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  1. This study employs supervised machine learning algorithms to test whether locomotive features during exploratory activity in open field arenas can serve as predictors for the genotype of fruit flies. Because of the nonlinearity in locomotive trajectories, traditional statistical methods that are used to compare exploratory activity between genotypes of fruit flies may not reveal all insights. 10-minute-long trajectories of four different genotypes of fruit flies in an open-field arena environment were captured. Turn angles and step size features extracted from the trajectories were used for training supervised learning models to predict the genotype of the fruit flies. Using the first five minute locomotive trajectories, an accuracy of 83% was achieved in differentiating wild-type flies from three other mutant genotypes. Using the final 5 min and the entire ten minute duration decreased the performance indicating that the most variations between the genotypes in their exploratory activity are exhibited in the first few minutes. Feature importance analysis revealed that turn angle is a better predictor than step size in predicting fruit fly genotype. Overall, this study demonstrates that features of trajectories can be used to predict the genotype of fruit flies through supervised machine learning methods. 
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    Free, publicly-accessible full text available October 1, 2024
  2. Unexpected long query latency of a database system can cause domino effects on all the upstream services and se- verely degrade end users’ experience with unpredicted long waits, resulting in an increasing number of users disengaged with the services and thus leading to a high user disengage- ment ratio (UDR). A high UDR usually translates to reduced revenue for service providers. This paper proposes UTSLO, a UDR-oriented SLO guaranteed system, which enables a database system to support multi-tenant UDR targets in a cost-effective fashion through UDR-oriented capacity plan- ning and dynamic UDR target enforcement. The former aims to estimate the feasibility of UDR targets while the latter dynamically tracks and regulates per-connection query la- tency distribution needed for accurate UDR target guarantee. In UTSLO, the database service capacity can be fully ex- ploited to efficiently accommodate tenants while minimizing resources required for UDR target guarantee. 
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    Free, publicly-accessible full text available November 1, 2024
  3. Tissue regeneration-promoting and drug-eluting biomaterials are commonly implanted into animals as a part of late-stage testing before committing to human trials required by the government. Because the trials are very expensive (e.g., they can cost over a billion U.S. dollars), it is critical for companies to have the best possible characterization of the materials' safety and efficacy before it goes into a human. However, the conventional approaches to biomaterial evaluation necessitate sacrificial analysis (i.e., euthanizing a different animal for measuring each time point and retrieving the implant for histological analysis), due to the inability to monitor how the host tissues respond to the presence of the material in situ. This is expensive, inaccurate, discontinuous, and unethical. In contrast, our manuscript presents a novel microfluidic platform potentially capable of performing non-disruptive fluid manipulations within the spatial constraints of an 8 mm diameter critical calvarial defect—a “gold standard” model for testing engineered bone tissue scaffolds in living animals. In particular, here, addressable microfluidic plumbing is specifically adapted for the in vivo implantation into a simulated rat's skull, and is integrated with a combinatorial multiplexer for a better scaling of many time points and/or biological signal measurements. The collected samples (modeled as food dyes for proof of concept) are then transported, stored, and analyzed ex vivo, which adds previously-unavailable ease and flexibility. Furthermore, care is taken to maintain a fluid equilibrium in the simulated animal's head during the sampling to avoid damage to the host and to the implant. Ultimately, future implantation protocols and technology improvements are envisioned toward the end of the manuscript. Although the bone tissue engineering application was chosen as a proof of concept, with further work, the technology is potentially versatile enough for other in vivo sampling applications. Hence, the successful outcomes of its advancement should benefit companies developing, testing, and producing vaccines and drugs by accelerating the translation of advanced cell culturing tech to the clinical market. Moreover, the nondestructive monitoring of the in vivo environment can lower animal experiment costs and provide data-gathering continuity superior to the conventional destructive analysis. Lastly, the reduction of sacrifices stemming from the use of this technology would make future animal experiments more ethical.

     
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  4. We present a highly efficient method for the extraction of optical properties of very large molecules via the Bethe–Salpeter equation. The crutch of this approach is the calculation of the action of the effective Coulombic interaction, W, through a stochastic time-dependent Hartree propagation, which uses only ten stochastic orbitals rather than propagating the full sea of occupied states. This leads to a scaling that is at most cubic in system size with trivial parallelization of the calculation. We apply this new method to calculate the spectra and electronic density of the dominant excitons of a carbon-nanohoop bound fullerene system with 520 electrons using less than 4000 core hours. 
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