L^2 torsion without the determinant class condition and extended L^2 cohomology

We associate determinant lines to objects of the extended abelian category built out of a von Neumann category with a trace. Using this we suggest constructions of the combinatorial and the analytic L^2 torsions which, unlike the work of the previous authors, requires no additional assumptions; in particular we do not impose the determinant class condition. The resulting torsions are elements of the determinant line of the extended L^2 cohomology. Under the determinant class assumption the L^2 torsions of this paper specialize to the invariants studied in our previous work. Applying a recent theorem of D. Burghelea, L. Friedlander and T. Kappeler we obtain a Cheeger - Muller type theorem stating the equality between the combinatorial and the analytic L^2 torsions.Comment: 39 page

Whole-exome sequencing validates a preclinical mouse model for the prevention and treatment of cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinomas (cSCC) are among the most common and highly mutated human malignancies. Solar UV radiation is the major factor in the etiology of cSCC. Wholeexome sequencing of 18 microdissected tumor samples (cases) derived from SKH-1 hairless mice that had been chronically exposed to solar-simulated UV (SSUV) radiation showed a median point mutation (SNP) rate of 155 per Mb. The majority (78.6%) of the SNPs are C.GT.A transitions, a characteristic UVR-induced mutational signature. Direct comparison with human cSCC cases showed high overlap in terms of both frequency and type of SNP mutations. Mutations in Trp53 were detected in 15 of 18 (83%) cases, with 20 of 21 SNP mutations located in the protein DNA-binding domain. Strikingly, multiple nonsynonymous SNP mutations in genes encoding Notch family members (Notch1-4) were present in 10 of 18 (55%) cases. The histopathologic spectrum of the mouse cSCC that develops in this model resembles very closely the spectrum of human cSCC. We conclude that the mouse SSUV cSCCs accurately represent the histopathologic and mutational spectra of the most prevalent tumor suppressors of human cSCC, validating the use of this preclinical model for the prevention and treatment of human cSCC.</p

FAM83D directs protein kinase CK1α to the mitotic spindle for proper spindle positioning

The concerted action of many protein kinases helps orchestrate the error-free progression through mitosis of mammalian cells. The roles and regulation of some prominent mitotic kinases, such as cyclin-dependent kinases, are well established. However, these and other known mitotic kinases alone cannot account for the extent of protein phosphorylation that has been reported during mammalian mitosis. Here we demonstrate that CK1α, of the casein kinase 1 family of protein kinases, localises to the spindle and is required for proper spindle positioning and timely cell division. CK1α is recruited to the spindle by FAM83D, and cells devoid of FAM83D, or those harbouring CK1α-binding-deficient FAM83D F283A/F283A knockin mutations, display pronounced spindle positioning defects, and a prolonged mitosis. Restoring FAM83D at the endogenous locus in FAM83D −/− cells, or artificially delivering CK1α to the spindle in FAM83D F283A/F283A cells, rescues these defects. These findings implicate CK1α as new mitotic kinase that orchestrates the kinetics and orientation of cell division. </p

GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science

The new polymath Large Language Models (LLMs) can speed-up greatly scientific reviews, possibly using more unbiased quantitative metrics, facilitating cross-disciplinary connections, and identifying emerging trends and research gaps by analyzing large volumes of data. However, at the present time, they lack the required deep understanding of complex methodologies, they have difficulty in evaluating innovative claims, and they are unable to assess ethical issues and conflicts of interest. Herein, we consider 13 GPT-related papers across different scientific domains, reviewed by a human reviewer and SciSpace, a large language model, with the reviews evaluated by three distinct types of evaluators, namely GPT-3.5, a crowd panel, and GPT-4. We found that 50% of SciSpace's responses to objective questions align with those of a human reviewer, with GPT-4 (informed evaluator) often rating the human reviewer higher in accuracy, and SciSpace higher in structure, clarity, and completeness. In subjective questions, the uninformed evaluators (GPT-3.5 and crowd panel) showed varying preferences between SciSpace and human responses, with the crowd panel showing a preference for the human responses. However, GPT-4 rated them equally in accuracy and structure but favored SciSpace for completeness

What do LLMs need to Synthesize Correct Router Configurations?

We investigate whether Large Language Models (e.g., GPT-4) can synthesize correct router configurations with reduced manual effort. We find GPT-4 works very badly by itself, producing promising draft configurations but with egregious errors in topology, syntax, and semantics. Our strategy, that we call Verified Prompt Programming, is to combine GPT-4 with verifiers, and use localized feedback from the verifier to automatically correct errors. Verification requires a specification and actionable localized feedback to be effective. We show results for two use cases: translating from Cisco to Juniper configurations on a single router, and implementing no-transit policy on multiple routers. While human input is still required, if we define the leverage as the number of automated prompts to the number of human prompts, our experiments show a leverage of 10X for Juniper translation, and 6X for implementing no-transit policy, ending with verified configurations

LIGHTYEAR: Using Modularity to Scale BGP Control Plane Verification

Current network control plane verification tools cannot scale to large networks, because of the complexity of jointly reasoning about the behaviors of all nodes in the network. In this paper we present a modular approach to control plane verification, whereby end-to-end network properties are verified via a set of purely local checks on individual nodes and edges. The approach targets the verification of safety properties for BGP configurations and provides guarantees in the face of both arbitrary external route announcements from neighbors and arbitrary node/link failures. We have proven the approach correct and also implemented it in a tool called Lightyear. Experimental results show that Lightyear scales dramatically better than prior control plane verifiers. Further, we have used Lightyear to verify three properties of the wide area network of a major cloud provider, containing hundreds of routers and tens of thousands of edges. To our knowledge no prior tool has been demonstrated to provide such guarantees at that scale. Finally, in addition to the scaling benefits, our modular approach to verification makes it easy to localize the causes of configuration errors and to support incremental re-verification as configurations are updatedComment: 12 pages (+ 2 pages references), 3 figures submitted to NSDI '2

Universality in the emergence of oscillatory instabilities in turbulent flows

Spontaneous emergence of periodic oscillations due to self-organization is ubiquitous in turbulent flows. The emergence of such oscillatory instabilities in turbulent fluid mechanical systems is often studied in different system-specific frameworks. We uncover the existence of a universal scaling behaviour during self-organization in turbulent flows leading to oscillatory instability. Our experiments show that the spectral amplitude of the dominant mode of oscillations scales inversely with the Hurst exponent of a fluctuating state variable following an inverse power law relation. Interestingly, we observe the same power law behaviour with a constant exponent near -2 across various turbulent systems such as aeroacoustic, thermoacoustic and aeroelastic systems.Comment: 5 pages, 4 figures and supplementary informatio