Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Effects of Resveratrol and Vitamin E From Peanut Seeds and Sprouts on Colorectal Cancer Cells

Resveratrol (RES) and Vitamin E (VE) are anti-cancer active ingredients with relatively high content in peanut seeds and sprouts. This study aimed to determine the synergistic inhibitory effect of RES and VE on colorectal cancer. Using 5-FU as a positive drug control, the effect of RES combined with VE on HCT-8 cells was determined, and cell viability was detected using the cell-counting kit 8 (CCK8) method. Cell morphology changes were observed using optical microscopy. Cell migration ability was evaluated by the scratch test, while cell colonies were determined by the cloning test formation ability. Apoptosis status was assessed by flow cytometry and nuclear staining by DAPI, and the expression level of apoptosis-related proteins was determined by western blotting. Compared with the single component group, the RES combined with VE group significantly inhibited the growth and proliferation of HCT-8 intestinal cancer cells in vitro. The RES combined with VE group had a greater impact on cell morphology changes and cell colony formation and significantly reduced cell migration ability and intestinal cancer cell apoptosis (p < 0.05). Additionally, combined treatment with RES and VE significantly upregulated the expression of pro-apoptotic proteins BAX, caspase-3, caspase-8, and caspase-9, and downregulated the expression of anti-apoptotic protein BCL-2, compared to the single component treatment. RES combined with VE is effective in promoting intestinal cancer cell apoptosis. This study demonstrated the significant positive synergy of RES and VE on HCT-8 cells, providing a new perspective for more effective use of RES.
The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis

It is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the possibility of blastocyst formation, we constructed a nomogram based on range of clinical characteristics to predict blastocyst formation rates in patients with different types of infertility. We divided patients into three groups based on female etiology: a tubal factor group, a polycystic ovary syndrome group, and an endometriosis group. Multiple logistic regression was used to analyze the relationship between patient characteristics and blastocyst formation. Each group of patients was divided into a training set and a validation set. The training set was used to construct the nomogram, while the validation set was used to test the performance of the model by using discrimination and calibration. The area under the curve (AUC) for the three groups indicated that the models performed fairly and that calibration was acceptable in each model.
Trends and Patterns of Antibiotics Use in China’s Urban Tertiary Hospitals, 2016–19

Objectives: This study aimed to identify the trends in antibiotics utilization and patients costs, evaluating the effect of the policy and exploring factors associated with the irrational use of antibiotics. Methods: Based on the Cooperation Project Database of Hospital Prescriptions, data were collected from 89 tertiary hospitals in nine cities in China during 2016–2019. The study sample consisted of prescription records with antibiotics for 3,422,710 outpatient and emergency visits and 26, 118, 436 inpatient hospitalizations. Results: For outpatients, the proportion of treated with antibiotics declined from 14.72 to 13.92% significantly (p < 0.01). The proportion of antibiotic costs for outpatients decreased from 5.79 to 4.45% significantly (p < 0.01). For emergency patients, the proportion of treated with antibiotics increased from 39.31 to 43.45% significantly (p < 0.01). The proportion of antibiotic costs for emergency patients decreased from 36.44 to 34.69%, with no significant change (p = 0.87). For inpatients, the proportion of treated with antibiotics increased from 23.82 to 27.25% significantly (p < 0.01). The proportion of antibiotic costs for outpatients decreased from 18.09 to 17.19% with no statistical significance (p = 0.89). Other β-lactam antibacterials (1,663.03 ten thousand DDD) far exceeded other antibiotics categories. Stablely ranked first, followed by Macrolides, lincosamide and streptogramins (965.74 ten thousand DDD), Quinolone antibacterials (710.42 ten thousand DDD), and β-lactam antibacterials, penicillins (497.01 ten thousand DDD). Conclusions: The proportion of treated with antibiotics for outpatients and inpatients meet the WHO standards. The antibiotics use varied by different survey areas, clinical departments, patient gender, patient age and antibiotics categories. More efforts should focus on improving the appropriateness of antibiotics use at the individual level.
Robot Evolution: Ethical Concerns

Rapid developments in evolutionary computation, robotics, 3D-printing, and material science are enabling advanced systems of robots that can autonomously reproduce and evolve. The emerging technology of robot evolution challenges existing AI ethics because the inherent adaptivity, stochasticity, and complexity of evolutionary systems severely weaken human control and induce new types of hazards. In this paper we address the question how robot evolution can be responsibly controlled to avoid safety risks. We discuss risks related to robot multiplication, maladaptation, and domination and suggest solutions for meaningful human control. Such concerns may seem far-fetched now, however, we posit that awareness must be created before the technology becomes mature.
Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

Background: Patients with acute heart failure (AHF) who require continuous renal replacement therapy (CRRT) have a high risk of in-hospital mortality. It is clinically important to screen high-risk patients using a model or scoring system. This study aimed to develop and validate a simple-to-use nomogram consisting of independent prognostic variables for the prediction of in-hospital mortality in patients with AHF undergoing CRRT. Methods: We collected clinical data for 121 patients with a diagnosis of AHF who underwent CRRT in an AHF unit between September 2011 and August 2020 and from 105 patients in the medical information mart for intensive care III (MIMIC-III) database. The nomogram model was created using a visual processing logistic regression model and verified using the standard method. Results: Patient age, days after admission, lactic acid level, blood glucose concentration, and diastolic blood pressure were the significant prognostic factors in the logistic regression analyses and were included in our model (named D-GLAD) as predictors. The resulting model containing the above-mentioned five factors had good discrimination ability in both the training group (C-index, 0.829) and the validation group (C-index, 0.740). The calibration and clinical effectiveness showed the nomogram to be accurate for the prediction of in-hospital mortality in both the training and validation cohort when compared with other models. The in-hospital mortality rates in the low-risk, moderate-risk, and high-risk groups were 14.46, 40.74, and 71.91%, respectively. Conclusion: The nomogram allowed the optimal prediction of in-hospital mortality in adults with AHF undergoing CRRT. Using this simple-to-use model, the in-hospital mortality risk can be determined for an individual patient and could be useful for the early identification of high-risk patients. An online version of the D-GLAD model can be accessed at https://ahfcrrt-d-glad.shinyapps. io/DynNomapp/. Clinical Trial Registration: www.ClinicalTrials. gov, identifier: NCT0751838.
Versatile Antibacterial Materials: An Emerging Arsenal for Combatting Bacterial Pathogens

Antibacterial materials that prevent bacterial infections and mitigate bacterial virulence have attracted great scientific interests. In recent decades, the bactericidal polymers have been presented as promising candidates to combat bacterial pathogens, mainly based on the construction of bactericidal cationic polymers, functionalization with biocidal agents, and formation of bacterial‐repelling layers. However, these established strategies have inherent disadvantages because they often overlook important features such as their biocompatibility and biosafety, especially for biomedical applications. In recent years, many efforts have been made focusing on the development of multifunctional antibacterial materials to meet the elaborate requirements for medical devices and public hygiene products. Herein the recent advances in developing multifunctional materials for their antibacterial activities together with other functions including “kill‐and‐release” capability, hemocompatibility, cell proliferation promoting properties, and coagulation promoting ability for wound dressing are highlighted. In addition, the outlooks on the remaining challenges that should be addressed in the field of multifunctional antibacterial materials are also described.
Challenges to the Vestibular System in Space: How the Brain Responds and Adapts to Microgravity

In the next century, flying civilians to space or humans to Mars will no longer be a subject of science fiction. The altered gravitational environment experienced during space flight, as well as that experienced following landing, results in impaired perceptual and motor performance—particularly in the first days of the new environmental challenge. Notably, the absence of gravity unloads the vestibular otolith organs such that they are no longer stimulated as they would be on earth. Understanding how the brain responds initially and then adapts to altered sensory input has important implications for understanding the inherent abilities as well as limitations of human performance. Space-based experiments have shown that altered gravity causes structural and functional changes at multiple stages of vestibular processing, spanning from the hair cells of its sensory organs to the Purkinje cells of the vestibular cerebellum. Furthermore, ground-based experiments have established the adaptive capacity of vestibular pathways and neural mechanism that likely underlie this adaptation. We review these studies and suggest that the brain likely uses two key strategies to adapt to changes in gravity: (i) the updating of a cerebellum-based internal model of the sensory consequences of gravity; and (ii) the re-weighting of extra-vestibular information as the vestibular system becomes less (i.e., entering microgravity) and then again more reliable (i.e., return to earth).
Insight Into an Outbreak of Canine Distemper Virus Infection in Masked Palm Civets in China

In August 2019, a suspected outbreak of canine distemper was observed in a masked palm civet farm that also received stray civets and rescued wild civets in Henan Province of China. A virulent canine distemper virus (CDV) strain, named HN19, from vaccinated masked palm civets was the etiologic agent identified in this outbreak using RT-PCR and sequencing of the complete genome. Serological analysis indicated a lower positive rate of CDV-neutralizing antibody in wild civets than in captive civets. Phylogenetic analysis of viral hemagglutinin (H) and the complete genome showed high identities with Rockborn-like strains at the nucleotide (98.7~99.72%) and the closest nucleotide similarity with a strain that killed lesser pandas in China in 1997, but low identities with America-1 strains (vaccine strains). Most importantly, one distinct amino acid exchange in the H protein at position 540 Asp → Gly (D540G), which confers CDV with an improved ability to adapt and utilize the human receptor, was observed in HN19. This study represents the first reported outbreak of a Rockborn-like CDV strain infection in masked palm civets in China. Based on this report, the existence of Rockborn-like strains in Chinese wild animals may not only cause immune failure in captive animals, but may also confer increased zoonotic potential.
Post-Transcriptional Regulation of RseA by Small RNAs RyhB and FnrS in Escherichia coli

RseA is the critical central regulator of the σE-dependent stress response in E. coli and other related bacteria. The synthesis of RseA is controlled at the transcriptional level by several promoters and transcriptional regulators, including σE itself at two σE-dependent promoters: rpoE P and rseA P3. The presence of these two independent polycistrons encoding rseA is potentially redundant. We hypothesized that post-transcriptional control of the rseA P3 transcript was necessary to overcome this redundancy. However, to date, nothing is known about the post-transcriptional control of the rseA P3 transcript. We executed a targeted genetic screen to identify small RNA regulators of the rseA P3 transcript and identified RyhB and FnrS as small RNA activators of the RseA P3 transcript. Through genetic analysis, we confirmed that a direct interaction occurs between RyhB and RseA. We also identified sequences within the 5′ untranslated region (UTR) of RseA that were inhibitory for RseA expression. Point mutations predicted to prevent an interaction between RyhB and RseA resulted in increased RseA expression. Taken together, this suggests that the 5’ UTR of the RseAP3 transcript prevents optimal expression of RseA, preventing redundancy due to RseA expression from the σE-dependent rpoE P, and this is overcome by the stimulatory activity of RyhB and FnrS.
Societal Implications of Forest and Water Body Area Evolution in Czechia and Selected Regions

Land cover evolution is an environmental factor that can be used to characterize forest ecosystem services (FES). This study aims to analyze the change in forest cover and water bodies between 1990 and 2018 in the whole Czech Republic, and in the Central Bohemian and South Moravian regions, and its effects on freshwater provision. Additionally, we attempt to understand the societal implications of water quality, public perception, and environmental investment on natural ecosystems. Forest cover and water body data were obtained from the Corine land cover database, while water quality and investment were compiled from the Czech Statistical Office. Public perceptions on the Czech FES were collected from a national survey. Between 1990 and 2018, forest cover has increased by 3.94% and water bodies by 7.65%; however, from 2014 to 2018, severe droughts were reported that compromised the availability of surface water, presumably on artificial structures, causing an increase in the occupied area. Regarding public perception, respondents with less education, and the older population, obtained an assessment of the low performance of the FES, while the water quality and investment indicate that environmental funding has contributed to improving the quality of outflow water from the wastewater treatment plants, fulfilling all the allowed limits of the urban wastewater treatment directive. Hence, a multidisciplinary approach can help decision makers promote policies that integrate environmental management measures, investment protection, and contribute to sustainable development.
An Integrated Counterfactual Sample Generation and Filtering Approach for SAR Automatic Target Recognition with a Small Sample Set

Although automatic target recognition (ATR) models based on data-driven algorithms have achieved excellent performance in recent years, the synthetic aperture radar (SAR) ATR model often suffered from performance degradation when it encountered a small sample set. In this paper, an integrated counterfactual sample generation and filtering approach is proposed to alleviate the negative influence of a small sample set. The proposed method consists of a generation component and a filtering component. First, the proposed generation component utilizes the overfitting characteristics of generative adversarial networks (GANs), which ensures the generation of counterfactual target samples. Second, the proposed filtering component is built by learning different recognition functions. In the proposed filtering component, multiple SVMs trained by different SAR target sample sets provide pseudo-labels to the other SVMs to improve the recognition rate. Then, the proposed approach improves the performance of the recognition model dynamically while it continuously generates counterfactual target samples. At the same time, counterfactual target samples that are beneficial to the ATR model are also filtered. Moreover, ablation experiments demonstrate the effectiveness of the various components of the proposed method. Experimental results based on the Moving and Stationary Target Acquisition and Recognition (MSTAR) and OpenSARship dataset also show the advantages of the proposed approach. Even though the size of the constructed training set was 14.5% of the original training set, the recognition performance of the ATR model reached 91.27% with the proposed approach.
Monitoring Cropping Intensity Dynamics across the North China Plain from 1982 to 2018 Using GLASS LAI Products

China is a large grain producer and consumer. Thus, obtaining information about the cropping intensity (CI) in cultivated land, as well as understanding the intensified utilization of cultivated land, is important to ensuring an increased grain production and food security for China. This study aims to detect and map the changes in CI over a period of 36 years across China’s core grain-producing area—the North China Plain (NCP)— using remotely sensed leaf area index (LAI) time series data acquired by the Global LAnd Surface Satellite (GLASS) products. We first selected 2132 sample points that consisted entirely, or almost entirely, of cultivated cropland from all pixels; the biennial LAI curves for the sample points were then extracted; the Savitzky–Golay filter and second-order difference algorithm were then applied to reconstruct the biennial LAI curves and obtain the number of peaks in these curves. In addition, the multiple cropping index (MCI) was calculated to represent the CI. Finally, the spatial distribution of the CI of cultivated land on the NCP was mapped from 1982 to 2018 using a geo-statistical kriging approach. Spatially, the results indicate that the CI of cultivated land over the NCP exhibits a distinct spatial pattern that conforms to “high in the south, low in the north”. The single cropping system (SCS) mainly occurred in the higher latitude area ranging from 37.04°N to 42.54°N, and the double cropping system (DCS) mainly existed in the lower latitude area between 31.95°N and 39.97°N. Temporally, the CI increased over the study period, but there were some large fluctuations in CI from 1982 to 1998 and it maintained relatively stable since 2000. Across the NCP, 68.14% of cultivated land experienced a significant increase in CI during the 36-year period, while only 3.87% showed a significant decrease. We also found that, between 1982 and 2018, the northern boundary of the area for DCS underwent a significant westward expansion and northward movement. Our results show a good degree of consistency with statistical data and previous research and also help to improve the reliability of satellite-based identification of CI using low spatial resolution LAI products. The results provide important information that can be used for analyzing and evaluating the rational utilization of cultivated land resources; thus, ensuring food security and realizing agricultural sustainability not only for the NCP, but for China as a whole. These results also highlight the value of satellite remote sensing to the long-term monitoring of cropping intensity at large scales.
HA-Net: A Lake Water Body Extraction Network Based on Hybrid-Scale Attention and Transfer Learning

Due to the large quantity of noise and complex spatial background of the remote sensing images, how to improve the accuracy of semantic segmentation has become a hot topic. Lake water body extraction is crucial for disaster detection, resource utilization, and carbon cycle, etc. The the area of lakes on the Tibetan Plateau has been constantly changing due to the movement of the Earth’s crust. Most of the convolutional neural networks used for remote sensing images are based on single-layer features for pixel classification while ignoring the correlation of such features in different layers. In this paper, the two-branch encoder is presented, which is a multiscale structure that combines the features of ResNet-34 with a feature pyramid network. Secondly, adaptive weights are distributed to global information using the hybrid-scale attention block. Finally, PixelShuffle is used to recover the feature maps’ resolution, and the densely connected block is used to refine the boundary of the lake water body. Likewise, we transfer the best weights which are saved on the Google dataset to the Landsat-8 dataset to ensure that our proposed method is robust. We validate the superiority of Hybrid-scale Attention Network (HA-Net) on two given datasets, which were created by us using Google and Landsat-8 remote sensing images. (1) On the Google dataset, HA-Net achieves the best performance of all five evaluation metrics with a Mean Intersection over Union (MIoU) of 97.38%, which improves by 1.04% compared with DeepLab V3+, and reduces the training time by about 100 s per epoch. Moreover, the overall accuracy (OA), Recall, True Water Rate (TWR), and False Water Rate (FWR) of HA-Net are 98.88%, 98.03%, 98.24%, and 1.76% respectively. (2) On the Landsat-8 dataset, HA-Net achieves the best overall accuracy and the True Water Rate (TWR) improvement of 2.93% compared to Pre_PSPNet, which proves to be more robust than other advanced models.
Optimizing Matching Area for Underwater Gravity-Aided Inertial Navigation Based on the Convolution Slop Parameter-Support Vector Machine Combined Method

This paper focuses on the selection of matching areas in the gravity-aided inertial navigation system. Firstly, the Sobel operator was used in convolution of the gravity anomaly map to obtain the feature map. The convolution slope parameters were constructed by combining the feature map and the gravity anomaly map. The characteristic parameters, such as the difference between convolution rows and columns, convolution variance of the feature map, the pooling difference, and range of the gravity anomaly map, were combined. Based on the support vector machine algorithm, the convolution slope parameter-support vector machine combined method is proposed. Second, we selected the appropriate training sample set and set parameters to verify. The results show that compared with the pre-calibration results, the classification accuracy of the test set is more than 92%, which proves that the convolution slope parameter-support vector machine combined method can effectively distinguish between the suitable and the unsuitable area. Thirdly, we applied this method to another region. The navigation experiment was performed in the split-matching area. The average positioning error was better than 100 m, and the correct rate was more than 90%. The results show that sailing in the selected area can accurately match the trajectory and reduce the positioning error.