Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of dietary Clostridium autoethanogenum protein on the growth, disease resistance, intestinal digestion, immunity and microbiota structure of Litopenaeus vannamei reared at different water salinities

The shortage of fishmeal (FM) resources limits the healthy development of aquaculture. Developing new protein sources to replace FM in aquatic feeds is an effective measure to alleviate this situation. However, the application effect of new protein sources is greatly affected by water salinity, which is an important parameter of aquaculture. In this study, the growth, disease resistance, and intestinal digestion, immunity, and microbiota structure of Litopenaeus vannamei (initial weight: 0.38 ± 0.01 g) fed on Clostridium autoethanogenum protein (CAP) or not at three different water salinities (15 ‰, 30 ‰, and 45 ‰) were compared, aiming to explore the effects of dietary CAP on shrimp when suffering different salinity stresses. The results showed that the growth performance, feed utilization, and survival rate (SR) after pathogen challenge of L. vannamei could be significantly improved by dietary CAP when compared with the control at the same salinity and they were also significantly affected by salinity changes when L. vannamei was fed on the same protein source. With the increase in salinity, obvious upregulation was observed in the activities and gene expression of digestive enzymes both in L. vannamei fed on FM and CAP, with significantly higher levels in L. vannamei fed on CAP than in those fed on FM at the same salinity. Meanwhile, the expression levels of immune genes in the CAP group were significantly higher than those in the FM group at different salinities. The intestinal microbiota analysis showed that CAP could increase the relative abundance of beneficial bacteria and decrease the relative abundance of harmful bacteria in the intestine of L. vannamei at the phylum, family, and genus levels, and it was more affected by salinity changes when compared with FM. Besides, the changes in salinity and protein sources led to different changes in the intestinal microflora function of L. vannamei. In sum, this study indicated that CAP could improve the growth, disease resistance, digestive capacity, and intestinal microflora of L. vannamei with a much more intense immune response and enhance its ability to cope with salinity stress.
Heightened metabolic responses in NK cells from patients with neuroblastoma suggests increased potential for immunotherapy

High risk neuroblastoma is responsible for 15% of deaths in pediatric cancer patients. The introduction of anti-GD2 immunotherapy has significantly improved outcomes but there is still only approximately a 50% 5 year event-free-survival for these children and improvements in treatments are urgently required. Anti-GD2 immunotherapy uses the patients’ own immune system to kill cancer cells. In particular, Natural Killer (NK) cells kill antibody coated tumor cells by a process called antibody dependent cellular cytotoxicity (ADCC). However, our previous work has highlighted metabolic exhaustion of NK cells in circulating blood of adult cancer patients, identifying this as a potential therapeutic target. In this study, we investigated circulating NK cells in patients newly diagnosed with neuroblastoma. We found evidence of activation of NK cells in vivo by the cancer itself. While some evidence of NK cell dysfunction was observed in terms of IFNγ production, most results indicated that the NK cell compartment remained relatively intact. In fact, some aspects of metabolic and functional activities were actually increased in patients compared to controls. Glycolytic responses, which we show are crucial for ADCC, were actually enhanced in patients and CD16, the NK cell receptor that mediates ADCC, was also expressed at high levels in some patients. Overall, the data suggest that patient NK cells could be harvested at diagnosis for subsequent beneficial autologous use during immunotherapy. Enhancing glycolytic capacity of cell therapies could also be a strategic goal of future cell therapies for patients with neuroblastoma and indeed other cancers.
Twistorial Topological Strings and a tt Geometry forN = 2 Theories in 4d

We define twistorial topological strings by considering tt* geometry of the 4d N=2 supersymmetric theories on the Nekrasov-Shatashvili half-Omega background, which leads to quantization of the associated hyperKahler geometries. We show that in one limit it reduces to the refined topological string amplitude. In another limit it is a solution to a quantum Riemann-Hilbert problem involving quantum Kontsevich-Soibelman operators. In a further limit it encodes the hyperKahler integrable systems studied by GMN. In the context of AGT conjecture, this perspective leads to a twistorial extension of Toda. The 2d index of the half-Omega theory leads to the recently introduced index for N=2 theories in 4d. The twistorial topological string can alternatively be viewed, using the work of Nekrasov-Witten, as studying the vacuum geometry of 4d N=2 supersymmetric theories on T^2x I where I is an interval with specific boundary conditions at the two ends.
Transfer-learning-based cloud detection for Zhuhai-1 satellite hyperspectral imagery

The Zhuhai-1 hyperspectral satellite can simultaneously obtain spectral information in 32 spectral bands and effectively obtain accurate information on land features through integrated hyperspectral observations of the atmosphere and land, while the presence of clouds can contaminate remote sensing images. To improve the utilization rate of hyperspectral images, this study investigates the cloud detection method for hyperspectral satellite data based on the transfer learning technique, which can obtain a model with high generalization capability with a small training sample size. In this study, for the acquired Level-1B products, the top-of-atmosphere reflectance data of each band are obtained by using the calibration coefficients and spectral response functions of the product packages. Meanwhile, to eliminate the data redundancy between hyperspectral bands, the data are downscaled using the principal component transformation method, and the top three principal components are extracted as the sample input data for model training. Then, the pretrained VGG16 and ResNet50 weight files are used as the backbone network of the encoder, and the model is updated and trained again using Orbita hyperspectral satellite (OHS) sample data to fine-tune the feature extraction parameters. Finally, the cloud detection model is obtained. To verify the accuracy of the method, the multi-view OHS images are visually interpreted, and the cloud pixels are sketched out as the baseline data. The experimental results show that the overall accuracy of the cloud detection model based on the Resnet50 backbone network can reach 91%, which can accurately distinguish clouds from clear sky and achieve high-accuracy cloud detection in hyperspectral remote sensing images.
Genome-wide analyses using multi-locus models revealed marker-trait associations for major agronomic traits in Sorghum bicolor

Globally, sorghum is the fifth most important cereal crop, and it is a major crop in Ethiopia, where it has a high genetic diversity. The country’s sorghum gene pool contributes significantly to sorghum improvement worldwide. This study aimed to identify genomic regions and candidate genes associated with major agronomic traits in sorghum by using its genetic resources in Ethiopia for a genome-wide association study (GWAS). Phenotypic data of days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT), and grain yield (GY) were collected from a GWAS panel comprising 324 sorghum accessions grown in three environments. SeqSNP, a targeted genotyping method, was used to genotype the panel using 5,000 gene-based single nucleotide polymorphism (SNP) markers. For marker-trait association (MTA) analyses, fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) models were used. In all traits, high phenotypic variation was observed, with broad-sense heritability ranging from 0.32 (for GY) to 0.90 (for PALH). A population structure, principal component analysis, and kinship analysis revealed that the accessions could be divided into two groups. In total, 54 MTAs were identified, 11 of which were detected by both BLINK and farmCPU. MTAs identified for each trait ranged from five (PAWT and GY) to fourteen (PH) representing both novel and previously identified quantitative trait loci (QTLs). Three SNPs were associated with more than one trait, including a SNP within the Sobic.004G189200 gene that was associated with PH and PAWT. Major effect SNP loci, Sbi2393610 (PVE = 23.3%), Sbi10438246 (PVE = 35.2%), Sbi17789352 (PVE = 11.9%) and Sbi30169733 (PVE = 18.9%) on chromosomes 1, 3, 5 and 9 that showed strong association signals for PAWD, DTF, GY and PALH, respectively, were major findings of this study. The SNP markers and candidate genes identified in this study provide insights into the genetic control of grain yield and related agronomic traits, and once validated, the markers could be used in genomics-led breeding.
Tsw – A case study on structure-function puzzles in plant NLRs with unusually large LRR domains

Plant disease immunity heavily depends on the recognition of plant pathogens and the subsequent activation of downstream immune pathways. Nod-like receptors are often crucial in this process. Tsw, a Nod-like resistance gene from Capsicum chinense conferring resistance against Tomato spotted wilt virus (TSWV), belongs to the small group of Nod-like receptors with unusually large LRR domains. While typical protein domain dimensions rarely exceed 500 amino acids due to stability constraints, the LRR of these unusual NLRs range from 1,000 to 3,400 amino acids and contain over 30 LRR repeats. The presence of such a multitude of repeats in one protein is also difficult to explain considering protein functionality. Interactions between the LRR and the other NLR domains (CC, TIR, NBS) take place within the first 10 LRR repeats, leaving the function of largest part of the LRR structure unexplained. Herein we discuss the structural modeling limits and various aspects of the structure-function relation conundrums of large LRRs focusing on Tsw, and raise questions regarding its recognition of its effector NSs and the possible inhibition on other domains as seen in other NLRs.
The joint association of physical activity and sedentary behavior with health-related quality of life among children and adolescents in Mainland China

Objectives The objective of this study was to investigate the joint association of physical activity (PA) and sedentary behavior (SB) with health-related quality of life (HRQoL) among children in Mainland China. Methods Children were randomly recruited from primary, junior, and senior high schools (graders 4–12) in Nanjing municipality of China in this cross-sectional survey in 2018. The outcome variable, HRQoL, was assessed using the validated Chinese version of Child Health Utility 9D (CHU9D-CHN) instrument. PA and SB were measured using a validated Physical Activity Scale and Food Frequency Questionnaire for Chinese school-aged children. The associations of PA and SB with HRQoL were assessed using mixed-effects linear regression models and reported as mean difference (MD) and 95% confidence interval (CI). Results Totally, 4,388 participants completed the survey (response rate = 97.6%). After adjustment for potential confounders and class-level clustering effects, relative to those with insufficient PA and prolonged SB, students with insufficient PA and shortened SB (MD = 0.054, 95%CI = 0.018, 0.089), or children with sufficient PA and prolonged SB (MD = 0.034, 95%CI = −0.030, 0.098), or students with sufficient PA and shortened SB (MD = 0.083, 95%CI = 0.045, 0.120), respectively, reported increased HRQoL scores. Conclusion PA was positively associated with HRQoL, and SB was in negative relation to HRQoL. Furthermore, sufficient PA and shortened SB might exert additive influence on HRQoL among children and adolescents in China. This study has public health implications that PA promotion and SB reduction are encouraged to be considered simultaneously for the purpose to maximally improve HRQoL in population-based behavior intervention campaigns among children and adolescents.
ournal of Statistical Mechanics: J Theory and Experiment Entanglement contour

In the context of characterizing the structure of quantum entanglement in many-body systems, we introduce the entanglement contour, a tool to identify which real-space degrees of freedom contribute, and how much, to the entanglement of a region A with the rest of the system B . The entanglement contour provides a complementary, more reﬁned approach to characterizing entanglement than just considering the entanglement entropy between A and B , with several concrete advantages. We illustrate this in the context of ground states and quantum quenches in fermionic quadratic systems. For instance, in a quantum critical system in D = 1 spatial dimensions, the entanglement contour allows us to determine the central charge of the underlying conformal ﬁeld theory from just a single partition of the system into regions A and B (using the entanglement entropy for the same task requires considering several partitions). In D (cid:2) 2 dimensions, the entanglement contour can distinguish between gapped and gapless phases that obey the same boundary law for entanglement entropy. During a local or global quantum quench, the time-dependent contour provides a detailed account of the dynamics of entanglement, including propagating entanglement waves, which oﬀers a microscopic explanation of the behavior of the entanglement entropy as a function of time.
THE STELLAR POPULATION AND METALLICITY DISTRIBUTION OF THE SOMBRERO GALAXY

Hubble Space Telescope studies of the resolved stellar population of elliptical galaxies have shown that the galaxies form by steady accretion of gas which is all the while forming stars and chemically evolving to a metallicity distribution that is as high as solar composition in the most massive objects that have been analyzed and much lower for low-mass ellipticals. In this paper, we study for the first time the stellar content of an early-type spiral galaxy, the massive disk galaxy, the Sombrero, and NGC 4594. We consider whether the metallicity distribution function (MDF) in the observed field matches that of elliptical galaxies of some luminosity, and what these data imply for the accretion and enrichment model that can be fitted to the MDF. The MDF of NGC 4594 is similar to that of the elliptical galaxy of similar luminosity, NGC 5128. The field we are probing is a combination of the galaxy's bulge and halo.
Black-hole hair loss: learning about binary progenitors from ringdown signals

Perturbed Kerr black holes emit gravitational radiation, which (for the practical purposes of gravitational-wave astronomy) consists of a superposition of damped sinusoids termed quasinormal modes. The frequencies and time constants of the modes depend only on the mass and spin of the black hole—a consequence of the no-hair theorem. It has been proposed that a measurement of two or more quasinormal modes could be used to confirm that the source is a black hole and to test if general relativity continues to hold in ultrastrong gravitational fields. In this paper, we propose a practical approach to testing general relativity with quasinormal modes. We will also argue that the relative amplitudes of the various quasinormal modes encode important information about the origin of the perturbation that caused them. This helps in inferring the nature of the perturbation from an observation of the emitted quasinormal modes. In particular, we will show that the relative amplitudes of the different quasinormal modes emitted in the process of the merger of a pair of nonspinning black holes can be used to measure the component masses of the progenitor binary.
Barriers to Community-Based Primary Health Care Delivery in Urban China: A Systematic Mapping Review

Providing access to a range of basic health services, community-based primary health care (CB-PHC) plays a vital role in achieving the goal of health for all. Driven by a strong political commitment, China’s CB-PHC progress in the past decade has been swift and impressive. However, a well-functioning delivery system for care has yet to be established. This systematic mapping review synthesizes selected evidence on barriers to CB-PHC delivery in urban China and draws lessons for policy development. We performed searches on five electronic databases: CINAHL, MEDLINE, Scopus, Web of Science, and China National Knowledge Infrastructure, and included studies published between 2012 and 2021. The Downs and Black and Critical Appraisal Skills Program checklists were used to assess the quality of eligible papers. We conducted our searches and syntheses following the framework set out in the Primary Health Care Performance Initiative (PHCPI). We synthesized the results of the included studies using a thematic narrative approach and reported according to PRISMA guidelines. Six salient barriers arose from our syntheses of 67 papers: lack of comprehensive health insurance schemes, lack of public awareness, superficial care relationships, gaps in communication, staff shortages and poor training, and second-rate equipment. These barriers are grouped into three subdomains following the PHCPI framework: access, people-centered care, and organization and management. A host of negative impacts of these barriers on community-based health care were also identified. It was not possible to determine clear causes of these barriers from the contributing evidence because of the lack of conceptual frameworks and research methods constraints. Non-eastern regions of China and access-related barriers require further exploration. It follows that, at the national level, the problems are likely more severe than the research suggests.
An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans

Academics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diagnostic solution that may be employed in an epidemiological scenario such as COVID-19. Consequently, this work offers an intelligent medicare system that is an IoT-empowered, deep learning-based decision support system (DSS) for the automated detection and categorization of infectious diseases (COVID-19 and pneumothorax). The proposed DSS system was evaluated using three independent standard-based chest X-ray scans. The suggested DSS predictor has been used to identify and classify areas on whole X-ray scans with abnormalities thought to be attributable to COVID-19, reaching an identification and classification accuracy rate of 89.58% for normal images and 89.13% for COVID-19 and pneumothorax. With the suggested DSS system, a judgment depending on individual chest X-ray scans may be made in approximately 0.01 s. As a result, the DSS system described in this study can forecast at a pace of 95 frames per second (FPS) for both models, which is near to real-time.
Design Requirements for a Monitoring System for a Mobile Hemodialysis Device: Patients’ and Care Partners’ Perspectives

Although mobile hemodialysis treatments have been found to be an effective alternative to current in-center and home-based hemodialysis treatments, many barriers to its successful implementation remain. These barriers include the lack of considering user-centered monitoring protocols. This study investigates 24 patients’ and 12 care partners’ expectations for monitoring procedures for a mobile hemodialysis device. Individual semi-structured interviews were conducted at three locations within the Veterans Affairs Health Care System: Seattle, WA; Nashville, TN; and Louisville, KY. All interviews were transcribed and analyzed using inductive or deductive content analysis approaches. We identified 10 categories of indicators suggesting patients’ needs to receive dialysis treatment and 11 categories of indicators suggesting patients’ successful dialysis treatment. Furthermore, we identified six categories of patients’ and care partners’ design expectations for monitoring procedures. The findings from this study have the potential to guide the development of a monitoring system to help ensure users’ acceptance of future mobile hemodialysis devices.
Granular Change Accuracy: A more accurate performance metric for Dialogue State Tracking

Current community-accepted metrics used to 001 evaluate Dialogue State Tracking (DST) have 002 key weaknesses: they do not assign partial 003 scores and over-penalize for mistakes that occur 004 in earlier turns. Their assumptions about error 005 uniformity leads to inaccurate DST evaluation. 006 We propose a new metric to address this chal-007 lenge — Granular Change Accuracy (GCA) 008 — that evaluates for predicted changes in di-009 alogue state over the entire dialogue history. 010 Our benchmarking shows that GCA mitigates 011 irrelevant traits in predictions; i
Ionospheric Response to Solar Flares Using an Improved Version of SAMI2

Abstract : Solar flare-induced disturbances in the ionosphere can affect the propagation of electromagnetic waves, causing errors in GPS navigation, false radar echoes, and loss of HF radio communications. Accurately modeling the ionospheric response to flares is the first step in predicting, and eventually mitigating their effects. Sami2 is Another Model of the Ionosphere (SAMI2) is a 2-D ionospheric model, which, in its standard form, is ill-suited for studying solar flare effects because it lacks adequate temporal resolution of the solar irradiance, and does not account for photoelectron effects. These deficiencies are addressed, and the modified version is successfully used to model the response to the 28 October, 2003 X17.2 solar flare, along a 2-D hemispheric domain. The response to the flare varied significantly between the low and mid-latitudes, and between high and low altitudes.