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In living organisms, changes in calcium flux are integral to many different cellular functions and are especially critical for the activity of neurons and myocytes. Genetically encoded calcium indicators (GECIs) have been popular tools for reporting changes in calcium levels in vivo. In particular, GCaMPs, derived from GFP, are the most widely used GECIs and have become an invaluable toolkit for neurophysiological studies. Recently, new variants of GCaMP, which offer a greater variety of temporal dynamics and improved brightness, have been developed. However, these variants are not readily available to the Caenorhabditis elegans research community. This work reports a set of GCaMP6 and jGCaMP7 reporters optimized for C. elegans studies. Our toolkit provides reporters with improved dynamic range, varied kinetics, and targeted subcellular localizations. Besides optimized routine uses, this set of reporters is also well suited for studies requiring fast imaging speeds and low magnification or low-cost platforms.

 

Benchmarks that closely match the behavior of production workloads are crucial to design and provision computer systems. However, current approaches fall short: First, open-source benchmarks use public datasets that cause different behavior from production workloads. Second, blackbox workload cloning techniques generate synthetic code that imitates the target workload, but the resulting program fails to capture most workload characteristics, such as microarchitectural bottlenecks or time-varying behavior. Generating code that mimics a complex application is an extremely hard problem. Instead, we propose a different and easier approach to benchmark synthesis. Our key insight is that, for many production workloads, the program is publicly available or there is a reasonably similar open-source program. In this case, generating the right dataset is sufficient to produce an accurate benchmark. Based on this observation, we present Datamime, a profile-guided approach to generate representative benchmarks for production workloads. Datamime uses the performance profiles of a target workload to generate a dataset that, when used by a benchmark program, behaves very similarly to the target workload in terms of its microarchitectural characteristics. We evaluate Datamime on several datacenter workloads. Datamime generates synthetic benchmarks that closely match the microarchitectural features of these workloads, with a mean absolute percentage error of 3.2% on IPC. Microarchitectural behavior stays close across processor types. Finally, time-varying behaviors are also replicated, making these benchmarks useful to e.g. characterize and optimize tail latency 

Abstract The DAMA/LIBRA collaboration has reported the observation of an annual modulation in the event rate that has been attributed to dark matter interactions over the last two decades. However, even though tremendous efforts to detect similar dark matter interactions were pursued, no definitive evidence has been observed to corroborate the DAMA/LIBRA signal. Many studies assuming various dark matter models have attempted to reconcile DAMA/LIBRA’s modulation signals and null results from other experiments, however no clear conclusion can be drawn. Apart from the dark matter hypothesis, several studies have examined the possibility that the modulation is induced by variations in detector’s environment or their specific analysis methods. In particular, a recent study presents a possible cause of the annual modulation from an analysis method adopted by the DAMA/LIBRA experiment in which the observed annual modulation could be reproduced by a slowly varying time-dependent background. Here, we study the COSINE-100 data using an analysis method similar to the one adopted by the DAMA/LIBRA experiment and observe a significant annual modulation, however the modulation phase is almost opposite to that of the DAMA/LIBRA data. Assuming the same background composition for COSINE-100 and DAMA/LIBRA, simulated experiments for the DAMA/LIBRA without dark matter signals also provide significant annual modulation with an amplitude similar to DAMA/LIBRA with opposite phase. Even though this observation does not directly explain the DAMA/LIBRA results directly, this interesting phenomenon motivates more profound studies of the time-dependent DAMA/LIBRA background data. 

The application of an external magnetic field of sufficient strength to a spin system composed of a localized singlet can overcome the energy gap and trigger bosonic condensation and so provide an alternative method to realize exotic phases of matter in real materials. Previous research has indicated that a spin Hamiltonian with on-site Kondo coupling may be the effective many-body Hamiltonian for Ba₂NiO₂(AgSe)₂(BNOAS) and here we study such a Hamiltonian using a tensor network ansatz in two dimensions. Our results unveil a phase diagram which indicates the underlying phases of BNOAS. We propose, in response to the possible doping-induced superconductivity of BNOAS, a fermionic model for further investigation. We hope that our discovery can bring up further interest in both theoretical and experimental researches for related nickelate compounds.