Tribulus terrestris extracts alleviate muscle damage and promote anaerobic performance of trained male boxers and its mechanisms: Roles of androgen, IGF-1, and IGF binding protein-3

AbstractPurposeTo investigate the effects of Tribulus terrestris (TT) extracts on muscle mass, muscle damage, and anaerobic performances of trained male boxers and its mechanisms: roles of plasma androgen, IGF-1, and IGF-1 binding protein-3 (IGFBP-3).MethodsFifteen male boxers were divided into exercise group (E, n = 7) and exercise plus TT group (E + TT, n = 8). The two groups both undertook 3-week high intensity and 3-week high volume trainings separated by a 4-week rest. TT extracts (1250 mg/day) were orally administered by boxers in E + TT group. TT extract compositions were detected by UHPLC–Q-TOF/MS. Before and at the end of the two trainings, muscle mass, anaerobic performance, and blood indicators were explored.ResultsCompared with E group, decreases of plasma CK (1591.50 ± 909.55 vs. 2719.86 ± 832.47 U/L) and IGFBP-3 (3075.53 ± 1072.45 vs. 3950.83 ± 479.25 ng/mL) as well as increases of mean power (MP, 459.42 ± 122.25 vs. 434.60 ± 69.47 W) and MP/body weight (MP/BW, 7.54 ± 0.85 vs. 7.07 ± 1.09 W/kg) were detected in E + TT group after a high intensity training. For high volume training, reduction of IGFBP-3 (2946.38 ± 974.07 vs. 3632.67 ± 470.06 ng/mL) and increases of MP (508.71 ± 103.21 vs. 477.81 ± 49.90 W) and MP/BW (8.24 ± 0.29 vs. 7.52 ± 0.92 W/kg) were detected in E + TT group. Muscle mass, blood levels of testosterone, dihydrotestosterone (DHT), and IGF-1 were unchanged between the two groups.ConclusionTaking 1250 mg capsules containing TT extracts did not change muscle mass and plasma levels of testosterone, DHT, and IGF-1 but significantly alleviated muscle damage and promoted anaerobic performance of trained male boxers, which may be related to the decrease of plasma IGFBP-3 rather than androgen in plasma

MCP: Self-supervised Pre-training for Personalized Chatbots with Multi-level Contrastive Sampling

Personalized chatbots focus on endowing the chatbots with a consistent personality to behave like real users and further act as personal assistants. Previous studies have explored generating implicit user profiles from the user's dialogue history for building personalized chatbots. However, these studies only use the response generation loss to train the entire model, thus it is prone to suffer from the problem of data sparsity. Besides, they overemphasize the final generated response's quality while ignoring the correlations and fusions between the user's dialogue history, leading to rough data representations and performance degradation. To tackle these problems, we propose a self-supervised learning framework MCP for capturing better representations from users' dialogue history for personalized chatbots. Specifically, we apply contrastive sampling methods to leverage the supervised signals hidden in user dialog history, and generate the pre-training samples for enhancing the model. We design three pre-training tasks based on three types of contrastive pairs from user dialogue history, namely response pairs, sequence augmentation pairs, and user pairs. We pre-train the utterance encoder and the history encoder towards the contrastive objectives and use these pre-trained encoders for generating user profiles while personalized response generation. Experimental results on two real-world datasets show a significant improvement in our proposed model MCP compared with the existing methods

Alzheimer Disease is Associated with Isotropic Ocular Enlargement

Recent studies have documented ocular changes in dementia patients, especially Alzheimer Disease (AD). In this study, we explored the change of eye size and eye shape in dementia, including AD patients. The eyeball volume and diameters were estimated via T1-weighted brain magnetic resonance (MR) images in the OASIS-3 database which included 83 AD, 247 non-AD dementiaand 336 normal-aging participants qualified for this study. After adjustment of age, sex, race, apolipoprotein E genotypes, anisotropic ratio and intracranial volume, we observed the eyeball volume of the AD group was significantly larger than both the normal control (6871mm3 vs 6415mm3, p < 0.001) and the non-AD dementia group (6871mm3 vs 6391 mm3, p < 0.001), but there was no difference between the non-AD dementia group and the normal control (6391 mm3 vs 6415mm3, p = 0.795). Similar results were observed for the axial, transverse and vertical length. No group differences were observed in the anisotropic ratio, indicating an isotropic volume increaseconsistent with previous changes induced by the ocular hypertension (OH), which suggested possible elevation of the intraocular pressure (IOP) in AD. In consideration of the recent findings in ocular changes of dementia, our findings emphasize routine eye examinations and eye cares for AD patients in the clinic

A locally active discrete memristor model and its application in a hyperchaotic map

© 2022 Springer Nature Switzerland AG. Part of Springer Nature. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1007/s11071-021-07132-5The continuous memristor is a popular topic of research in recent years, however, there is rare discussion about the discrete memristor model, especially the locally active discrete memristor model. This paper proposes a locally active discrete memristor model for the first time and proves the three fingerprints characteristics of this model according to the definition of generalized memristor. A novel hyperchaotic map is constructed by coupling the discrete memristor with a two-dimensional generalized square map. The dynamical behaviors are analyzed with attractor phase diagram, bifurcation diagram, Lyapunov exponent spectrum, and dynamic behavior distribution diagram. Numerical simulation analysis shows that there is significant improvement in the hyperchaotic area, the quasi-periodic area and the chaotic complexity of the two-dimensional map when applying the locally active discrete memristor. In addition, antimonotonicity and transient chaos behaviors of system are reported. In particular, the coexisting attractors can be observed in this discrete memristive system, resulting from the different initial values of the memristor. Results of theoretical analysis are well verified with hardware experimental measurements. This paper lays a great foundation for future analysis and engineering application of the discrete memristor and relevant the study of other hyperchaotic maps.Peer reviewedFinal Accepted Versio

High MB solution degradation efficiency of FeSiBZr amorphous ribbon with surface tunnels

© 2020 by the authors. The as spun amorphous (Fe78Si9B13)99.5Zr0.5 (Zr0.5) and (Fe78Si9B13)99Zr1 (Zr1) ribbons having a Fenton-like reaction are proved to bear a good degradation performance in organic dye wastewater treatment for the first time by evaluating their degradation efficiency in methylene blue (MB) solution. Compared to the widely studied (Fe78Si9B13)100Zr0 (Zr0) amorphous ribbon for degradation, with increasing cZr (Zr atomic content), the as-spun Zr0, Zr0.5 and Zr1 amorphous ribbons have gradually increased degradation rate of MB solution. According to δc (characteristic distance) of as-spun Zr0, Zr0.5 and Zr1 ribbons, the free volume in Zr1 ribbon is higher Zr0 and Zr0.5 ribbons. In the reaction process, the Zr1 ribbon surface formed the 3D nano-porous structure with specific surface area higher than the cotton floc structure formed by Zr0 ribbon and coarse porous structure formed by Zr0.5 ribbon. The Zr1 ribbon\u27s high free volume and high specific surface area make its degradation rate of MB solution higher than that of Zr0 and Zr0.5 ribbons. This work not only provides a new method to remedying the organic dyes wastewater with high efficiency and low-cost, but also improves an application prospect of Fe-based glassy alloys

Unified Transformer Tracker for Object Tracking

As an important area in computer vision, object tracking has formed two separate communities that respectively study Single Object Tracking (SOT) and Multiple Object Tracking (MOT). However, current methods in one tracking scenario are not easily adapted to the other due to the divergent training datasets and tracking objects of both tasks. Although UniTrack \cite{wang2021different} demonstrates that a shared appearance model with multiple heads can be used to tackle individual tracking tasks, it fails to exploit the large-scale tracking datasets for training and performs poorly on single object tracking. In this work, we present the Unified Transformer Tracker (UTT) to address tracking problems in different scenarios with one paradigm. A track transformer is developed in our UTT to track the target in both SOT and MOT. The correlation between the target and tracking frame features is exploited to localize the target. We demonstrate that both SOT and MOT tasks can be solved within this framework. The model can be simultaneously end-to-end trained by alternatively optimizing the SOT and MOT objectives on the datasets of individual tasks. Extensive experiments are conducted on several benchmarks with a unified model trained on SOT and MOT datasets. Code will be available at https://github.com/Flowerfan/Trackron.Comment: CVPR 202

DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation

Deep learning architecture with convolutional neural network achieves outstanding success in the field of computer vision. Where U-Net has made a great breakthrough in biomedical image segmentation and has been widely applied in a wide range of practical scenarios. However, the equal design of every downsampling layer in the encoder part and simply stacked convolutions do not allow U-Net to extract sufficient information of features from different depths. The increasing complexity of medical images brings new challenges to the existing methods. In this paper, we propose a deeper and more compact split-attention u-shape network, which efficiently utilises low-level and high-level semantic information based on two frameworks: primary feature conservation and compact split-attention block. We evaluate the proposed model on CVC-ClinicDB, 2018 Data Science Bowl, ISIC-2018, SegPC-2021 and BraTS-2021 datasets. As a result, our proposed model displays better performance than other state-of-the-art methods in terms of the mean intersection over union and dice coefficient. More significantly, the proposed model demonstrates excellent segmentation performance on challenging images. The code for our work and more technical details can be found at https://github.com/xq141839/DCSAU-Net

Linking drought indices to impacts in the Liaoning province of China

Drought is an inherent meteorological characteristic of any given region, but is particularly important in China due to its monsoon climate and the “three ladder” landform system. The Chinese government has constructed large-scale water conservation projects since 1949, and developed drought and water scarcity relief frameworks. However, drought still causes huge impacts on water supply, environment and agriculture. China has, therefore, created specialized agencies for drought management called Flood Control and Drought Relief Headquarters, which include four different levels: state, provincial, municipal and county. The impact datasets they collect provide an effective resource for drought vulnerability assessment, and provide validation options for hydro-meteorological indices used in risk assessment and drought monitoring. In this study, we use the statistical drought impact data collected by the Liaoning province Drought Relief Headquarter and meteorological drought indices (Standardized Precipitation Index, SPI and Standard Precipitation Evaporation Index, SPEI) to explore a potential relationship between drought impacts and these indices. The results show that SPI-24 and SPEI-24 are highly correlated to the populations that have difficulties in obtaining drinking water in four out of the six cities studied. Three impacts related to reservoirs and the availability of drinking water for humans and livestock exhibit strong correlations with SPI and SPEI of different accumulated periods. Results reveal that meteorological indices used for drought monitoring and early warning in China can be effectively linked to drought impacts. Further work is exploring how this information can be used to optimize drought monitoring and risk assessment in the whole Liaoning province and elsewhere in China