18 research outputs found
Robust Navigation with Cross-Modal Fusion and Knowledge Transfer
Recently, learning-based approaches show promising results in navigation
tasks. However, the poor generalization capability and the simulation-reality
gap prevent a wide range of applications. We consider the problem of improving
the generalization of mobile robots and achieving sim-to-real transfer for
navigation skills. To that end, we propose a cross-modal fusion method and a
knowledge transfer framework for better generalization. This is realized by a
teacher-student distillation architecture. The teacher learns a discriminative
representation and the near-perfect policy in an ideal environment. By
imitating the behavior and representation of the teacher, the student is able
to align the features from noisy multi-modal input and reduce the influence of
variations on navigation policy. We evaluate our method in simulated and
real-world environments. Experiments show that our method outperforms the
baselines by a large margin and achieves robust navigation performance with
varying working conditions.Comment: Accepted by ICRA 202
Key Guessing Strategies for Linear Key-Schedule Algorithms in Rectangle Attacks
When generating quartets for the rectangle attacks on ciphers with linear key-schedule, we find the right quartets which may suggest key candidates have to satisfy some nonlinear relations. However, some quartets generated always violate these relations, so that they will never suggest any key candidates. Inspired by previous rectangle frameworks, we find that guessing certain key cells before generating quartets may reduce the number of invalid quartets. However, guessing a lot of
key cells at once may lose the benefit from the early abort technique, which may lead to a higher overall complexity. To get better tradeoff, we build a new rectangle framework on ciphers with linear key-schedule with the purpose of reducing overall complexity or attacking more rounds.
In the tradeoff model, there are many parameters affecting the overall complexity, especially for the choices of the number and positions of key guessing cells before generating quartets. To identify optimal parameters, we build a uniform automatic tool on SKINNY as an example, which includes the optimal rectangle distinguishers for key-recovery phase, the number and positions of guessing key cells before generating quartets, the size of key counters to build that affecting the exhaustive search step, etc. Based on the automatic tool, we identify a 32-round key-recovery attack on SKINNY-128-384 in the related-key setting, which extends the best previous attack by 2 rounds. For other versions with n-2n or n-3n, we also achieve one more round than before. In addition, using the previous rectangle distinguishers, we achieve better attacks on round-reduced ForkSkinny, Deoxys-BC-384 and GIFT-64. At last, we discuss the conversion of our rectangle framework from related-key setting into single-key setting and give new single-key rectangle attack on 10-round Serpent
Mix-keying or desirability-matching in the construction of forced-choice measures? an empirical investigation and practical recommendations
Forced-choice (FC) measures are becoming increasingly popular as an alternative to single-statement (SS) measures. However, to ensure the practical usefulness of an FC measure, it is crucial to address the tension between psychometric properties and faking resistance by balancing mixed keying and social desirability matching. It is currently unknown from an empirical perspective whether the two design criteria can be reconciled, and how they impact respondent reactions. By conducting a two-wave experimental design, we constructed four FC measures with varying degrees of mixed-keying and social desirability matching from the same statement pool and investigated their differences in terms of psychometric properties, faking resistance, and respondent reactions. Results showed that all FC measures demonstrated comparable reliability and induced similar respondent reactions. FC measures with stricter social desirability matching were more faking resistant, while FC measures with more mixed keyed blocks had higher convergent validity with SS measures and displayed similar discriminant and criterion-related validity profiles as the SS benchmark. More importantly, we found that it is possible to strike a balance between social desirability matching and mixed keying, such that FC measures can have adequate psychometric properties and faking resistance. A 7-step recommendation and a tutorial based on the autoFC R package were provided to help readers construct their own FC measures
Investigation of Volumetric Modulated Arc Therapy Dosimetry: from Planning to Delivery
Volumetric modulated arc therapy (VMAT) for cancer treatment uses high-energy radiation to kill malignant cells. The general goal is to deliver a high and conformal dose to the target while minimizing dose to organs-at-risk. This thesis focuses on two areas in VMAT: developing high quality treatment plans and assessing the dosimetric impact of delivering pre-designed plans to patients whose anatomy and position change during treatment. Firstly, a quantitative assessment was made by comparing prostate plans optimized with and without a planning target volume upper dose constraint. It was found that removing the target dose uniformity requirement resulted in better rectum sparing and improved tumor control probability. Secondly, the impact of body contour changes on dose distributions for prostate and head and neck VMAT plans was examined. Rules of thumb for dose percentage change and isodose line shift were developed and body contour changes unlikely to require further investigations were addressed
In vitro activities of six antifungal agents and their combinations against Chaetomium spp.
Impairment of Th cell response in Card9 knockout mice with cutaneous mucormycosis caused by Rhizopus arrhizus
Effect of biochar on biochemical properties of saline soil and growth of rice
To amend physical properties of coastal saline soil for rice production, six biochar treatments (0, 0.5, 1, 2, 4 and 6 kg biochar per m2 soil) were set up as CK, T1, T2, T3, T4 and T5, respectively and their effect on the biochemical properties of coastal saline soil and rice growth characteristics were evaluated in a barrel planting experiment. The results showed that compared with CK (with no biochar added), the soil EC of T1 and T2-T5 was reduced by 11.5 %, but increased by 8.8–62.9 %, respectively. The available potassium and organic matter contents of T1-T5 increased ranging from 3.7-10.2 % to 8.0–46.8 %, respectively. With the increase of the biochar amount, the urease activity of soil in the 0–10 cm deep soil showed an increasing trend by 194.8–744.6 % with T1-T5, compared with that of the CK treatment. The activity of alkaline phosphatase in soil increased first and then decreased, and its increment with T1-T5 was between 28.2 and 64.8 % in comparison with that of CK. With more biochar added to soil, the leaf dry weight, root dry weight, total dry matter mass, total root length, single panicle quality and weight per 100 grains showed a trend of increase first and then decrease. The highest incremental values of all measurements were obtained with T1 by 21.8 %, 23.9 %, 13.8 %, 33.9 %, 30.8 % and 11.6 % respectively, compared with those with CK. However, adding biochar in soil demonstrated insignificant effect on the weight of single panicle, panicle length, stem thickness, tillers, setting rate, soil hydrolyzable nitrogen, available phosphorus content, rice protein, amylose, and taste quality among all treatments. In summary, the application of 0.5 kg m−2 biochar can improve the biochemical properties of saline soil and therefore increase rice yield
sj-docx-1-orm-10.1177_10944281241229784 - Supplemental material for Mixed-Keying or Desirability-Matching in the Construction of Forced-Choice Measures? An Empirical Investigation and Practical Recommendations
Supplemental material, sj-docx-1-orm-10.1177_10944281241229784 for Mixed-Keying or Desirability-Matching in the Construction of Forced-Choice Measures? An Empirical Investigation and Practical Recommendations by Mengtong Li, Bo Zhang, Lingyue Li, Tianjun Sun and Anna Brown in Organizational Research Methods</p
Predicting Erectile Dysfunction after Highly Conformal, Hypofractionated Radiotherapy to the Prostate
Background: Erectile dysfunction (ED) is common after prostate cancer treatment. It has been studied for conventional radiotherapy, but associations in the hypofractionated radiotherapy context are less clear. This study aimed to determine which factors are predicted for worsening ED after highly conformal, modestly hypofractionated radiotherapy to the prostate. Methods: Two hundred and twelve patients treated with 6000 cGy in twenty fractions across four centers were included in this study. Demographic, clinical, and dosimetry factors were then evaluated for post-treatment declines in erectile function using logistic regression and an explainable machine learning-based neural network. Results: 212 patients with a median follow-up of 3.6 years were evaluated. A total of 104 (49%) patients received androgen deprivation therapy. Prior to treatment, 52 (25%) patients were on ED medication. Mean doses to the penile bulb, penile crus, and penile shaft were 2490 (IQR: 1529–3656) cGy, 2095 (1306–3036) cGy, and 444 (313–650) cGy, respectively. Fifty-nine (28%) patients had a worsening of ED after treatment. On multivariable analysis, only the mean dose to the penile shaft [OR >345 vs. ≤345: 4.47 (1.43–13.99); p = 0.010] and pretreatment use of ED medication [OR yes vs. no: 12.5 (5.7–27.5; p < 0.001)] predicted for worsening ED. The neural network confirmed that the penile shaft mean dose and pre-treatment ED medication use are the most important factors in predicting ED. Conclusions: Pre-treatment ED and penile shaft dosimetry are important predictors for ED after hypofractionated radiotherapy for prostate cancer