Miracle-dz/UniFAR-FTUs huggingface dataset:
Slice-Tune: a system for high performance DNN autotuning

Autotuning DNN models prior to their deployment is an essential but time-consuming task. Using expensive (and power-hungry) GPU and TPU accelerators efficiently is also key. Since DNNs do not always use a GPU fully, spatial multiplexing of multiple models can provide just the right amount of GPU resources for each DNN. We find that a DNN model tuned with the maximum GPU resources has higher inference latency if less GPU resources are available at inference time. We present methods to tune a DNN model, so that we provide the right amount of accelerator resources during tuning. Thus, even when a wide range of GPU resources are available at inference time, the tuned model achieves low inference latency. Further, existing autotuning frameworks take a long time to tune a model due to inefficient utilization of the client and server-side CPU and GPU. Our system, Slice-Tune, improves several autotuning frameworks to efficiently use system resources by re-thinking the partitioning of tasks between the client and server (where models are profiled on the server GPU), in a Kubernetes environment. We increase parallelism during tuning by sharding the tuning model across multiple tuning application instances, providing concurrent tuning of different operators of a model. We also scale server instances to achieve better GPU multiplexing. Slice-Tune reduces DNN autotuning time in a single GPU and in GPU clusters. Slice-Tune decreases DNN autotuning time by up to 75%, and increase autotuning throughput by a factor of 5, across 3 different autotuning frameworks (TVM, Ansor, and Chameleon).
Differentiable Iterative Surface Normal Estimation

This paper presents an end-to-end differentiable algorithm for anisotropic surface normal estimation on unstructured point-clouds. We utilize graph neural networks to iteratively infer point weights for a plane fitting algorithm applied to local neighborhoods. The approach retains the interpretability and efficiency of traditional sequential plane fitting while benefiting from a data-dependent deep-learning parameterization. This results in a state-of-the-art surface normal estimator that is robust to noise, outliers and point density variation and that preserves sharp features through anisotropic kernels and a local spatial transformer. Contrary to previous deep learning methods, the proposed approach does not require any hand-crafted features while being faster and more parameter efficient.
ForETaxi: Data-Driven Fleet-Oriented Charging Resource Allocation in Large-Scale Electric Taxi Networks

Charging processes are the key to promoting electric taxis and improving their operational efficiency due to frequent charging activities and long charging time. Nevertheless, optimizing charging resource allocation in real time is extremely challenging because of uneven charging demand/supply distributions, heuristic-based charging behaviors of drivers, and city-scale of the fleets. The existing solutions have utilized real-time contextual information for charging recommendation, but they do not consider the much-richer fleet information, leading to the suboptimal individual-based charging recommendation. In this paper, we design a data-driven fleet-oriented charging recommendation system for charging resource allocation called ForETaxi for electric taxis, which aims to minimize the overall charging overhead for the entire fleet, instead of individual vehicles. ForETaxi considers not only current charging requests but also possible charging requests of other nearby electric taxis in the near future by inferring their status in real time. More importantly, we implement ForETaxi with multiple types of sensor data from the Chinese Shenzhen city including GPS data, and taxi transaction data from more than 13,000 electric taxis, combined with road network data and charging station data. The data-driven evaluation results show that compared to the state-of-the-art individual-based recommendation methods, our fleet-oriented ForETaxi outperforms them by 16% in the total charging time reduction and 82% in the queuing time reduction.
ShadowSync: latency long tail caused by hidden synchronization in real-time LSM-tree based stream processing systems

Mission-critical, real-time, continuous stream processing applications that interact with the real world have stringent latency requirements. For example, e-commerce websites like Amazon improve their marketing strategy by performing real-time advertising based on customers' behavior, and latency long tail can cause significant revenue loss. Recent work [39] showed a positive correlation between latency long tail and variance in the execution time of synchronous invocation chains (critical paths) in microservices benchmarks. This paper shows that asynchronous, very short but intense resource demands (called millibottlenecks) outside of critical paths can also cause significant latency long tail. Using a traffic analysis stream processing application benchmark, we evaluated the impact of asynchronous workload bursts generated by a multi-layer data structure called LSM-tree (log-structured merge-tree) for continuous checkpointing. Outside of the critical path, LSM-tree relies on maintenance operations (e.g., flushing/compaction during a checkpoint) to reorganize LSM-tree in memory and on disk to keep data access latency short. Although asynchronous, such recurrent maintenance operations can cause frequent millibottlenecks, particularly when they overlap, a problem we call ShadowSync. For scheduling and statistical reasons, significant latency long tail can arise from ShadowSync caused by asynchronous recurrent operations. Our experimental results show that with typical settings of benchmark components such as RocksDB, ShadowSync can prolong request message latency by up to 2 seconds. We show effective mitigation methods can alleviate both scheduled and statistical ShadowSync reducing the latency long tail to less than 20% of the original at the 99.9th percentile.
Tuning the electrically evaluated electron Landé g factor in GaAs quantum dots and quantum wells of different well widths

We evaluate the Land\'e $g$ factor of electrons in quantum dots (QDs) fabricated from GaAs quantum well (QW) structures of different well width. We first determine the Land\'e electron $g$ factor of the QWs through resistive detection of electron spin resonance and compare it to the enhanced electron $g$ factor determined from analysis of the magnetotransport. Next, we form laterally defined quantum dots using these quantum wells and extract the electron $g$ factor from analysis of the cotunneling and Kondo effect within the quantum dots. We conclude that the Land\'e electron $g$ factor of the quantum dot is primarily governed by the electron $g$ factor of the quantum well suggesting that well width is an ideal design parameter for $g$-factor engineering QDs.
ALIGNMENTS OF GALAXIES WITHIN COSMIC FILAMENTS FROM SDSS DR7

Using a sample of galaxy groups selected from the Sloan Digital Sky Survey Data Release 7, we examine the alignment between the orientation of galaxies and their surrounding large-scale structure in the context of the cosmic web. The latter is quantified using the large-scale tidal field, reconstructed from the data using galaxy groups above a certain mass threshold. We find that the major axes of galaxies in filaments tend to be preferentially aligned with the directions of the filaments, while galaxies in sheets have their major axes preferentially aligned parallel to the plane of the sheets. The strength of this alignment signal is strongest for red, central galaxies, and in good agreement with that of dark matter halos in N-body simulations. This suggests that red, central galaxies are well aligned with their host halos, in quantitative agreement with previous studies based on the spatial distribution of satellite galaxies. There is a luminosity and mass dependence that brighter and more massive galaxies in filaments and sheets have stronger alignment signals. We also find that the orientation of galaxies is aligned with the eigenvector associated with the smallest eigenvalue of the tidal tensor. These observational results indicate that galaxy formation is affected by large-scale environments and strongly suggest that galaxies are aligned with each other over scales comparable to those of sheets and filaments in the cosmic web.
An optimal design of GNSS interference localisation wireless security network based on time-difference of arrivals for the Arlanda international airport

Abstract Today, most of the aircrafts are navigated by global navigation satellite systems (GNSSs). Landing is a dangerous phase of a flight especially when an airport runway is not clearly seen from the aircrafts. In such cases, GNSSs are useful for a safe landing under the circumstances that healthy signals, free of any interference, reach to GNSSs receiver antennas mounted on the aircrafts. This shows the importance of establishing GNSS interference localisation security networks around airports. Designing a good configuration for the points with GNSS antennas at for receiving interference signals is important for a successful localisation of the interference device. Here, the time-difference of the arrivals of an interference signal to such points or anchor nodes (ANs), are used as observables, and a security network with four ANs is optimally designed along the runways of the Arlanda airport to reduce the dilution of precision (DOP) of the network. Our study showed that by such an optimisation, the maximum DOP value can reduce by 50% meaning a significant increase in the probability of a successful interference device localisation.
Intra-layer synchronization in multiplex networks

We study synchronization of N oscillators indirectly coupled through a medium which is inhomogeneous and has its own dynamics. The system is formalized in terms of a multilayer network, where the top layer is made of disconnected oscillators and the bottom one, modeling the medium, consists of oscillators coupled according to a given topology. The different dynamics of the medium and the top layer is accounted for by including a frequency mismatch between them. We show a novel regime of synchronization as intra-layer coherence does not necessarily require inter-layer coherence. This regime appears under mild conditions on the bottom layer: arbitrary topologies may be considered, provided that they support synchronization of the oscillators of the medium. The existence of a density-dependent threshold as in quorum-sensing phenomena is also demonstrated.
Clustering laminar cytoarchitecture on the cortical surfaces

In recent years, multiple neuroimaging studies have utilized magnetic resonance imaging (MRI) relaxometry to visualize and explore the intricate laminar microstructure of the cerebral cortex, which is considered a unique anatomical mark of the development, function, connectivity, and even various pathologies of the brain. T1 relaxometry has successfully delineated laminar components across the cortex, expanding its applicability from solely a direct measure of myelin content to an indirect measure of cortical cytoarchitecture. However, analyzing the resulting laminar dataset is no simple task due to its multidimensionality and geometric complexity: six cortical laminar components, representing the regionally varying microstructure of the cortex, are dispersed across a triangulated surface, representing the intricate and tortuous geometry of the cortex. In this study we implement an adaptation of an algorithm that clusters cell omics profiles using their spatial organization to cluster multidimensional surface-based microstructural data in the cortex. The correspondence of the results with an established atlas of cytoarchitectonic features provides further validation of the T1 imaging framework for cortical laminar composition analysis and highlights the role of MRI neuroimaging as a probe of tissue microstructure.
Bayesian Photon Counting with EMCCDs

Context. The EMCCD is a CCD type that delivers fast readout and negligible detector noise, making it an ideal detector for high frame rate applications. Because of the very low detector noise, this detector can potentially count single photons. Aims. Considering that an EMCCD has a limited dynamical range and negligible detector noise, one would typically apply an EMCCD in such a way that multiple images of the same object are available, for instance, in so called lucky imaging. The problem of counting photons can then conveniently be viewed as statistical inference of flux or photon rates, based on a stack of images. Methods. A simple probabilistic model for the output of an EMCCD is developed. Based on this model and the prior knowledge that photons are Poisson distributed, we derive two methods for estimating the most probable flux per pixel, one based on thresholding, and another based on full Bayesian inference. Results. We find that it is indeed possible to derive such expressions, and tests of these methods show that estimating fluxes with only shot noise is possible, up to fluxes of about one photon per pixel per readout.
Exploring work-life balance among professional women in mainland China: A qualitative study

This article introduces a qualitative study utilizing semi-structured interviews to explore the barriers and resources of professional women to attain work-life balance (WLB) in the context of mainland China. Interviews were conducted with full-time employed women who had received higher education and possessed professional qualifications (N = 20). The findings reveal underlying factors in work and non-work domains which influence the achievement of work-life balance among Chinese professional women. Participants were found to perceive and attain their work-life balance differently according to their personal traits. The findings also highlight social and family support resources for Chinese professional women from the perspective of Confucianism. This study contributes to current knowledge on work and life issues through the lens of professional women's work-life balance perceptions and experiences in mainland China.
Super-Entropic Black Holes

Super-entropic black holes form a new class of exact solutions to the Einstein–Maxwell–AdS equations. They are obtained from taking a new ultraspinning limit to the class of Kerr-AdS metrics, and have a number of intriguing properties. Their event horizons are not compact but have finite area, they have no closed timelike curves, and their entropy is larger than expected from general considerations of their thermodynamic volume. Here a brief overview of the construction and basic physical properties of these metrics is presented.
On the scaling properties of oscillatory modes with balanced energy

Animal bodies maintain themselves with the help of networks of physiological processes operating over a wide range of timescales. Many physiological signals are characterized by 1/f scaling where the amplitude is inversely proportional to frequency, presumably reflecting the multi-scale nature of the underlying network. Although there are many general theories of such scaling, it is less clear how they are grounded on the specific constraints faced by biological systems. To help understand the nature of this phenomenon, we propose to pay attention not only to the geometry of scaling processes but also to their energy. The first key assumption is that physiological action modes constitute thermodynamic work cycles. This is formalized in terms of a theoretically defined oscillator with dissipation and energy-pumping terms. The second assumption is that the energy levels of the physiological action modes are balanced on average to enable flexible switching among them. These ideas were addressed with a modelling study. An ensemble of dissipative oscillators exhibited inverse scaling of amplitude and frequency when the individual oscillators’ energies are held equal. Furthermore, such ensembles behaved like the Weierstrass function and reproduced the scaling phenomenon. Finally, the question is raised whether this kind of constraint applies both to broadband aperiodic signals and periodic, narrow-band oscillations such as those found in electrical cortical activity.
Lithium doped biphasic calcium phosphate: Structural analysis and osteo/odontogenic potential in vitro

Biphasic calcium phosphate (BCP) is generally considered a good synthetic bone graft material with osteoinductive potential. Lithium ions are trace elements that play a role in the bone-remodeling process. This study aimed to investigate the effects of lithium ions on the phase, crystal structure, and biological responses of lithium doped BCPs and to identify improvements in their osteogenic properties. Lithium-doped BCP powders with different doping levels (0, 5, 10, and 20 at%) were synthesized via the co-precipitation method. We found that the four types of lithium-doped BCP powders showed different phase compositions of hydroxyapatite and β-tricalcium phosphate. In addition, lithium ions favored entering the β-tricalcium phosphate structure at the Ca (4) sites and calcium vacancy sites [VCa(4)] up to 10 at%. This substitution improves the crystal stabilization by filling the vacancies with Ca2+ and Li+ in all Ca sites. However, when the concentration of Li ions was higher than 10 at%, lithium-induced crystal instability resulted in the burst release of lithium ions, and the osteogenic behavior of human dental pulp stem cells did not improve further. Although lithium ions regulate osteogenic properties, it is important to determine the optimal amount of lithium in BCPs. In this study, the most effective lithium doping level in BCP was approximately 10 at% to improve its biological properties and facilitate medical applications.
Diversity and Disturbance: How Mussels and Sea Stars Strengthen the Rocky Intertidal Community

In the rocky intertidal zone, tides and rocks set the stage. Together they create habitat for a diverse community of species adapted to a world both underwater (high tide) and exposed to air (low tide). In some protected areas, like national parks, we study rocky intertidal ecosystems as vital signs of nature’s health. Studying them helps us understand the impact of disturbances, which play an important role in shaping these communities. Some disturbances, like the tides, happen daily. Others, like diseases, might happen once every decade. This article is about how tides and diseases affect two important members of rocky intertidal communities—mussels and sea stars. We explain the roles these organisms play and what happened when ochre sea stars, an important species in these habitats, suffered a major disease outbreak. Last, we emphasize the importance of protecting these vital ecosystems so we can continue to learn about the health of the natural environment.
Capacitive interactions and Kondo effect tuning in double quantum impurity systems

We present a study of the correlated transport regimes of a double quantum impurity system with mutual capacitive interactions. Such system can be implemented by a double quantum dot arrangement or by a quantum dot and nearby quantum point contact, with independently connected sets of metallic terminals. Many-body spin correlations arising within each dot-lead subsystem give rise to the Kondo effect under appropriate conditions. The otherwise independent Kondo ground states may be modified by the capacitive coupling, decisively modifying the ground state of the double quantum impurity system. We analyze this coupled system through variational methods and the numerical renormalization group technique. Our results reveal a strong dependence of the coupled system ground state on the electron-hole asymmetries of the individual subsystems, as well as on their hybridization strengths to the respective reservoirs. The electrostatic repulsion produced by the capacitive coupling produces an effective shift of the individual energy levels toward higher energies, with a stronger effect on the ``shallower'' subsystem (that closer to resonance with the Fermi level), potentially pushing it out of the Kondo regime and dramatically changing the transport properties of the system. The effective remote gating that this entails is found to depend nonlinearly on the capacitive coupling strength, as well as on the independent subsystem levels. The analysis we present here of this mutual interaction should be important to fully characterize transport through such coupled systems.
Expedited retrieval of high-quality Usutu virus genomes via Nanopore sequencing with and without target enrichment

Usutu virus (USUV) is a mosquito-borne zoonotic virus and one of the causes of flavivirus encephalitis in birds and occasionally in humans. USUV rapidly disperses in a susceptible host and vector environment, as is the case in South and Central Europe. However, compared to other flaviviruses, USUV has received less research attention and there is therefore limited access to whole-genome sequences and also to in-depth phylogenetic and phylodynamic analyses. To ease future molecular studies, this study compares first- (partial sequencing via Sanger), second- (Illumina), and third-generation (MinION Nanopore) sequencing platforms for USUV. With emphasis on MinION Nanopore sequencing, cDNA-direct and target-enrichment (amplicon-based) sequencing approaches were validated in parallel. The study was based on four samples from succumbed birds commonly collected throughout Germany. The samples were isolated from various sample matrices, organs as well as blood cruor, and included three different USUV lineages. We concluded that depending on the focus of a research project, amplicon-based MinION Nanopore sequencing can be an ideal cost- and time-effective alternative to Illumina in producing optimal genome coverage. It can be implemented for an array of lab- or field-based objectives, including among others: phylodynamic studies and the analysis of viral quasispecies.
SLC7A8 coding for LAT2 is associated with early disease progression in osteosarcoma and transports doxorubicin

Background: Despite (neo) adjuvant chemotherapy with cisplatin, doxorubicin and methotrexate, some patients with primary osteosarcoma progress during first-line systemic treatment and have a poor prognosis. In this study, we investigated whether patients with early disease progression (EDP), are characterized by a distinctive pharmacogenetic profile. Methods and Findings: Germline DNA from 287 Dutch high-grade osteosarcoma patients was genotyped using the DMET Plus array (containing 1,936 genetic markers in 231 drug metabolism and transporter genes). Associations between genetic variants and EDP were assessed using logistic regression models and associated variants (p <0.05) were validated in independent cohorts of 146 (Spain and United Kingdom) and 28 patients (Australia). In the association analyses, EDP was significantly associated with an SLC7A8 locus and was independently validated (meta-analysis validation cohorts: OR 0.19 [0.06–0.55], p = 0.002). The functional relevance of the top hits was explored by immunohistochemistry staining and an in vitro transport models. SLC7A8 encodes for the L-type amino acid transporter 2 (LAT2). Transport assays in HEK293 cells overexpressing LAT2 showed that doxorubicin, but not cisplatin and methotrexate, is a substrate for LAT2 (p < 0.0001). Finally, SLC7A8 mRNA expression analysis and LAT2 immunohistochemistry of osteosarcoma tissue showed that the lack of LAT2 expression is a prognostic factor of poor prognosis and reduced overall survival in patients without metastases (p = 0.0099 and p = 0.14, resp.). Conclusion: This study identified a novel locus in SLC7A8 to be associated with EDP in osteosarcoma. Functional studies indicate LAT2-mediates uptake of doxorubicin, which could give new opportunities to personalize treatment of osteosarcoma patients.