More comprehensive facial inversion for more effective expression recognition

Facial expression recognition (FER) plays a significant role in the ubiquitous application of computer vision. We revisit this problem with a new perspective on whether it can acquire useful representations that improve FER performance in the image generation process, and propose a novel generative method based on the image inversion mechanism for the FER task, termed Inversion FER (IFER). Particularly, we devise a novel Adversarial Style Inversion Transformer (ASIT) towards IFER to comprehensively extract features of generated facial images. In addition, ASIT is equipped with an image inversion discriminator that measures the cosine similarity of semantic features between source and generated images, constrained by a distribution alignment loss. Finally, we introduce a feature modulation module to fuse the structural code and latent codes from ASIT for the subsequent FER work. We extensively evaluate ASIT on facial datasets such as FFHQ and CelebA-HQ, showing that our approach achieves state-of-the-art facial inversion performance. IFER also achieves competitive results in facial expression recognition datasets such as RAF-DB, SFEW and AffectNet. The code and models are available at https://github.com/Talented-Q/IFER-master

A meaningful exploration of ofatumumab in refractory NMOSD: a case report

ObjectiveTo report the case of a patient with refractory neuromyelitis optica spectrum disorder (NMOSD), who, despite showing poor response or intolerance to multiple immunosuppressants, was successfully treated with Ofatumumab.Case presentationA 42-year-old female was diagnosed with NMOSD in the first episode of the disease. Despite treatment with intravenous methylprednisolone, immunoglobulin, rituximab and immunoadsorption, together with oral steroids, azathioprine, mycophenolate mofetil and tacrolimus, she underwent various adverse events, such as abnormal liver function, repeated infections, fever, rashes, hemorrhagic shock, etc., and experienced five relapses over the ensuing four years. Finally, clinicians decided to initiate Ofatumumab to control the disease. The patient received 9 doses of Ofatumumab over the next 10 months at customized intervals. Her symptoms were stable and there was no recurrence or any adverse events.ConclusionOfatumumab might serve as an effective and safe alternative for NMOSD patients who are resistant to other current immunotherapies

Long-term nitrogen fertilizer management for enhancing use efficiency and sustainable cotton (Gossypium hirsutum L.)

Optimal management of nitrogen fertilizer profoundly impacts sustainable development by influencing nitrogen use efficiency (NUE) and seed cotton yield. However, the effect of long-term gradient nitrogen application on the sandy loam soil is unclear. Therefore, we conducted an 8-year field study (2014–2021) using six nitrogen levels: 0 kg/hm2 (N0), 75 kg/hm2 (N1), 150 kg/hm2 (N2), 225 kg/hm2 (N3), 300 kg/hm2 (N4), and 375 kg/hm2 (N5). The experiment showed that 1) Although nitrogen application had insignificantly affected basic soil fertility, the soil total nitrogen (STN) content had decreased by 5.71%–19.67%, 6.67%–16.98%, and 13.64%–21.74% at 0-cm–20-cm, 20-cm–40-cm, and 40-cm–60-cm soil layers, respectively. 2) The reproductive organs of N3 plants showed the highest nitrogen accumulation and dry matter accumulation in both years. Increasing the nitrogen application rate gradually decreased the dry matter allocation ratio to the reproductive organs. 3) The boll number per unit area of N3 was the largest among all treatments in both years. On sandy loam, the most optional nitrogen rate was 190 kg/hm2–270 kg/hm2 for high seed cotton yield with minimal nitrogen loss and reduced soil environment pollution

Relevance of Bcl-x expression in different types of endometrial tissues

<p>Abstract</p> <p>Objectives</p> <p>To explore the roles of Bcl-xl and Bcl-xs in the development and progression of endometrial carcinoma, and to analyze the correlation between Bcl-xl and Bcl-xs.</p> <p>Methods</p> <p>RT-PCR and Western-blot assay were applied to detect the expressions of Bcl-xl and Bcl-xs in endometrial tissues of various histomorphologic types.</p> <p>Results</p> <p>The Bcl-xl expression levels of simple and atypical hyperplasia endometrial tissues were not significantly different from that of normal endometrial tissue (both <it>P </it>> 0.05). On contrary, Bcl-xl expression in endometrial carcinoma tissue was significantly higher than the normal endometrial tissue (<it>P </it>= 0.00), which was correlated with the pathological grading of endometrial carcinoma (F = 5.33, <it>P </it>= 0.02). In addition, Bcl-xs mRNA level in simple hyperplasia endometrial tissue had no significant difference compared to that in normal endometrial tissue (<it>P </it>= 0.12), while the levels of atypical hyperplasia and endometrial carcinoma endometrial tissues were significantly different from the normal endometrial tissue (both <it>P </it>= 0.00). Furthermore, level of Bcl-xs mRNA was correlated with the clinical staging and lymph node metastasis of the endometrial carcinoma (<it>P </it>< 0.05). The expressions of Bcl-xl and Bcl-xs were negatively correlated with each other (<it>r </it>= -0.76).</p> <p>Conclusion</p> <p>The abnormal expressions of Bcl-xs and Bcl-xl were one of the molecular mechanisms for the pathogenesis of endometrial carcinoma, and altered ratio between these two might involve in the onset of endometrial carcinoma.</p

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating, and enabling our understanding of natural phenomena at a wide range of spatial and temporal scales, giving rise to a new area of research known as AI for science (AI4Science). Being an emerging research paradigm, AI4Science is unique in that it is an enormous and highly interdisciplinary area. Thus, a unified and technical treatment of this field is needed yet challenging. This work aims to provide a technically thorough account of a subarea of AI4Science; namely, AI for quantum, atomistic, and continuum systems. These areas aim at understanding the physical world from the subatomic (wavefunctions and electron density), atomic (molecules, proteins, materials, and interactions), to macro (fluids, climate, and subsurface) scales and form an important subarea of AI4Science. A unique advantage of focusing on these areas is that they largely share a common set of challenges, thereby allowing a unified and foundational treatment. A key common challenge is how to capture physics first principles, especially symmetries, in natural systems by deep learning methods. We provide an in-depth yet intuitive account of techniques to achieve equivariance to symmetry transformations. We also discuss other common technical challenges, including explainability, out-of-distribution generalization, knowledge transfer with foundation and large language models, and uncertainty quantification. To facilitate learning and education, we provide categorized lists of resources that we found to be useful. We strive to be thorough and unified and hope this initial effort may trigger more community interests and efforts to further advance AI4Science

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial

Background: Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods: We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results: Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions: In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792. Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial.

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial (vol 26, 46, 2022)

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017