496 research outputs found
PEGA: Personality-Guided Preference Aggregator for Ephemeral Group Recommendation
Recently, making recommendations for ephemeral groups which contain dynamic
users and few historic interactions have received an increasing number of
attention. The main challenge of ephemeral group recommender is how to
aggregate individual preferences to represent the group's overall preference.
Score aggregation and preference aggregation are two commonly-used methods that
adopt hand-craft predefined strategies and data-driven strategies,
respectively. However, they neglect to take into account the importance of the
individual inherent factors such as personality in the group. In addition, they
fail to work well due to a small number of interactive records. To address
these issues, we propose a Personality-Guided Preference Aggregator (PEGA) for
ephemeral group recommendation. Concretely, we first adopt hyper-rectangle to
define the concept of Group Personality. We then use the personality attention
mechanism to aggregate group preferences. The role of personality in our
approach is twofold: (1) To estimate individual users' importance in a group
and provide explainability; (2) to alleviate the data sparsity issue that
occurred in ephemeral groups. The experimental results demonstrate that our
model significantly outperforms the state-of-the-art methods w.r.t. the score
of both Recall and NDCG on Amazon and Yelp datasets
Comparative venom gland transcriptome analysis of the scorpion Lychas mucronatus reveals intraspecific toxic gene diversity and new venomous components
<p>Abstract</p> <p>Background</p> <p><it>Lychas mucronatus </it>is one scorpion species widely distributed in Southeast Asia and southern China. Anything is hardly known about its venom components, despite the fact that it can often cause human accidents. In this work, we performed a venomous gland transcriptome analysis by constructing and screening the venom gland cDNA library of the scorpion <it>Lychas mucronatus </it>from Yunnan province and compared it with the previous results of Hainan-sourced <it>Lychas mucronatus</it>.</p> <p>Results</p> <p>A total of sixteen known types of venom peptides and proteins are obtained from the venom gland cDNA library of Yunnan-sourced <it>Lychas mucronatus</it>, which greatly increase the number of currently reported scorpion venom peptides. Interestingly, we also identified nineteen atypical types of venom molecules seldom reported in scorpion species. Surprisingly, the comparative transcriptome analysis of Yunnan-sourced <it>Lychas mucronatus </it>and Hainan-sourced <it>Lychas mucronatus </it>indicated that enormous diversity and vastly abundant difference could be found in venom peptides and proteins between populations of the scorpion <it>Lychas mucronatus </it>from different geographical regions.</p> <p>Conclusions</p> <p>This work characterizes a large number of venom molecules never identified in scorpion species. This result provides a comparative analysis of venom transcriptomes of the scorpion <it>Lychas mucronatus </it>from different geographical regions, which thoroughly reveals the fact that the venom peptides and proteins of the same scorpion species from different geographical regions are highly diversified and scorpion evolves to adapt a new environment by altering the primary structure and abundance of venom peptides and proteins.</p
X-ray performance of a customized large-format scientifc CMOS detector
In recent years, the performance of Scientifc Complementary Metal Oxide
Semiconductor (sCMOS) sensors has been improved signifcantly. Compared with CCD
sensors, sCMOS sensors have various advantages, making them potentially better
devices for optical and X-ray detection, especially in time-domain astronomy.
After a series of tests of sCMOS sensors, we proposed a new dedicated
high-speed, large-format X-ray detector in 2016 cooperating with Gpixel Inc.
This new sCMOS sensor has a physical size of 6 cm by 6 cm, with an array of
4096 by 4096 pixels and a pixel size of 15 um. The frame rate is 20.1 fps under
current condition and can be boosted to a maximum value around 100 fps. The
epitaxial thickness is increased to 10 um compared to the previous sCMOS
product. We show the results of its frst taped-out product in this work. The
dark current of this sCMOS is lower than 10 e/pixel/s at 20C, and lower than
0.02 e/pixel/s at -30C. The Fixed Pattern Noise (FPN) and the readout noise are
lower than 5 e in high-gain situation and show a small increase at low
temperature. The energy resolution reaches 180.1 eV (3.1%) at 5.90 keV for
single-pixel events and 212.3 eV (3.6%) for all split events. The continuous
X-ray spectrum measurement shows that this sensor is able to response to X-ray
photons from 500 eV to 37 keV. The excellent performance, as demonstrated from
these test results, makes sCMOS sensor an ideal detector for X-ray imaging and
spectroscopic application.Comment: 20 pages. published in PAS
Magnetically assisted DNA assays: high selectivity using conjugated polymers for amplified fluorescent transduction
We report a strategy for conjugated polymer (CP)-based optical DNA detection with improved selectivity. The high sensitivity of CP-based biosensors arises from light harvesting by the CP and the related amplified fluorescent signal transduction. We demonstrate that the use of magnetic microparticles significantly improves the selectivity of this class of DNA sensors. Compared with previously reported DNA sensors with CP amplification, this novel sensing strategy displays excellent discrimination against non-cognate DNA in the presence of a protein mixture or even human serum. We also demonstrate that the magnetically assisted DNA sensor can conveniently identify even a single-nucleotide mismatch in the target sequence
A Scorpion Defensin BmKDfsin4 Inhibits Hepatitis B Virus Replication in Vitro
Hepatitis B virus (HBV) infection is a major worldwide health problem which can cause
acute and chronic hepatitis and can significantly increase the risk of liver cirrhosis and primary
hepatocellular carcinoma (HCC). Nowadays, clinical therapies of HBV infection still mainly rely on
nucleotide analogs and interferons, the usage of which is limited by drug-resistant mutation or side
effects. Defensins had been reported to effectively inhibit the proliferation of bacteria, fungi, parasites
and viruses. Here, we screened the anti-HBV activity of 25 scorpion-derived peptides most recently
characterized by our group. Through evaluating anti-HBV activity and cytotoxicity, we found that
BmKDfsin4, a scorpion defensin with antibacterial and Kv1.3-blocking activities, has a comparable
high inhibitory rate of both HBeAg and HBsAg in HepG2.2.15 culture medium and low cytotoxicity
to HepG2.2.15. Then, our experimental results further showed that BmKDfsin4 can dose-dependently
decrease the production of HBV DNA and HBV viral proteins in both culture medium and cell lysate.
Interestingly, BmKDfsin4 exerted high serum stability. Together, this study indicates that the scorpion
defensin BmKDfsin4 also has inhibitory activity against HBV replication along with its antibacterial
and potassium ion channel Kv1.3-blocking activities, which shows that BmKDfsin4 is a uniquely
multifunctional defensin molecule. Our work also provides a good molecule material which will be
used to investigate the link or relationship of its antiviral, antibacterial and ion channel–modulating
activities in the future
The causality between human immunoglobulin g (IgG) n-glycosylation and aging: A mendelian randomization study
Background: Immunoglobulin G (IgG) N-glycosylation is considered a potential biomarker for aging and various pathological conditions. However, whether these changes in IgG N-glycosylation are a consequence or a contributor to the aging process remains unclear. This study aims to investigate the causality between IgG N-glycosylation and aging using Mendelian randomization (MR) analysis. Methods: We utilized genetic variants associated with IgG N-glycosylation traits, the frailty index (FI), and leukocyte telomere length (LTL) from a previous genome-wide association study (GWAS) on individuals of European ancestry. Two-sample and multivariable MR analyses were conducted, employing the inverse-variance weighted (IVW) method. Sensitivity analyses were performed to assess potential confounding factors. Results: Using the IVW method, we found suggestive evidence of a causal association between GP14 and FI ( 0.026, 95% CI 0.003 to 0.050, p = 0.027) and LTL ( −0.020, 95% CI −0.037 to −0.002, p = 0.029) in the two-sample MR analysis. In the multivariable MR analysis, suggestive evidence was found for GP23 and FI ( −0.119, 95% CI −0.219 to −0.019, p = 0.019) and GP2 and LTL ( 0.140, 95% CI 0.020 to 0.260, p = 0.023). Conclusions: In conclusion, our results supported a potentially causal effect of lower GP23 levels on an advanced aging state. Additional verification is required to further substantiate the causal relationship between glycosylation and aging
DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation
Sequential recommendations have made great strides in accurately predicting
the future behavior of users. However, seeking accuracy alone may bring side
effects such as unfair and overspecialized recommendation results. In this
work, we focus on the calibrated recommendations for sequential recommendation,
which is connected to both fairness and diversity. On the one hand, it aims to
provide fairer recommendations whose preference distributions are consistent
with users' historical behaviors. On the other hand, it can improve the
diversity of recommendations to a certain degree. But existing methods for
calibration have mainly relied on the post-processing on the candidate lists,
which require more computation time in generating recommendations. In addition,
they fail to establish the relationship between accuracy and calibration,
leading to the limitation of accuracy. To handle these problems, we propose an
end-to-end framework to provide both accurate and calibrated recommendations
for sequential recommendation. We design an objective function to calibrate the
interests between recommendation lists and historical behaviors. We also
provide distribution modification approaches to improve the diversity and
mitigate the effect of imbalanced interests. In addition, we design a
decoupled-aggregated model to improve the recommendation. The framework assigns
two objectives to two individual sequence encoders, and aggregates the outputs
by extracting useful information. Experiments on benchmark datasets validate
the effectiveness of our proposed model
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