nitriles and Their Biocatalytic Conversion to Asymmetric γ-Lactones

Asymmetric γ-hydroxy nitriles are valuable intermediates because hydrolysis of the nitriles can result in an intramolecular cyclization to chiral γ-lactones, which have a variety of biological uses. Starting with an assortment of different aldehydes (alkyl and aryl) a 4-step synthesis of γ-keto nitriles was developed. These prochiral substrates were then screened against a library of ketoreductases for their ability to stereoselectively reduce the carbonyl. Enzymes from the short chain dehydrogenase family showed activity and these enzymatic reactions were scaled up to produce a diverse set of chiral γ-lactones.
Monte Carlo sampling bias in the microwave uncertainty framework

Uncertainty propagation software can have unknown, inadvertent biases introduced by various means. This work treats bias identification and reduction in one such software package, the microwave uncertainty framework (MUF). The MUF provides automated multivariate statistical uncertainty propagation and analysis on a Monte Carlo (MC) basis. is a key module in the MUF, responsible for merging data, raw or transformed, to accurately reflect the variability in the data and in its central tendency. In this work the performance of 's MC replicates is analytically compared against its stated design goals. An alternative construction is proposed for 's MC replicates and its performance is compared, too, against 's design goals. These comparisons reveal that 's MC uncertainty results with the current construction method are biased except under restrictive conditions. The bias with the proposed alternative construction, by contrast, is, without restriction, asymptotically zero (in the large MC sample size limit), and this construction is recommended.
PolyCRACKER, a robust method for the unsupervised partitioning of polyploid subgenomes by signatures of repetitive DNA evolution

Our understanding of polyploid genomes is limited by our inability to definitively assign sequences to a specific subgenome without extensive prior knowledge like high resolution genetic maps or genome sequences of diploid progenitors. In theory, existing methods for assigning sequences to individual species from metagenome samples could be used to separate subgenomes in polyploid organisms, however, these methods rely on differences in coarse genome properties like GC content or sequences from related species. Thus, these approaches do not work for subgenomes where gross features are indistinguishable and related genomes are lacking. Here we describe a method that uses rapidly evolving repetitive DNA to circumvent these limitations. By using short, repetitive, DNA sequences as species-specific signals we separated closely related genomes from test datasets and subgenomes from two polyploid plants, tobacco and wheat, without any prior knowledge. This approach is ideal for separating the subgenomes of polyploid species with unsequenced or unknown progenitor genomes.
Gamifying Security Awareness: A New Prototype.

Data breaches within an organization have many causes. Social engineering attacks, ransom-ware applications and harmful spam email messages are data breach catalysts that are the result of human error. Human error is the leading cause of data breach and is also one of the more difficult factors for an organization to mitigate. Many users are unable to see how their role is impacted by organizational security policy, and therefor see no benefit to abide the policy. When employees use company devices to perform personal tasks, or use personal devices to perform business tasks, lines of ownership can be blurred and important organizational data assets can be put at risk. Training and awareness programs are too often treated as a bandage to fix a wound inflicted by a breach after the fact. If employees were trained effectively, the breach might not have occurred in the first place. This project and accompanying research paper will explore the gamification of the security training and awareness program. By developing role-based game modules to teach secure behavior to all organizational users, incentivizing secure behavior with real rewards that matter to participants and applying the training throughout the year, it can be possible to reinvent security awareness and prevent future data breaches.
How wired are U.S. hospitals? A study of patient-oriented interactive tools

This study examined U.S. hospital websites to find out how they have used interactive tools to engage and serve their patients. The findings and recommendations from this study will provide guidanc...
A Unique Continuation Property for the Level Set Equation

We prove the following unique continuation result: if a solution to the level set equation for mean curvature flow in a mean-convex domain agrees to infinite order at the point where it attains its maximum with the solution for a ball, then it agrees everywhere and the domain is a ball.
On cellular algebras with Jucys Murphy elements

Abstract We study analogues of Jucys–Murphy elements in cellular algebras arising from repeated Jones basic constructions. Examples include Brauer and BMW algebras and their cyclotomic analogues.
Decoherence and quantum interference assisted electron trapping in a quantum dot

We present a theoretical model for the dynamics of an electron that gets trapped by means of decoherence and quantum interference in the central quantum dot (QD) of a semiconductor nanoring (NR) made of five QDs, between 100 and 300 K. The electron's dynamics is described by a master equation with a Hamiltonian based on the tight-binding model, taking into account electron–LO phonon interaction. Based on this configuration, the probability to trap an electron with no decoherence is almost 27%. In contrast, the probability to trap an electron with decoherence is 70% at 100 K, 63% at 200 K and 58% at 300 K. Our model provides a novel method of trapping an electron at room temperature.
On the second smallest prime non-residue

Abstract Let χ be a non-principal Dirichlet character modulo a prime p. Let q 1 q 2 denote the two smallest prime non-residues of χ. We give explicit upper bounds on q 2 that improve upon all known results. We also provide a good upper estimate on the product q 1 q 2 which has an upcoming application to the study of norm-Euclidean Galois fields.
Latency Aware Drone Base Station Placement in Heterogeneous Networks

Different from traditional static small cells, Drone Base Stations (DBSs) exhibit their own advantages, i.e., faster and cheaper to deploy, more flexibly reconfigured, and likely to have better communications channels owing to the presence of short-range line-of-sight links. Thus, applying DBSs into the cellular network has great potential to increase the throughput of the network and improve Quality of Service (QoS) of Mobile Users (MUs). In this paper, we focus on how to place the DBS (i.e., jointly determining the location and the association coverage of a DBS) in order to improve the QoS in terms of minimizing the total average latency ratio of MUs by considering the energy capacity limitation of the DBS. We formulate the DBS placement problem as an optimization problem and design a Latency aware dronE bAse station Placement (LEAP) algorithm to solve it efficiently. The performance of LEAP is demonstrated via simulations as compared to other two baseline methods.
Double-Diffusive Convection

Much progress has recently been made in understanding and quantifying vertical mixing induced by double-diffusive instabilities such as fingering convection (usually called thermohaline convection) and oscillatory double-diffusive convection (a process closely related to semiconvection). This was prompted in parts by advances in supercomputing, which allow us to run Direct Numerical Simulations of these processes at parameter values approaching those relevant in stellar interiors, and in parts by recent theoretical developments in oceanography where such instabilities also occur. In this paper I summarize these recent findings, and propose new mixing parametrizations for both processes that can easily be implemented in stellar evolution codes.
Data Clustering and Graph Partitioning via Simulated Mixing

Spectral clustering approaches have led to well-accepted algorithms for finding accurate clusters in a given dataset. However, their application to large-scale datasets has been hindered by the computational complexity of eigenvalue decompositions. Several algorithms have been proposed in the recent past to accelerate spectral clustering, however they compromise on the accuracy of the spectral clustering to achieve faster speed. In this paper, we propose a novel spectral clustering algorithm based on a mixing process on a graph. Unlike the existing spectral clustering algorithms, our algorithm does not require computing eigenvectors. Specifically, it finds the equivalent of a linear combination of eigenvectors of the normalized similarity matrix weighted with corresponding eigenvalues. This linear combination is then used to partition the dataset into meaningful clusters. Simulations on real datasets show that partitioning datasets based on such linear combinations of eigenvectors achieves better accuracy than standard spectral clustering methods as the number of clusters increase. Our algorithm can easily be implemented in a distributed setting.
Volumes of chain links

Agol has conjectured that minimally twisted n-chain links are the smallest volume hyperbolic manifolds with n cusps, for n ≤ 10. In his thesis, Venzke mentions that these cannot be smallest volume ...
The Generation of Warm Dense Matter Using a Magnetic Anvil Cell

Warm dense matter is present at the heart of gas giants and large exo-planets. Yet, its most basic properties are unknown, limiting our understanding of planetary formation and evolution. In this state, where pressure climbs above 1 Mbar, matter is strongly coupled and quantum degenerate. This combination invalidates most theories capable of predicting the equation of state, the viscosity, or heat conductivity of the material. When such properties are missing, understanding planetary evolution becomes an arduous endeavor. Henceforth, research in this field is actively growing, using high-power laser or heavy ion beams to produce samples dense enough to overcome the 1-Mbar limit. These samples are not actively confined and tend to expand rapidly, precluding the existence of any thermodynamically stable equilibrium. However, a mega-ampere-class pulsed-power generator can produce confined matter in the Mbar range, providing two conditions are being met. First, the sample needs to be compressed cylindrically, to maximize magnetic pressure (compared to slab compression). Second, an “electrical damper” must be used to limit the formation of a plasma at the sample surface. This corona robs the main sample from valuable current and limits the homogeneity of the compression. According to numerical simulations, the setup proposed here, called a magnetic anvil cell (MAC), can reach pressures on the order of 1 Mbar using a mega-ampere pulsed-power driver. These samples span several millimeters in length. Unlike diamond anvil cell, the MAC has virtually no pressure limit. Furthermore, the current heats the sample to several eV, a temperature well beyond the capabilities of diamond anvil cells.
Online and Distributed Robust Regressions Under Adversarial Data Corruption

In today's era of big data, robust least-squares regression becomes a more challenging problem when considering the adversarial corruption along with explosive growth of datasets. Traditional robust methods can handle the noise but suffer from several challenges when applied in huge dataset including 1) computational infeasibility of handling an entire dataset at once, 2) existence of heterogeneously distributed corruption, and 3) difficulty in corruption estimation when data cannot be entirely loaded. This paper proposes online and distributed robust regression approaches, both of which can concurrently address all the above challenges. Specifically, the distributed algorithm optimizes the regression coefficients of each data block via heuristic hard thresholding and combines all the estimates in a distributed robust consolidation. Furthermore, an online version of the distributed algorithm is proposed to incrementally update the existing estimates with new incoming data. We also prove that our algorithms benefit from strong robustness guarantees in terms of regression coefficient recovery with a constant upper bound on the error of state-of-the-art batch methods. Extensive experiments on synthetic and real datasets demonstrate that our approaches are superior to those of existing methods in effectiveness, with competitive efficiency.
Asynchronous Approximation of a Single Component of the Solution to a Linear System

We present a distributed asynchronous algorithm for approximating a single component of the solution to a system of linear equations $Ax = b$ , where $A$ is a positive definite real matrix and $b \in \mathbb {R}^n$ . This can equivalently be formulated as solving for $x_i$ in $x = Gx + z$ for some $G$ and $z$ such that the spectral radius of $G$ is less than 1. Our algorithm relies on the Neumann series characterization of the component $x_i$ , and is based on residual updates. We analyze our algorithm within the context of a cloud computation model motivated by frameworks, such as Apache Spark, in which the computation is split into small update tasks performed by small processors with shared access to a distributed file system. We prove a robust asymptotic convergence result when the spectral radius $\rho (|G|) , regardless of the precise order and frequency in which the update tasks are performed. We provide convergence rate bounds that depend on the order of update tasks performed, analyzing both deterministic update rules via counting weighted random walks, as well as probabilistic update rules via concentration bounds. The probabilistic analysis requires analyzing the product of random matrices that are drawn from distributions that are time and path dependent. We specifically consider the setting where $n$ is large, yet $G$ is sparse, e.g., each row has at most $d$ nonzero entries. This is motivated by applications in which $G$ is derived from the edge structure of an underlying graph. Our results prove that if the local neighborhood of the graph does not grow too quickly as a function of $n$ , our algorithm can provide significant reduction in computation cost as opposed to any algorithm that computes the global solution vector $x$ . Our algorithm obtains an $\epsilon \Vert x\Vert _2$ additive approximation for $x_i$ in constant time with respect to the size of the matrix when the maximum row sparsity $d = O(1)$ and $1/(1-\Vert G\Vert _2) = O(1)$ , where $\Vert G\Vert _2$ is the induced matrix operator 2-norm.
An Improved Multi-parametric Programming Algorithm for Flux Balance Analysis of Metabolic Networks

Flux balance analysis has proven an effective tool for analyzing metabolic networks. In flux balance analysis, reaction rates and optimal pathways are ascertained by solving a linear program, in which the growth rate is maximized subject to mass-balance constraints. A variety of cell functions in response to environmental stimuli can be quantified using flux balance analysis by parameterizing the linear program with respect to extracellular conditions. However, for most large, genome-scale metabolic networks of practical interest, the resulting parametric problem has multiple and highly degenerate optimal solutions, which are computationally challenging to handle. An improved multi-parametric programming algorithm based on active-set methods is introduced in this paper to overcome these computational difficulties. Degeneracy and multiplicity are handled, respectively, by introducing generalized inverses and auxiliary objective functions into the formulation of the optimality conditions. These improvements are especially effective for metabolic networks because their stoichiometry matrices are generally sparse; thus, fast and efficient algorithms from sparse linear algebra can be leveraged to compute generalized inverses and null-space bases. We illustrate the application of our algorithm to flux balance analysis of metabolic networks by studying a reduced metabolic model of Corynebacterium glutamicum and a genome-scale model of Escherichia coli. We then demonstrate how the critical regions resulting from these studies can be associated with optimal metabolic modes and discuss the physical relevance of optimal pathways arising from various auxiliary objective functions. Achieving more than fivefold improvement in computational speed over existing multi-parametric programming tools, the proposed algorithm proves promising in handling genome-scale metabolic models.
The Dehn–Sommerville relations and the Catalan matroid

The $f$-vector of a $d$-dimensional polytope $P$ stores the number of faces of each dimension. When $P$ is simplicial the Dehn--Sommerville relations condense the $f$-vector into the $g$-vector, which has length $\lceil{\frac{d+1}{2}}\rceil$. Thus, to determine the $f$-vector of $P$, we only need to know approximately half of its entries. This raises the question: Which $(\lceil{\frac{d+1}{2}}\rceil)$-subsets of the $f$-vector of a general simplicial polytope are sufficient to determine the whole $f$-vector? We prove that the answer is given by the bases of the Catalan matroid.
Implementing the Lexicographic Maxmin Bargaining Solution.

There has been much work on exhibiting mechanisms that implement various bargaining solutions, in particular, the Kalai-Smorodinsky solution \cite{moulin1984implementing} and the Nash Bargaining solution. Another well-known and axiomatically well-studied solution is the lexicographic maxmin solution. However, there is no mechanism known for its implementation. To fill this gap, we construct a mechanism that implements the lexicographic maxmin solution as the unique subgame perfect equilibrium outcome in the n-player setting. As is standard in the literature on implementation of bargaining solutions, we use the assumption that any player can grab the entire surplus. Our mechanism consists of a binary game tree, with each node corresponding to a subgame where the players are allowed to choose between two outcomes. We characterize novel combinatorial properties of the lexicographic maxmin solution which are crucial to the design of our mechanism.
Contingency-Constrained Unit Commitment With Intervening Time for System Adjustments

The $N$ -1-1 contingency reliability criterion considers the consecutive loss of two components in a power system, with intervening time for system adjustments between the two losses. In this paper, we consider the problem of optimizing generation unit while ensuring the $N$ -1-1 criterion. Due to the coupling of time periods associated with consecutive component losses, the resulting problem yields a very large-scale mixed-integer linear optimization model. For efficient solution, we introduce a novel branch-and-cut algorithm using a temporally decomposed bilevel separation oracle. The model and algorithm are assessed using multiple IEEE test systems, and a comprehensive analysis is performed to compare system performance across different contingency criteria. Computational results demonstrate the value of considering intervening time for system adjustments in terms of total cost and system robustness.
Classical Verification of Quantum Computations

We present the first protocol allowing a classical computer to interactively verify the result of an efficient quantum computation. We achieve this by constructing a measurement protocol, which enables a classical verifier to use a quantum prover as a trusted measurement device. The protocol forces the prover to behave as follows: the prover must construct an n qubit state of his choice, measure each qubit in the Hadamard or standard basis as directed by the verifier, and report the measurement results to the verifier. The soundness of this protocol is enforced based on the assumption that the learning with errors problem is computationally intractable for efficient quantum machines.