121 research outputs found
Do Multi-hop Readers Dream of Reasoning Chains?
General Question Answering (QA) systems over texts require the multi-hop
reasoning capability, i.e. the ability to reason with information collected
from multiple passages to derive the answer. In this paper we conduct a
systematic analysis to assess such an ability of various existing models
proposed for multi-hop QA tasks. Specifically, our analysis investigates that
whether providing the full reasoning chain of multiple passages, instead of
just one final passage where the answer appears, could improve the performance
of the existing QA models. Surprisingly, when using the additional evidence
passages, the improvements of all the existing multi-hop reading approaches are
rather limited, with the highest error reduction of 5.8% on F1 (corresponding
to 1.3% absolute improvement) from the BERT model.
To better understand whether the reasoning chains could indeed help find
correct answers, we further develop a co-matching-based method that leads to
13.1% error reduction with passage chains when applied to two of our base
readers (including BERT). Our results demonstrate the existence of the
potential improvement using explicit multi-hop reasoning and the necessity to
develop models with better reasoning abilities.Comment: Accepted by MRQA Workshop 201
Deep-learning-based app sensitive behavior surveillance for Android powered cyber-physical systems
Biaxial strain modulated electronic structures of layered two-dimensional MoSiGeN4 Rashba systems
The two-dimensional (2D) MA2Z4 family has received extensive attention in
manipulating its electronic structure and achieving intriguing physical
properties. However, engineering the electronic properties remains a challenge.
Herein, based on first-principles calculations, we systematically investigate
the effect of biaxial strains on the electronic structures of 2D Rashba
MoSiGeN4 (MSGN), and further explore how the interlayer interactions affect the
Rashba spin splitting in such strained layered MSGNs. After applying biaxial
strains, the band gap decreases monotonically with increasing tensile strains
but increases when the compressive strains are applied. An
indirect-direct-indirect band gap transition is induced by applying a moderate
compressive strain (< 5%) in the MSGNs. Due to the symmetry breaking and
moderate spin-orbit coupling (SOC), the monolayer MSGN possess an isolated
Rashba spin splitting (R) near the Fermi level, which could be effectively
regulated to the Lifshitz transition (L) by biaxial strain. For instance, a
L-R-L transformation of Fermi surface is presented in monolayer and a more
complex and changeable L-R-L-R evolution is observed in bilayer and trilayer
MSGNs as the biaxial strain vary from -8% to 12%, which actually depend on the
appearance, variation, and vanish of the Mexican hat band in the absence of SOC
under different strains. The contribution of Mo-dz2 orbital hybridized with
N-pz orbital in the highest valence band plays a dominant role on the band
evolution under biaxial strains, where the R-L evolution corresponds to the
decreased Mo-dz2 orbital contribution. Our study highlights the biaxial strain
controllable Rashba spin splitting, in particular the introduction and even the
evolution of Lifshitz transition near Fermi surface, which makes the strained
MSGNs as promising candidates for future applications in spintronic devices.Comment: 21 pages, 7 figures, supplementary informatio
ClickINC: In-network Computing as a Service in Heterogeneous Programmable Data-center Networks
In-Network Computing (INC) has found many applications for performance boosts
or cost reduction. However, given heterogeneous devices, diverse applications,
and multi-path network typologies, it is cumbersome and error-prone for
application developers to effectively utilize the available network resources
and gain predictable benefits without impeding normal network functions.
Previous work is oriented to network operators more than application
developers. We develop ClickINC to streamline the INC programming and
deployment using a unified and automated workflow. ClickINC provides INC
developers a modular programming abstractions, without concerning to the states
of the devices and the network topology. We describe the ClickINC framework,
model, language, workflow, and corresponding algorithms. Experiments on both an
emulator and a prototype system demonstrate its feasibility and benefits
Absence of topological Hall effect in FeRh epitaxial films: revisiting their phase diagram
A series of FeRh () films were epitaxially
grown using magnetron sputtering, and were systematically studied by
magnetization-, electrical resistivity-, and Hall resistivity measurements.
After optimizing the growth conditions, phase-pure FeRh films
were obtained, and their magnetic phase diagram was revisited. The
ferromagnetic (FM) to antiferromagnetic (AFM) transition is limited at narrow
Fe-contents with in the bulk FeRh alloys. By
contrast, the FM-AFM transition in the FeRh films is extended to
cover a much wider range between 33 % and 53 %, whose critical temperature
slightly decreases as increasing the Fe-content. The resistivity jump and
magnetization drop at the FM-AFM transition are much more significant in the
FeRh films with 50 % Fe-content than in the Fe-deficient
films, the latter have a large amount of paramagnetic phase. The
magnetoresistivity (MR) is rather weak and positive in the AFM state, while it
becomes negative when the FM phase shows up, and a giant MR appears in the
mixed FM- and AFM states. The Hall resistivity is dominated by the ordinary
Hall effect in the AFM state, while in the mixed state or high-temperature FM
state, the anomalous Hall effect takes over. The absence of topological Hall
resistivity in FeRh films with various Fe-contents implies that
the previously observed topological Hall effect is most likely extrinsic. We
propose that the anomalous Hall effect caused by the FM iron moments at the
interfaces nicely explains the hump-like anomaly in the Hall resistivity. Our
systematic investigations may offer valuable insights into the spintronics
based on iron-rhodium alloys.Comment: 9 pages, 10 figures; accepted by Phys. Rev.
Negative Curvature Hollow Core Fiber Based All-Fiber Interferometer and Its Sensing Applications to Temperature and Strain
Negative curvature hollow core fiber (NCHCF) is a promising candidate for sensing applications; however, research on NCHCF based fiber sensors starts only in the recent two years. In this work, an all-fiber interferometer based on an NCHCF structure is proposed for the first time. The interferometer was fabricated by simple fusion splicing of a short section of an NCHCF between two singlemode fibers (SMFs). Both simulation and experimental results show that multiple modes and modal interferences are excited within the NCHCF structure. Periodic transmission dips with high spectral extinction ratio (up to 30 dB) and wide free spectral range (FSR) are produced, which is mainly introduced by the modes coupling between HE11 and HE12. A small portion of light guiding by means of Anti-resonant reflecting optical waveguide (ARROW) mechanism is also observed. The transmission dips, resulting from multimode interferences (MMI) and ARROW effect have a big difference in sensitivities to strain and temperature, thus making it possible to monitor these two parameters with a single sensor head by using a characteristic matrix approach. In addition, the proposed sensor structure is experimentally proven to have a good reproducibility
YOLOv8-Peas: a lightweight drought tolerance method for peas based on seed germination vigor
IntroductionDrought stress has become an important factor affecting global food production. Screening and breeding new varieties of peas (Pisum sativum L.) for drought-tolerant is of critical importance to ensure sustainable agricultural production and global food security. Germination rate and germination index are important indicators of seed germination vigor, and the level of germination vigor of pea seeds directly affects their yield and quality. The traditional manual germination detection can hardly meet the demand of full-time sequence nondestructive detection. We propose YOLOv8-Peas, an improved YOLOv8-n based method for the detection of pea germination vigor.MethodsWe constructed a pea germination dataset and used multiple data augmentation methods to improve the robustness of the model in real-world scenarios. By introducing the C2f-Ghost structure and depth-separable convolution, the model computational complexity is reduced and the model size is compressed. In addition, the original detector head is replaced by the self-designed PDetect detector head, which significantly improves the computational efficiency of the model. The Coordinate Attention (CA) mechanism is added to the backbone network to enhance the model's ability to localize and extract features from critical regions. The neck used a lightweight Content-Aware ReAssembly of FEatures (CARAFE) upsampling operator to capture and retain detailed features at low levels. The Adam optimizer is used to improve the model's learning ability in complex parameter spaces, thus improving the model's detection performance.ResultsThe experimental results showed that the Params, FLOPs, and Weight Size of YOLOv8-Peas were 1.17M, 3.2G, and 2.7MB, respectively, which decreased by 61.2%, 61%, and 56.5% compared with the original YOLOv8-n. The mAP of YOLOv8-Peas was on par with that of YOLOv8-n, reaching 98.7%, and achieved a detection speed of 116.2FPS. We used PEG6000 to simulate different drought environments and YOLOv8-Peas to analyze and quantify the germination vigor of different genotypes of peas, and screened for the best drought-resistant pea varieties.DiscussionOur model effectively reduces deployment costs, improves detection efficiency, and provides a scientific theoretical basis for drought-resistant genotype screening in pea
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