cssi/SciSciGPT-SciSciNet huggingface dataset:
Adversarial Decomposition of Text Representation

In this paper, we present a method for adversarial decomposition of text representation. This method can be used to decompose a representation of an input sentence into several independent vectors, each of them responsible for a specific aspect of the input sentence. We evaluate the proposed method on two case studies: the conversion between different social registers and diachronic language change. We show that the proposed method is capable of fine-grained controlled change of these aspects of the input sentence. It is also learning a continuous (rather than categorical) representation of the style of the sentence, which is more linguistically realistic. The model uses adversarial-motivational training and includes a special motivational loss, which acts opposite to the discriminator and encourages a better decomposition. Furthermore, we evaluate the obtained meaning embeddings on a downstream task of paraphrase detection and show that they significantly outperform the embeddings of a regular autoencoder.
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning

We identify two issues with the family of algorithms based on the Adversarial Imitation Learning framework. The first problem is implicit bias present in the reward functions used in these algorithms. While these biases might work well for some environments, they can also lead to sub-optimal behavior in others. Secondly, even though these algorithms can learn from few expert demonstrations, they require a prohibitively large number of interactions with the environment in order to imitate the expert for many real-world applications. In order to address these issues, we propose a new algorithm called Discriminator-Actor-Critic that uses off-policy Reinforcement Learning to reduce policy-environment interaction sample complexity by an average factor of 10. Furthermore, since our reward function is designed to be unbiased, we can apply our algorithm to many problems without making any task-specific adjustments.
Defining far transfer via thematic similarity

One of the most valuable functions of philosophy within the cognitive sciences and education is to help clarify important concepts, and the transfer of learning—particularly far transfer—is one suc...
Subcubic Equivalences Between Path, Matrix, and Triangle Problems

We say an algorithm on n × n matrices with integer entries in l−M,Mr (or n-node graphs with edge weights from l−M,M]) is truly subcubic if it runs in O(n3 − δ c poly(log M)) time for some δ > 0. We define a notion of subcubic reducibility and show that many important problems on graphs and matrices solvable in O(n3) time are equivalent under subcubic reductions. Namely, the following weighted problems either all have truly subcubic algorithms, or none of them do:•The all-pairs shortest paths problem on weighted digraphs (APSP).•Detecting if a weighted graph has a triangle of negative total edge weight.•Listing up to n2.99 negative triangles in an edge-weighted graph.•Finding a minimum weight cycle in a graph of non-negative edge weights.•The replacement paths problem on weighted digraphs.•Finding the second shortest simple path between two nodes in a weighted digraph.•Checking whether a given matrix defines a metric.•Verifying the correctness of a matrix product over the (min, +)-semiring.•Finding a maximum subarray in a given matrix.Therefore, if APSP cannot be solved in n3−e time for any e > 0, then many other problems also need essentially cubic time. In fact, we show generic equivalences between matrix products over a large class of algebraic structures used in optimization, verifying a matrix product over the same structure, and corresponding triangle detection problems over the structure. These equivalences simplify prior work on subcubic algorithms for all-pairs path problems, since it now suffices to give appropriate subcubic triangle detection algorithms.Other consequences of our work are new combinatorial approaches to Boolean matrix multiplication over the (OR,AND)-semiring (abbreviated as BMM). We show that practical advances in triangle detection would imply practical BMM algorithms, among other results. Building on our techniques, we give two improved BMM algorithms: a derandomization of the combinatorial BMM algorithm of Bansal and Williams (FOCS’09), and an improved quantum algorithm for BMM.
Kinship, Cooperation, and the Evolution of Moral Systems

Across the social sciences, a key question is how societies manage to enforce cooperative behavior in social dilemmas such as public goods provision or bilateral trade. According to an influential body of theories in psychology, anthropology, and evolutionary biology, the answer is that humans have evolved moral systems: packages of functional psychological and biological mechanisms that regulate economic behavior, including a belief in moralizing gods; moral values; negative reciprocity; and emotions of shame, guilt, and disgust. Based on a stylized model, this article empirically studies the structure and evolution of these moral traits as a function of historical heterogeneity in extended kinship relationships. The evidence shows that societies with a historically tightly knit kinship structure regulate behavior through communal moral values, revenge taking, emotions of external shame, and notions of purity and disgust. In loose kinship societies, on the other hand, cooperation appears to be enforced through universal moral values, internalized guilt, altruistic punishment, and an apparent rise and fall of moralizing religions. These patterns point to the presence of internally consistent but culturally variable functional moral systems. Consistent with the model, the relationship between kinship ties, economic development, and the structure of the mediating moral systems amplified over time.
Structural organization of a Type III-A CRISPR effector subcomplex determined by X-ray crystallography and cryo-EM.

Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated Cas proteins provide an immune-like response in many prokaryotes against extraneous nucleic acids. CRISPR-Cas systems are classified into different classes and types. Class 1 CRISPR-Cas systems form multi-protein effector complexes that includes a guide RNA (crRNA) used to identify the target for destruction. Here we present crystal structures of Staphylococcus epidermidis Type III-A CRISPR subunits Csm2 and Csm3 and a 5.2 A resolution single-particle cryo-electron microscopy (cryo-EM) reconstruction of an in vivo assembled effector subcomplex including the crRNA. The structures help to clarify the quaternary architecture of Type III-A effector complexes, and provide details on crRNA binding, target RNA binding and cleavage, and intermolecular interactions essential for effector complex assembly. The structures allow a better understanding of the organization of Type III-A CRISPR effector complexes as well as highlighting the overall similarities and differences with other Class 1 effector complexes.
Valuing the risk of workplace sexual harassment

Using data on sexual harassment charges filed with the Equal Employment Opportunity Commission, I calculate the risk of sexual harassment by gender, industry, and age and establish that white females, but not nonwhite females, receive a compensating wage differential for exposure to a higher risk of sexual harassment. I use this risk premium to calculate the value of statistical harassment (VSH) in a manner analogous to the calculation of the value of statistical life (VSL). The VSH is around $7.6 million, about three-quarters of the size of the most-commonly cited levels of the VSL, and far above the maximum damages award for sexual harassment available under federal law. Boosting the maximum damages award to equal the VSH would create the appropriate economic incentives for organizations to deter sexual harassment.
Statistics of Lasing Peaks and ASE Spikes from Amplifying Random Media

We studied experimentally the ensemble-averaged spectral correlation functions and statistical distributions of spectral spacing and intensity of ASE spikes and lasing peaks from weakly scattering systems under local pumping. Their differences revealed distinct physical mechanisms.
Finding fault: Criticism as a care management strategy and its impact on outcomes for dementia caregivers

BACKGROUND Despite a large literature on the stress process, little attention has focused on how caregivers for persons living with dementia (PLWDs) provide care and how this may impact care outcomes. Criticism is a management strategy caregivers may use to respond to behavioral symptoms. We consider whether criticism is associated with caregivers' mental health and service utilization. METHODS Data are drawn from the Advancing Caregiver Training intervention study including 256 informal caregivers living with a PLWD. In multiple linear regressions controlling for caregivers' demographics and PLWDs' clinical factors, we consider criticism (criticism subscale of the Dementia Management Strategies Scale) as a predictor of caregiver burden, depressive symptoms, desire to institutionalize the PLWD, level of frustration with care, and the number of home-based, social, and health services utilized. RESULTS On average, 15% of the sample sometimes reported using criticism as a management strategy to manage the challenges of care. Greater use of criticism was associated with significantly more caregiver burden (β = 0.26, P < 0.001) and frustration with caregiving (β = 0.66, P < 0.001), but not depressive symptoms or a desire to institutionalize the PLWD. Criticism was also associated with significantly greater utilization of home-based (β = 0.14, P < 0.05) and social services (β = 0.15, P < 0.05), but not health care services. CONCLUSION Criticism appears to be used by more burdened and frustrated caregivers. The association of criticism with social and home-based services potentially reflects a need for greater support among this group of caregivers. Behavioral interventions that can help caregivers manage behavioral symptoms with positive, empirically validated strategies may be helpful.
Estimation of Design Parameters of Single-Phase Distribution Transformers from Terminal Measurements

In this paper a novel method is proposed for the estimation of the design parameters of single-phase distribution transformers us-ing data acquired from terminal measurements along with name-plate data and external tank dimensions. Transformer parame-ters that can be measured from terminals, e.g. leakage induct-ance, saturation inductance, winding resistance, are considered first. These parameters are analytically correlated with the geometrical information of the transformer structure. A system of non-linear equations is derived accordingly. Winding dimensions and the number of turns are computed with acceptable engineer-ing accuracy. The core dimensions (including its cross sectional area) are calculated using winding information. The obtained data can be utilized to develop white- or gray-box models to be used in the investigation of the thermal and/or electromagnetic behavior of power transformers as presented in several research studies published to date. Examples on laboratory and utility-grade transformers are shown for illustration and validation of the proposed design parameter estimation method.
Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches

Risk stratification (characterization) of tumors from radiology images can be more accurate and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such tools can also enable non-invasive cancer staging, prognosis, and foster personalized treatment planning as a part of precision medicine. In this papet, we propose both supervised and unsupervised machine learning strategies to improve tumor characterization. Our first approach is based on supervised learning for which we demonstrate significant gains with deep learning algorithms, particularly by utilizing a 3D convolutional neural network and transfer learning. Motivated by the radiologists’ interpretations of the scans, we then show how to incorporate task-dependent feature representations into a CAD system via a graph-regularized sparse multi-task learning framework. In the second approach , we explore an unsupervised learning algorithm to address the limited availability of labeled training data, a common problem in medical imaging applications. Inspired by learning from label proportion approaches in computer vision, we propose to use proportion-support vector machine for characterizing tumors. We also seek the answer to the fundamental question about the goodness of “deep features” for unsupervised tumor classification. We evaluate our proposed supervised and unsupervised learning algorithms on two different tumor diagnosis challenges: lung and pancreas with 1018 CT and 171 MRI scans, respectively, and obtain the state-of-the-art sensitivity and specificity results in both problems.
There and Back: Vindicating the Listener’s Interests in Targeted Advertising in the Internet Information Economy

This Note argues first, that the Commercial Speech Doctrine as currently conceived is an ill-fitting tool for resolving difficult free speech questions in the context of data, privacy, and the modern Internet Information Economy. The application of the Commercial Speech Doctrine to a particular economic interaction should not be a nigh-complete bar to the regulation of Internet platforms that profit from data collection and transmission. For this reason, qualified constitutional protection appropriately accounts for the speaker’s interests while not short-changing those of the listener/consumer. This Note proposes that regulators and reviewing tribunals consider the context surrounding the data collection and transmission process, including: method of collection, relationship between miner and mined party, and whether the user has consented to such collection in justifying the relative need for regulation. Second, in order to vindicate the Commercial Speech Doctrine’s initial purposes, more transparency of data collection procedures for use in targeted advertising is warranted and indeed possible as a regulatory hook to protect consumers, despite the Court’s move towards according more protection to commercial speakers. In so doing, this Note builds upon Erin Bernstein and Theresa J. Lee’s Where the Consumer Is the Commodity: The Difficulty with the Current Definition of Commercial Speech, which proposes that the “rise of new non-linear commercial transactions” necessitates a shift in the definition of commercial speech to accommodate the seismic change in the modern online economy. The stakes are not inconsequential: failure to expand the scope of commercial speech would foreclose the use of many tools in a legislature’s arsenal to address current concerns related to consumer privacy and eliminating advertisements that seek to capitalize on discriminatory indicia, among other salient policy issues. Part I details the Court’s jurisprudence regarding both personal solicitations and data practices and considers the shift away from a bifurcated speech paradigm that treats commercial speech as speech of “lesser value.” Part II illustrates the most common forms of data collection and transmission. Part III locates these methods of data collection and transmission within the current commercial speech framework to conclude that qualified constitutional protection is the coherent tier of scrutiny that should apply. Part IV proposes policy recommendations that fit within the Court’s current approach to commercial speech and alternatives that would require a departure from the present doctrine.
On upper bounding Shannon capacity of graph through generalized conic programming

The Shannon capacity of a graph is an important graph invariant in information theory that is extremely difficult to compute. The Lovasz number, which is based on semidefinite programming relaxation, is a well-known upper bound for the Shannon capacity. To improve this upper bound, previous research tried to generalize the Lovasz number using the ideas from the sum-of-squares optimization. In this paper, we consider the possibility of developing general conic programming upper bounds for the Shannon capacity, which include the previous attempts as special cases, and show that it is impossible to find better upper bounds for the Shannon capacity along this way.
Goal-setting And Achievement In Activity Tracking Apps: A Case Study Of MyFitnessPal

Activity tracking apps often make use of goals as one of their core motivational tools. There are two critical components to this tool: setting a goal, and subsequently achieving that goal. Despite its crucial role in how a number of prominent self-tracking apps function, there has been relatively little investigation of the goal-setting and achievement aspects of self-tracking apps. Here we explore this issue, investigating a particular goal setting and achievement process that is extensive, recorded, and crucial for both the app and its users' success: weight loss goals in MyFitnessPal. We present a large-scale study of 1.4 million users and weight loss goals, allowing for an unprecedented detailed view of how people set and achieve their goals. We find that, even for difficult long-term goals, behavior within the first 7 days predicts those who ultimately achieve their goals, that is, those who lose at least as much weight as they set out to, and those who do not. For instance, high amounts of early weight loss, which some researchers have classified as unsustainable, leads to higher goal achievement rates. We also show that early food intake, self-monitoring motivation, and attitude towards the goal are important factors. We then show that we can use our findings to predict goal achievement with an accuracy of 79% ROC AUC just 7 days after a goal is set. Finally, we discuss how our findings could inform steps to improve goal achievement in self-tracking apps.
The OH (1720 MHz) Supernova Remnant Masers in W28: MERLIN and VLBA Polarization Observations

Full-polarization MERLIN and VLBA observations of the 1720 MHz maser emission from the OH molecule in the supernova remnant W28 are presented. Zeeman splitting (|| ? 0.75 mG) has been directly resolved between right- and left-circularly polarized spectra for the first time. Linear polarization position angles and circular polarization Zeeman splitting observed in the maser emission permit interpretation of a comprehensive picture of the magnetic field at the supernova/molecular cloud interface marked by the masers. We find the post-SNR shock magnetic field to be well ordered over the ~1 pc covered by the maser region (compared with the approximately 30 pc diameter of the entire SNR) and well aligned with the shock front that is traced by synchrotron radiation and molecular emission. Based on MERLIN data having a resolution of 200 mas and VLBA data with a resolution of 15 mas, the masers are measured to have deconvolved angular sizes of 90-350 mas (225-875 AU) with compact cores 20 mas (50 AU) in size, consistent with theoretical expectation and previous observations.
Large-scale uniform optical focus array generation with a phase spatial light modulator

In this Letter, to the best of our knowledge, we report a new method to generate uniform large-scale optical focus arrays (LOFAs). By identifying and removing undesired phase rotation in the iterative Fourier transform algorithm (IFTA), our approach rapidly produces computer-generated holograms of highly uniform LOFAs. The new algorithm also shows a faster compensation of system-induced LOFA intensity inhomogeneity than the conventional IFTA. After only three adaptive correction steps, we demonstrate LOFAs consisting of O(103) optical foci with an intensity uniformity greater than 98%.
Exact Solution of the Six-Vertex Model with Domain Wall Boundary Conditions: Antiferroelectric Phase

We obtain the large-n asymptotics of the partition function Zn of the six-vertex model with domain wall boundary conditions in the antiferroelectric phase region, with the weights a = sinh(γ − t), b = sinh(γ + t), c = sinh(2γ), |t| < γ. We prove the conjecture of Zinn-Justin, that as n → ∞, Zn = Cϑ4(nω)F [1 + O(n−1)], where ω and F are given by explicit expressions in γ and t, and ϑ4(z) is the Jacobi theta function. The proof is based on the Riemann-Hilbert approach to the large-n asymptotic expansion of the underlying discrete orthogonal polynomials and on the Deift-Zhou nonlinear steepest-descent method. © 2009 Wiley Periodicals, Inc.
Photoreceptor metabolic reprogramming provides survival advantage in acute stress while causing chronic degeneration

Photoreceptor death is the root cause of vision loss in many retinal disorders, and there is an unmet need for neuroprotective modalities to improve photoreceptor survival. The biosynthetic requirement of photoreceptors is among the highest in the body, and to meet this demand, photoreceptors maintain their ability to perform aerobic glycolysis. This highly regulated form of glycolysis allows cells to efficiently budget their metabolic needs and may be a critical link between photoreceptor function and survival. Pyruvate kinase muscle isozyme 2 (PKM2) is a key regulator of aerobic glycolysis. In the present study, we characterized the effect of PKM2 deletion on baseline functioning and survival of photoreceptors over time by utilizing a photoreceptor-specific, PKM2 knockout mouse model. We found that upon PKM2 deletion, PKM1 is upregulated in the outer retina and there is increased expression of genes involved in glucose metabolism, which led to chronic degenerative changes in the outer retina of these mice. We also discovered that this metabolic reprogramming provided a survival advantage to photoreceptors in an experimental model of retinal detachment. This study strongly supports the hypothesis that reprogramming metabolism may be a novel therapeutic strategy for photoreceptor neuroprotection during acute stress.
PHDP: Preserving Persistent Homology in Differentially Private Graph Publications

Online social networks (OSNs) routinely share and analyze user data. This requires protection of sensitive user information. Researchers have proposed several techniques to anonymize the data of OSNs. Some differential-privacy techniques claim to preserve graph utility under certain graph metrics, as well as guarantee strict privacy. However, each graph utility metric reveals the whole graph in specific aspects.We employ persistent homology to give a comprehensive description of the graph utility in OSNs. This paper proposes a novel anonymization scheme, called PHDP, which preserves persistent homology and satisfies differential privacy. To strengthen privacy protection, we add exponential noise to the adjacency matrix of the network and find the number of adding/deleting edges. To maintain persistent homology, we collect edges along persistent structures and avoid perturbation on these edges. Our regeneration algorithms balance persistent homology with differential privacy, publishing an anonymized graph with a guarantee of both. Evaluation result show that the PHDP-anonymized graph achieves high graph utility, both in graph metrics and application metrics.
What the odor is not: Estimation by elimination

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.
Development status and decision-making in investment treaty arbitration

Abstract In this paper, I reproduce, replicate and extend two representative empirical studies that examine biases against developing states in investment treaty arbitration and arrive at contradictory conclusions. I find no evidence of biases against developing states using the same datasets and estimation strategies as the original studies. I find similar results when using alternative estimation strategies in the replication. However, when I change to a larger and more up-to-date dataset in the extension, I start to find consistent negative correlations between respondent states’ development status and their likelihood of losing. The results remain robust after I take into account confounding factors that could be correlated with unobserved case strength, and use the Heckman probit selection model to correct for potential selection bias caused by settlement. The patterns indicate that there may exist biases against developing states in investment treaty arbitration.
Learning the Depths of Moving People by Watching Frozen People

We present a method for predicting dense depth in scenarios where both a monocular camera and people in the scene are freely moving. Existing methods for recovering depth for dynamic, non-rigid objects from monocular video impose strong assumptions on the objects’ motion and may only recover sparse depth. In this paper, we take a data-driven approach and learn human depth priors from a new source of data: thousands of Internet videos of people imitating mannequins, i.e., freezing in diverse, natural poses, while a hand-held camera tours the scene. Since the people are stationary, training data can be created from these videos using multi-view stereo reconstruction. At inference time, our method uses motion parallax cues from the static areas of the scenes, and shows clear improvement over state-of-the-art monocular depth prediction methods. We demonstrate our method on real-world sequences of complex human actions captured by a moving hand-held camera, and show various 3D effects produced using our predicted depth.
The Mechanical Power of Titin Folding

The delivery of mechanical power, a crucial component of animal motion, is constrained by the universal compromise between the force and the velocity of its constituent molecular systems. While the mechanisms of force generation have been studied at the single molecular motor level, there is little understanding of the magnitude of power that can be generated by folding proteins. Here, we use single-molecule force spectroscopy techniques to measure the force-velocity relation of folding titin domains that contain single internal disulfide bonds, a common feature throughout the titin I-band. We find that formation of the disulfide regulates the peak power output of protein folding in an all-or-none manner, providing at 6.0 pN, for example, a boost from 0 to 6,000 zW upon oxidation. This mechanism of power generation from protein folding is of great importance for muscle, where titin domains may unfold and refold with each extension and contraction of the sarcomere.
Benzotriazole mediated syntheses of α-fluoro-β-amino esters

Abstract Mono- and difluoro-β-amino esters were synthesized via Reformatsky reaction of fluorinated ethyl bromoacetates with N-(α-aminoalkyl)benzotriazoles. Secondary and tertiary amines are easily formed, but primary amines can only be made in the difluorinated case. This approach has led to the first synthesis of di- and tetrafluorinated bis(β-amino esters).
Correlated evolution of self and interspecific incompatibility across the range of a Texas wildflower.

Selection to prevent interspecific mating can cause an increase or a decrease in self-pollination in sympatric populations. Characterizing the geographical variation in self and interspecific incompatibilities within a species can reveal if and how the evolution of self and interspecific mate choice are linked. We used controlled pollinations to characterize the variation in self and interspecific incompatibility across 29 populations of Phlox drummondii. We evaluated seed set from these pollinations and described the developmental timing of variation in pollen-pistil compatibility. There is extensive quantitative variation in self-incompatibility and interspecific-incompatibility with its close congener P. cuspidata. Phlox drummondii populations that co-occur and hybridize with P. cuspidata have significantly higher interspecific incompatibility and self-incompatibility than geographically isolated P. drummondii populations. The strength of self and interspecific incompatibility is significantly correlated among individuals and the strength of both incompatibilities is explained by the success of pollen adhesion to the stigma. The correlated strength of self and interspecific incompatibility across the range of P. drummondii and the concurrent developmental timing of the pollen-pistil interaction, suggests these incompatibilities have an overlapping molecular mechanism. The geographical distribution of variation in incompatibilities indicates that this mechanistic link between incompatibilities may affect the evolution of mate choice in plants.
Synthesis of functionalized cyclic boronates.

Deprotonation of a simple borylated allylic sulfone and subsequent alkylation with certain unsaturated electrophiles provide substrates that are easily converted into functionalized alkenyl boronates with ring sizes from five- to seven-membered. A Chan–Lam reaction on one such substrate afforded an alkoxyallylic sulfone that was readily converted via a (4 + 3)-cycloaddition to a polycycle possessing the ABC ring substructure of ingenol.
About 1-triphenylmethyl-3-tert-butylaziridinone and some of its reactions†

A high-yield synthesis of 1-triphenylmethyl-3-tert-butylaziridinone (4), its physical and spectral properties, the limits of its thermal stability, and reactions with methanol, benzylamine and sodium methoxide in methanol are described.
INHIBITORS OF DIHYDROFOLATE REDUCTASE : DESIGN, SYNTHESIS AND ANTIMICROBIAL ACTIVITIES OF 2,4-DIAMINO-6-METHYL-5-ETHYNYLPYRIMIDINES

Novel 2,4-diamino-6-methyl-5-ethynylpyrimidines were prepared via palladium catalyzed coupling of 2,4-diamino-5-iodo-6-methyl-pyrimidine with terminal acetylenes. The compounds were inhibitors of dihydrofolate reductase and showed in vitro activity against several species of opportunistic fungi and the protozoan Toxoplasma gondii.
Structure−Property Relationships in Dendritic Encapsulation

Several molecular structure−property relationships are presented and compared to illustrate our current understanding of macromolecular encapsulation using dendrimers. Specifically, the effect that dendrimer architectures have on encapsulating photoactive and redox-active units fixed at the molecular core is considered.
Rearrangement reactions of aziridinylbenzaldoximes

Reactions of 2,2-dimethylaziridine with benzohydroximoyl chlorides [ArC(Cl)NOH] give aziridinylbenzaldoximes 1. It has been found that the aziridine ring in these compounds undergoes ring opening in hydrogen chloride-dioxane solution to give (Z)-N-hydroxy-N′-(2-chloro-2-methylpropyl)benzenecarboximidamides [ArC(NHCH2CR1R2Cl)NOH, 4]. Treatment of 1 with hydrochloric acid followed by neutralization with aqueous sodium hydroxide gave 6,6-dimethyl-3-aryl-1,2,4-oxadiazines 2. Reaction of 4 with sodium hydride in dioxane gave 5-isopropyl-3-aryl-4,5-dihydro-1,2,4-oxadiazoles 5. Reaction of the 4,5-dihydro-1,2,4-oxadiazoles 5 with N-chlorosuccinimide gave the heteroaromatic 1,2,4-oxadiazoles 6. It is suggested that reactions of 4 with sodium hydride in dioxane solution involve the conjugate base of 4 which undergoes a 1,2-hydride shift that is concerted with loss of chloride ion. In aqueous sodium hydroxide solution it is suggested that the conjugate base of 4 undergoes ionization of the chlorine atom followed by nucleophilic attack by the oximate anion.
Pt(IV)-catalyzed cyclization of arene–alkyne substrates via C–H bond functionalization

Abstract We herein report that PtCl 4 has proven to be a hydroarylation catalyst with an efficiency and substrate scope superior to previously known methods. This catalyst demonstrated consistent performance with arene–yne substrates of diverse structural features, including propargyl ethers, propargylamines, and alkynoate esters, providing good to excellent yields of the 6- endo products (chromenes, dihydroquinolines, and coumarins). In contrast, Pt(II), Pd(II), and Ga(III) salts were shown to be sensitive to the substitution on the alkyne moiety. PtCl 4 is compatible with both terminal and disubstituted alkynes, as well as with various functionalities on the arene ring, including methyl, methoxyl, hydroxyl, protected amine, and halide.
Learning and Imputation for Mass-spec Bias Reduction (LIMBR).

MOTIVATION Decreasing costs are making it feasible to perform time series proteomics and genomics experiments with more replicates and higher resolution than ever before. With more replicates and time points, proteome and genome-wide patterns of expression are more readily discernible. These larger experiments require more batches exacerbating batch effects and increasing the number of bias trends. In the case of proteomics, where methods frequently result in missing data this increasing scale is also decreasing the number of peptides observed in all samples. The sources of batch effects and missing data are incompletely understood necessitating novel techniques. RESULTS Here we show that by exploiting the structure of time series experiments, it is possible to accurately and reproducibly model and remove batch effects. We implement Learning and Imputation for Mass-spec Bias Reduction (LIMBR) software, which builds on previous block-based models of batch effects and includes features specific to time series and circadian studies. To aid in the analysis of time series proteomics experiments, which are often plagued with missing data points, we also integrate an imputation system. By building LIMBR for imputation and time series tailored bias modeling into one straightforward software package, we expect that the quality and ease of large-scale proteomics and genomics time series experiments will be significantly increased. AVAILABILITY AND IMPLEMENTATION Python code and documentation is available for download at https://github.com/aleccrowell/LIMBR and LIMBR can be downloaded and installed with dependencies using 'pip install limbr'. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Communication pathways between the nucleotide pocket and distal regulatory sites in protein kinases.

Protein kinases control many cellular processes via the ATP-dependent phosphorylation of specific amino acids on target proteins. Despite the availability of the three-dimensional structures of a variety of protein kinases, it has been particularly difficult to explain how noncatalytic domains removed from the active site regulate catalytic function. In this review, we describe how solution methodologies complement the available structural data and help explain how protein kinases may utilize medium-to-long-range effects to regulate substrate phosphorylation. For illustration, two protein kinases, cAMP-dependent protein kinase and the C-terminal Src kinase, are presented as paradigms for the serine/threonine- and tyrosine-specific families. While active-site residues provide an optimal environment for fast phosphoryl group transfer in these and other kinases, the overall rate of protein phosphorylation is limited by nucleotide binding and associated structural changes. Hydrogen−deuterium exchange studies ...
How Obstacles Perturb Population Fronts and Alter Their Genetic Structure.

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle’s shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call ‘geometry-enhanced genetic drift’, complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles.
Synthesis of 1,1-bis-phosphorus compounds from organoboranes

Abstract The facile synthesis of various P–C–P compounds is described, based on the reaction of phosphorus carbenoids with organoboranes, followed by reaction with phosphorus electrophiles. Using this approach, symmetrically and differentially substituted 1,1-bisphosphorus compounds can be obtained in good yields. A number of novel P–C–P motifs are described for the first time.
Exact Time Evolution of the Asymmetric Hubbard Dimer

We examine the time evolution of an asymmetric Hubbard dimer, which has a different on-site interaction on the two sites. The Hamiltonian has a time-dependent hopping term, which can be employed to describe an electric field (which creates a Hamiltonian with complex matrix elements), or it can describe a modulation of the lattice (which has real matrix elements). By examining the symmetries under spin and pseudospin, we show that the former case involves at most a 3 × 3 block—it can be mapped onto the time evolution of a time-independent Hamiltonian, so the dynamics can be evaluated analytically and exactly (by solving a nontrivial cubic equation). We also show that the latter case reduces to at most 2 × 2 blocks, and hence, the time evolution for a single Trotter step can be determined exactly, but the time evolution generically requires a Trotter product.
A mixture copula Bayesian network model for multimodal genomic data

Gaussian Bayesian networks have become a widely used framework to estimate directed associations between joint Gaussian variables, where the network structure encodes the decomposition of multivariate normal density into local terms. However, the resulting estimates can be inaccurate when the normality assumption is moderately or severely violated, making it unsuitable for dealing with recent genomic data such as the Cancer Genome Atlas data. In the present paper, we propose a mixture copula Bayesian network model which provides great flexibility in modeling non-Gaussian and multimodal data for causal inference. The parameters in mixture copula functions can be efficiently estimated by a routine expectation–maximization algorithm. A heuristic search algorithm based on Bayesian information criterion is developed to estimate the network structure, and prediction can be further improved by the best-scoring network out of multiple predictions from random initial values. Our method outperforms Gaussian Bayesian networks and regular copula Bayesian networks in terms of modeling flexibility and prediction accuracy, as demonstrated using a cell signaling data set. We apply the proposed methods to the Cancer Genome Atlas data to study the genetic and epigenetic pathways that underlie serous ovarian cancer.
Formation of vicinal tricarbonyl compounds by selective oxidation of ylides using potassium peroxymonosulfate

Abstract Potassium peroxymonosulfate (commercially available as Oxone® = 2KHSO5·KHSO4&·K2SO4) oxidatively cleaves substituted ylides to afford products containing vicinal tricarbonyl groups.
Chemical effects of radical vibrational energy content on the abstraction reaction: CF3+Br2→CF3Br+Br

We have the effect of vibrational mode activation in the CF 3 radical on the bromine abstraction reaction; CF 3 +Br 2 →CF 3 Br+Br. Excess vibrational energy resides in the symmetric modes of the radical after 248 nm photolysis of the parent molecule, CF 3 I. Our data indicate that the hot radicals react no faster than thermalized CF 3 , and may actually have a lower cross-section for reaction. Dynamical factors that result in poor coupling of the vibrational energy to the reaction coordinate, as well as other similar considerations, could be responsible for the experimental observations. In addition, we have made an independent determination of the rate for the bromine abstraction reaction of (1.08±.13)×10 12 s −1 cm 3 mol −1
Most calbindin-immunoreactive neurons, but few calretinin-immunoreactive neurons, express the m1 acetylcholine receptor in the middle temporal visual area of the macaque monkey.

Introduction Release of the neuromodulator acetylcholine into cortical circuits supports cognition, although its precise role and mechanisms of action are not well understood. Little is known about functional differences in cholinergic modulatory effects across cortical model systems, but anatomical evidence suggests that such differences likely exist because, for example, the expression of cholinergic receptors differs profoundly both within and between species. Methods In the primary visual cortex (V1) of macaque monkeys, cholinergic receptors are strongly expressed by inhibitory interneurons. Using dual-immunofluorescence confocal microscopy, we examine m1 muscarinic acetylcholine receptor expression by two subclasses of inhibitory interneurons-identified by their expression of the calcium-binding proteins calbindin and calretinin-in the middle temporal extrastriate area (MT) of the macaque. Results and conclusions We find that the majority of calbindin-immunoreactive neurons (55%) and only few calretinin-immunoreactive neurons (10%) express the m1 acetylcholine receptor. These results differ from the pattern observed in V1 of the same species, lending further support to the notion that cholinergic modulation in the cortex is tuned such that different cortical compartments will respond to acetylcholine release in different ways.
Repliscan: a tool for classifying replication timing regions

Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds. Repliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage.
Counterion Interaction and Association in Metal-Oxide Cluster Macroanionic Solutions and the Consequent Self- Assembly

The interaction between large metal-oxide polyan- ions and their counterions is unique. Owing to their size disparity, there is a moderate ion-pairing effect and loose distribution of counterions around macroions, which leads to the unique solution behavior and the self-assembly of the macroions in polar solvents, and the counterion exchange capability around macroions. Furthermore, the macroion- counterion interaction also affects the catalytic behavior of the polyoxometalate (POM) clusters. Replacement of func- tionalized cations helps to modify the POM anions through static charge attraction. At the same time, the strong POM- counterion interaction can also lead to counterion-depen- dent synthesis. Recent developments on theoretical simula- tions help to understand this interaction at the molecular scale. This review summarizes the chronological progress of the exploration of macroion-counterion interaction (both theoretically and experimentally) and its impact on related research fields.
Photochemical Ring Expansion of α-Alkoxycyclobutanones to 2-Acetoxy-5-alkoxytetrahydrofurans: Nucleophilic Reactions at the 2-Position

Photolysis of cyclobutanones in the presence of acetic acid produced 2-acetoxy-5-alkoxytetrahydrofurans regiospecifically and with retention of configuration at the migrating α-position. The acetoxy group was replaced by nucleophiles such as allylsilane, trimethylsilyl azide, diethylaluminum cyanide, and silylated thymine in the presence of Lewis acids.
Unbiased Strain-Typing of Arbovirus Directly from Mosquitoes Using Nanopore Sequencing: A Field-forward Biosurveillance Protocol

The future of infectious disease surveillance and outbreak response is trending towards smaller hand-held solutions for point-of-need pathogen detection. Here, samples of Culex cedecei mosquitoes collected in Southern Florida, USA were tested for Venezuelan Equine Encephalitis Virus (VEEV), a previously-weaponized arthropod-borne RNA-virus capable of causing acute and fatal encephalitis in animal and human hosts. A single 20-mosquito pool tested positive for VEEV by quantitative reverse transcription polymerase chain reaction (RT-qPCR) on the Biomeme two3. The virus-positive sample was subjected to unbiased metatranscriptome sequencing on the Oxford Nanopore MinION and shown to contain Everglades Virus (EVEV), an alphavirus in the VEEV serocomplex. Our results demonstrate, for the first time, the use of unbiased sequence-based detection and subtyping of a high-consequence biothreat pathogen directly from an environmental sample using field-forward protocols. The development and validation of methods designed for field-based diagnostic metagenomics and pathogen discovery, such as those suitable for use in mobile “pocket laboratories”, will address a growing demand for public health teams to carry out their mission where it is most urgent: at the point-of-need.
Synthesis of Orthogonally Protected S,S-2,6-Diaminopimelic Acid via Olefin Cross-Metathesis

Abstract A short synthesis of orthogonally protected S,S-diaminopimelic acid, DAP, via a selective cross-metathesis between S-allyl glycine and S-vinyl glycine followed by hydrogenation is reported. By analogy, the S,S-diaminosuberic acid, DAS, is produced by self-metathesis of S-allyl glycine, and the self-metathesis of S-vinyl glycine is described.
Environmentally benign nucleophilic substitution reactions

Abstract Herein, the development of environmentally benign conditions for heterogeneous nucleophilic addition reactions under novel high speed ball milling conditions is described.