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Abstract Background Case-based learning (CBL) utilizing three-dimensional (3D) printed hip joint models is a problem-solving teaching method that combines the tactile and visual advantages of 3D-printed models with CBL. This study aims to investigate the impact of integrating 3D printing with CBL on learning developmental dysplasia of the hip (DDH). Methods We conducted a prospective study from 2022 to 2023, including 120 fourth-year clinical medical students at Xuzhou Medical University. Students were randomly allocated into two groups of 60 participants each. The CBL group received conventional CBL teaching methods, while the 3D + CBL group utilized 3D-printed models in conjunction with CBL. Post-teaching, we analyzed and compared the theoretical and practical achievements of both groups. A questionnaire was designed to assess the impact of the educational approach on orthopedic surgery learning. Results The theory scores of the CBL group (62.88 ± 7.98) and 3D + CBL group (66.35 ± 8.85) were significantly different (t = 2.254, P = 0.026); the practical skills scores of the CBL group (57.40 ± 8.80) and 3D + CBL group (63.42 ± 11.14) were significantly different (t = 3.283, P = 0.001). The questionnaire results showed that the 3D + CBL group was greater than the CBL group in terms of hip fundamentals, ability to diagnose cases and plan treatments, interesting teaching content, willingness to communicate with the instructor and satisfaction. Conclusions The integration of 3D printing with case-based learning has yielded positive outcomes in teaching DDH, providing valuable insights into the use of 3D-printed orthopedic models in clinical education.

Abstract Sowing date and soil fertility are very important factors in the overwintering and production performance of alfalfa (Medicago sativa L.), yet there’s a knowledge gap in knowledge on how late-seeded alfalfa responds to phosphorus (P) fertilization. A field study was conducted in Inner Mongolia from 2020 to 2022 using a split-plot design. The main plots consisted of five sowing dates (31 July, 8, 16, and 24 August, and 1 September), while the subplots involved five P application rates (0, 40, 70, 100, and 130 kg P2O5 ha−1). Throughout the growing seasons, the overwintering rate, root traits, forage yield, and yield components were measured. The results revealed a consistent decrease in overwintering ability and productivity with the delayed sowing. This reduction in overwintering rate was mainly due to diminished root traits, while the decrease in forage yield was largely associated with a reduction in plants per square meter. However, P fertilizer application to late-seeded alfalfa demonstrated potential in enhancing the diameter of both the crown and taproot, thus strengthening the root system and improving the overwintering rate, the rate of increase ranges from 11.6 to 49%. This adjustment could also improve the shoots per square meter and mass per shoot, increasing by 9.4–31.3% and 15.0–27.1% respectively in 2 years, which can offset the decline in forage yield caused by late sowing and might even increase the forage yield. Regression and path analysis indicated that alfalfa forage yield is primarily affected by mass per shoot rather than shoots per square meter. This study recommended that the sowing of alfalfa in similar regions of Inner Mongolia should not be later than mid-August. Moreover, applying P fertilizer (P2O5) at 70.6–85.9 kg ha−1 can enhance the forage yield and persistence of late-seeded alfalfa. Therefore, appropriate late sowing combined with the application of P fertilizer can be used as an efficient cultivation strategy for alfalfa cultivation after a short-season crop harvest in arid and cold regions.

With the increasing social pressure and academic competition, the mental health (for convenience, abbreviated as MH) problems of college students are becoming increasingly prominent, but there are often challenges that are difficult to accurately predict and intervene in a timely manner. The aim of this article is to address the early warning needs of college students’ MH problems and construct a model that can timely identify the MH problems of college students. The experiment collected MH related data from college students in S city, and analyzed and trained these data using the Long short-term memory (LSTM) network model. By changing the number of hidden layers, learning rate, batch size, and epoch times, the most suitable training effect was achieved. By using the time-series characteristics of the LSTM model, the selected parameters from the experiment can better capture the changing trends of college students’ MH status, thereby improving prediction accuracy. Finally, three stage indicators of low, medium, and high were set up for early warning of the predicted results, in order to effectively and timely take measures. The research results indicated that the constructed model achieved a minimum regularization loss of 0.0674 after training. Finally, the adjusted model was used to predict the test set, with an average accuracy of 0.852 and an average accuracy of 0.906. The LSTM-based MH risk model performed well in predicting college students’ MH problems and could identify potential risk factors in a timely manner.

Abstract Objective In chronic low back pain (CLBP), the relationship between spinal pathologies and paraspinal muscles fat infiltration remains unclear. This study aims to evaluate the relationship between MRI findings and paraspinal muscles morphology and fat infiltration in CLBP patients by quantitative MRI. Methods All the CLBP patients were enrolled from July 2021 to December 2022 in four medical institutions. The cross-sectional area (CSA) and proton density fat fraction (PDFF) of the multifidus (MF) and erector spinae (ES) muscles at the central level of the L4/5 and L5/S1 intervertebral discs were measured. MRI findings included degenerative lumbar spondylolisthesis (DLS), intervertebral disc degeneration (IVDD), facet arthrosis, disc bulge or herniation, and disease duration. The relationship between MRI findings and the paraspinal muscles PDFF and CSA in CLBP patients was analyzed. Results A total of 493 CLBP patients were included in the study (198 females, 295 males), with an average age of 45.68 ± 12.91 years. Our research indicates that the number of MRI findings are correlated with the paraspinal muscles PDFF at the L4/5 level, but is not significant. Moreover, the grading of IVDD is the primary factor influencing the paraspinal muscles PDFF at the L4-S1 level (BES at L4/5=1.845, P

Alfalfa (Medicago sativa. L.) is a globally significant autotetraploid legume forage crop. However, despite its importance, establishing efficient gene editing systems for cultivated alfalfa remains a formidable challenge. In this study, we pioneered the development of a highly effective ultrasonic-assisted leaf disc transformation system for Gongnong 1 alfalfa, a variety widely cultivated in Northeast China. Subsequently, we created a single transcript CRISPR/Cas9 (CRISPR_2.0) toolkit, incorporating multiplex gRNAs, designed for gene editing in Gongnong 1. Both Cas9 and gRNA scaffolds were under the control of the Arabidopsis ubiquitin-10 promoter, a widely employed polymerase II constitutive promoter known for strong transgene expression in dicots. To assess the toolkit’s efficiency, we targeted PALM1, a gene associated with a recognizable multifoliate phenotype. Utilizing the CRISPR_2.0 toolkit, we directed PALM1 editing at two sites in the wild-type Gongnong 1. Results indicated a 35.1% occurrence of editing events all in target 2 alleles, while no mutations were detected at target 1 in the transgenic-positive lines. To explore more efficient sgRNAs, we developed a rapid, reliable screening system based on Agrobacterium rhizogenes-mediated hairy root transformation, incorporating the visible reporter MtLAP1. This screening system demonstrated that most purple visible hairy roots underwent gene editing. Notably, sgRNA3, with an 83.0% editing efficiency, was selected using the visible hairy root system. As anticipated, tetra-allelic homozygous palm1 mutations exhibited a clear multifoliate phenotype. These palm1 lines demonstrated an average crude protein yield increase of 21.5% compared to trifoliolate alfalfa. Our findings highlight the modified CRISPR_2.0 system as a highly efficient and robust gene editing tool for autotetraploid alfalfa.

Abstract Nervous system diseases are among the most common diseases globally, posing a severe threat to patients' quality of life and placing a considerable burden on families and society. With improvements in miniaturization, intelligence, and the safety of biosensors, the combination of machinery and organisms is becoming increasingly common. In neuroscience research, biosensors of different macroscopic dimensions have been uniquely utilized to harness their relevant properties. One‐dimensional (1D) biosensors can achieve in situ real‐time monitoring of neural markers at the subcellular, single‐cell, ex vivo, and in vivo levels, with reduced impacts on organisms. Two‐dimensional (2D) biosensors can monitor the chemical behavior of cells and the neural activity of living animals. They are helpful for objectively identifying the characteristics of cells in response to external stimuli and studying the neural circuits of living animals. Three‐dimensional (3D) biosensors have shown unique advantages in point‐of‐care testing, liquid biopsy, drug screening, and mechanistic research. In clinical practice, brain‐computer interfaces (BCIs) and wearable devices have become important tools for monitoring and treatment. To date, there has been widespread adoption of BCIs in clinical practice. BCIs not only exhibit good efficacy in severe neurological and mental diseases but also provide a method for early diagnosis and treatment of these diseases. Wearable sensor devices can accurately assess the symptoms of movement disorders and play an active role in rehabilitation and treatment. In this review, we summarize the application of advanced biosensors in neuroscience research and clinical practice. The challenges and prospects of biosensors as applied to nervous system diseases under interdisciplinary promotion are also discussed in depth.

Interventional therapy has been widely used in surgeries involving neurology, vasculature, and breasts.Image-guided, robot-assisted interventional therapy significantly enhances surgical precision and safety, emerging as a critical trend in modern interventional surgery. Among various interventional imaging methods, interventional magnetic resonance imaging (i-MRI) stands out due to its excellent soft tissue differentiation, diverse imaging contrasts, ability to yield quantitative data, and no ionizing radiation. However, the challenges facing MRI-guided therapy include the relatively low speed of imaging and the stringent compatibility demands of interventional devices. Advance in the rapid i-MRI techniques and MR-compatible equipment have propelled i-MRI to a pivotal role in clinical applications, encompassing neurological, cardiovascular, prostate, and breast interventions. This review initially provides an overview of the current i-MRI landscape. It then consolidates the application of i-MRI in multiple medical interventions, offering illustrative examples. The article further delves into the obstacles posed by i-MRI, specifically slow imaging speed and the delicate spatiotemporal resolution balance. Ultimately, it envisages the growth potential of i-MRI in multimodal imaging, real-time MRI, and i-MRI-guided interventional robotic surgery.

BackgroundOsteoporosis (OP), affecting millions around the globe, is a prevalent degenerative condition of the bones characterized by a decrease in bone mineral density (BMD) and an increase in bone fragility. A novel anthropometric measure, the Body Roundness Index (BRI), provides a more accurate assessment of body fat distribution compared to traditional metrics. Using data from the National Health and Nutrition Examination Survey (NHANES), this study aims to explore the relationship between BRI and total BMD in U.S. adults aged 20 and above.MethodsData from NHANES (2011–2018) were examined, encompassing 9,295 participants following exclusions. Dual-energy X-ray absorptiometry (DXA) was employed to measure BMD. BRI was calculated using waist circumference (WC) and height. The study accounted for variables such as demographic traits, physical exam results, lab test findings, and survey responses. Weighted multivariable linear regression models and smooth curve fitting methods were utilized to assess the relationship between BRI and total BMD.ResultsThe research found a notable inverse relationship between BRI and total BMD. In the model with full adjustments, an increase of one unit in BRI was linked to a 0.0313 g/cm2 reduction in total BMD (P < 0.0001). Moreover, an inflection point was identified at BRI = 9.5229, where each one-unit rise in BRI beyond this threshold corresponded to a more substantial decrease in total BMD (0.0363 g/cm2). Analysis by subgroups revealed that this negative association was consistent across most demographic and health-related categories.ConclusionsThe results demonstrate a notable inverse relationship between BRI and total BMD, indicating that a higher BRI could be associated with lower BMD and a potentially greater risk of developing OP. This underscores the significance of accounting for body fat distribution in preventing OP and advocates for the use of BRI as a valuable marker for early intervention approaches.

Ischemic stroke poses a significant global health burden, with rapid revascularization treatments being crucial but often insufficient to mitigate ischemia-reperfusion (I/R) injury. Dexmedetomidine (DEX) has shown promise in reducing cerebral I/R injury, but its potential molecular mechanism, particularly its interaction with non-coding RNAs (ncRNAs), remains unclear. This study investigates DEX’s therapeutic effect and potential molecular mechanisms in reducing cerebral I/R injury. A transient middle cerebral artery obstruction (tMACO) model was established to simulate cerebral I/R injury in adult rats. DEX was administered pre-ischemia and post-reperfusion. RNA sequencing and bioinformatic analyses were performed on the ischemic cerebral cortex to identify differentially expressed non-coding RNAs (ncRNAs) and mRNAs. The sequencing results showed 6,494 differentially expressed (DE) mRNA and 2698 DE circRNA between the sham and tMCAO (I/R) groups. Additionally, 1809 DE lncRNA, 763 DE mRNA, and 2795 DE circRNA were identified between the I/R group and tMCAO + DEX (I/R + DEX) groups. Gene ontology (GO) analysis indicated significant enrichment in multicellular biogenesis, plasma membrane components, and protein binding. KEGG analysis further highlighted the potential mechanism of DEX action in reducing cerebral I/R injury, with hub genes involved in inflammatory pathways. This study demonstrates DEX’s efficacy in reducing cerebral I/R injury and offers insights into its brain-protective effects, especially in ischemic stroke. Further research is warranted to fully understand DEX’s neuroprotective mechanisms and its clinical applications.

IntroductioncGMP-dependent protein kinase 1 (PRKG1) has shown to be associated with some tumorigenesis, while the role of PRKG1 in bladder cancer is unclear.MethodsTo investigate the biological and clinical significance of PRKG1 in bladder cancer, we detected the expression of PRKG1 and explored the function of PRKG1 in bladder cancer cells. The PRKG1 transcripts data was downloaded from The Cancer Genome Atlas (TCGA) database, and immunohistochemistry staining was conducted on formalin-fixed paraffin-embedded (FFPE) sample tissues. Relationship between clinical characteristics of patients and expression of PRKG1 was analyzed in FFPE samples, TCGA database, and GSE19423 dataset. PRKG1 was over-expressed, and cell proliferation, migration, invasion, apoptosis, and spheroidizing ability were then detected. Chemosensitivity to cisplatin was detected with cell viability, and half-maximal drug inhibitory concentration (IC50) was calculated. In addition, the relation between PRKG1 expression and the infiltration level of tumor immune cells in tumor microenvironment were analyzed.ResultsThe results showed expression of PRKG1 was lower in bladder cancer, compared with normal tissues both at protein and transcript levels. Lower PRKG1 expression was related to higher tumor grade, T stage, and muscle invasion, also predicted worse overall survival and recurrence free survival in patients treated with Bacillus Calmette–Guerin (BCG) intravesical immunotherapy. Analysis of tumor immune cells infiltration showed lower PRKG1 was associated with non-inflamed tumor microenvironment.ConclusionThe present study firstly identified the anti-tumor role and tumor immune regulatory role of PRKG1, also found loss of PRKG1 could be used as a prognosis factor. The present study provided a potential biomarker and therapy target to bladder cancer.

We discuss the angular dependence of the recently proposed transverse momentum dependent quark and gluon diffractive parton distributions at small-x. We introduce the diffractive versions of the Sivers function and the elliptic gluon Wigner distribution and evaluate them in simple models with gluon saturation and study their geometric scaling properties. We also show that the diffractive version of the linearly polarized gluon distribution identically vanishes to leading order. These distributions enrich the physics opportunities for measuring semi-inclusive diffractive DIS processes at the future electron-ion colliders.

The gaming industry has been greatly impacted by virtual reality (VR), augmented reality (AR), and metaverse which provide immersive and interactive experiences. A detailed summary of the use of VR and AR in game development is given in this paper. It looks at how AR platforms are being developed for environmental simulations, assesses how presence is used in AR location-aware games, and talks about how mobile AR games that rely on image recognition are made. It also explores how VR technology affects gamer satisfaction, how AR is being used to create innovative gameplay and interactive interfaces, and how AR-based interactive training systems are being developed. We dive into the technical underpinnings, examining how VR and AR combine real-world and virtual elements to create innovative gaming experiences. This review attempts to provide insights into the current state of VR and AR in game development as well as the possible future trajectories of these technologies by looking into case studies and new developments. It becomes clear as we navigate this fusion of reality and imagination that VR and AR are more than just technological tools, rather, they are catalysts that are changing the way we interact with and experience games.

The growing interest in the fish farming industry is driven by the depletion of natural fish stocks in the market. However, intensive aquaculture systems, which involve raising fish in artificial tanks and cages, can lead to challenges such as low-quality fish and increased mortality rates, depending on the species being cultivated. To address these issues and maximize yield, this paper proposes a fish quality monitoring system with automatic correction. The system focuses on monitoring and maintaining critical water quality parameters essential for fish growth, including temperature, water level, and pH level. The system comprises an Arduino connected to sensors and a web-based application for data collection and monitoring. Correction devices such as an aquarium heater, a valve, and a water pump are integrated into the system to maintain these parameters at optimal levels for fish development. To assess the system's efficiency and reliability, two fish monitoring setups were compared: one using the proposed controlled system and the other using a traditional setup. Results indicate that the controlled system increased efficiency, reduced stress on fish farmers, decreased fish mortality rates, and improved product quality compared to the traditional setup.

Artificial intelligence and machine learning are essential for the development of IR4.0 due to their ability to analyse vast amounts of data, automate processes, and drive innovation across various sectors. These technologies enable intelligent decision-making, predictive analytics, and automation, leading to increased efficiency, productivity, and competitiveness in the digital age. In IR4.0, AI and ML power smart systems and connected devices, transforming industries. They facilitate the integration of digital, physical, and biological systems, enabling the creation of personalized medicine and medical diagnosis smart manufacturing, self-autonomous driving vehicles, smart cities, and smart home. Hence, this review aims to address the contribution of AI and ML in the development of medical diagnosis, smart manufacturing, smart cars, smart cities, and smart homes as well as to highlight the existing challenges faced by AI and ML in these fields. This review also showcases the relevant prospects of AI and ML applications in the fields mentioned.

Abstract Drought stress has been a key environmental factor affecting plant growth and development. The plant genome is capable of producing long noncoding RNAs (lncRNAs). To better understand white mulberry (Morus alba L.) drought response mechanism, we conducted a comparative transcriptome study comparing two treatments: drought‐stressed (EG) and well‐watered (CK) plants. A total of 674 differentially expressed lncRNAs (DElncRNAs) were identified. In addition, 782 differentially expressed messenger RNAs (DEmRNAs) were identified. We conducted Gene Ontology (GO) and KEGG enrichment analyses focusing on the differential lncRNAs cis‐target genes. The target genes of the DElncRNAs were most significantly involved in the biosynthesis of secondary metabolites. Gene regulatory networks of the target genes involving DElncRNAs–mRNAs–DEmRNAs and DElncRNA–miRNA–DEmRNA were constructed. In the DElncRNAs–DEmRNAs network, 30 DEmRNAs involved in the biosynthesis of secondary metabolites are collocated with 46 DElncRNAs. The interaction between DElncRNAs and candidate genes was identified using LncTar. In summary, quantitative real‐time polymerase chain reaction (qRT‐PCR) validated nine candidate genes and seven target lncRNAs including those identified by LncTar. We predicted that the DElncRNAs–DEmRNAs might recruit microRNAs (miRNAs) to interact with gene regulatory networks under the drought stress response in mulberry. The findings will contribute to our understanding of the regulatory functions of lncRNAs under drought stress and will shed new light on the mulberry–drought stress interactions.

In the field of geosciences, the integration of artificial intelligence is transitioning from perceptual intelligence to cognitive intelligence. The simultaneous utilization of knowledge and data in the geoscience domain is a universally addressed concern. In this paper, based on the interpretability of deep learning models for rock images, rock features such as structure, texture, mineral and macroscopic identification characteristics were selected to extract a rock identification subgraph from the petrographic knowledge graph and carry out rock type similarity reasoning. Comparative experiments were conducted on few-shot learning of rock images under the supervision of rock type similarity knowledge. The results of the few-shot learning comparisons demonstrate that the supervision of rock type similarity knowledge significantly enhances performance. Additionally, rock type similarity knowledge exhibits a marginal effect on improving few-shot learning performance. Given the absence of Chinese word embedding and large-scale Chinese pre-trained language models in the geological domain, graph embedding based on domain-specific knowledge graphs in geosciences can offer computable geoscience knowledge for research dually propelled by data and knowledge.

ObjectivesTo establish a radiomics model for distinguishing between the benign and malignant mammary gland nodules via combining the features from nodule and mammary regions on DCE-MRIMethodsIn this retrospective study, a total of 103 cases with mammary gland nodules (malignant/benign = 80/23) underwent DCE-MRI, and was confirmed by biopsy pathology. Features were extracted from both nodule region and mammary region on DCE-MRI. Three SVM classifiers were built for diagnosis of benign and malignant nodules as follows: the model with the features only from nodule region (N model), with the features only from mammary region (M model) and the model combining the features from nodule region and mammary region (NM model). The performance of models was evaluated with the area under the curve of receiver operating characteristic (AUC).ResultsOne radiomic features is selected from nodule region and 3 radiomic features is selected from mammary region. Compared with N or M model, NM model exhibited the best performance with an AUC of 0.756.ConclusionsCompared with the model only using the features from nodule or mammary region, the radiomics-based model combining the features from nodule and mammary region outperformed in the diagnosis of benign and malignant nodules.

Access control is a security technique that can restrict access to protected resources, and data to only authorized users. In this paper, we design a blockchain-based access control scheme for cloud storage that is enabled by revocation. First, initialize blockchain to generate global parameters, generate complete user encryption keys and decryption keys, and perform data encryption. When the blockchain receives a user’s access request, the authorization contract determines if it is on the revocation list. If not, the key is checked. Then, it determines abnormal access and adds its identity to the revocation list, preventing further access to the database. The access control model is created by combining attribute-based encryption. After the security analysis and operational efficiency test, it can be considered that the model meets the security features, such as IND-CPA security. Regarding the time overhead of generating encryption keys, the computational overhead of this paper is the lowest, and the time required to generate encryption keys for 10 attributes is only 0.09 seconds, and for 100 attributes is only 1.62 seconds, which is better than the performance of the two attribute-based access control schemes, FIFC and AACE. The user access time overhead for 10 to 100 attributes at user encryption time is 1.38, 1.56, 1.98, 2.1, 2.53, 2.76, 3.03, 3.27, 3.66, and 3.94 seconds, respectively. The lowest decryption time consumed ensures data security and a good access experience. This study achieves fine-grained access control while protecting data privacy.

The cold interstellar medium (ISM) as the raw material for star formation is critical to understanding galaxy evolution. It is generally understood that galaxies stop making stars when, in one way or another, they run out of gas. However, here we provide evidence that central spiral galaxies remain rich in atomic gas even if their star formation rate (SFR) and molecular gas fraction have dropped significantly compared to “normal” star-forming galaxies of the same mass. Since H i is sensitive to external processes, here we investigate central spiral galaxies using a combined sample from the Sloan Digital Sky Survey, Arecibo Legacy Fast ALFA survey, and the extended GALEX Arecibo SDSS Survey. After proper incompleteness corrections, we find that the key H i scaling relations for central spirals show significant but regular systematic dependence on stellar mass. At any given stellar mass, the H i gas mass fraction is about constant with changing specific star formation rate (sSFR), which suggests that H i reservoir is ubiquitous in central spirals with any star formation status down to M _* ∼ 10 ^9 M _⊙ . Together with the tight correlation between the molecular gas mass fraction and sSFR for galaxies across a wide range of different properties, it suggests that the decline of SFR of all central spirals in the local Universe is due to the halt of H _2 supply, though there is plenty of H i gas around. These hence provide critical observations of the dramatically different behavior of the cold multiphase ISM, and a key to understand the star formation process and quenching mechanism.

In a companion paper, we present the first spatially resolved polarized image of Sagittarius A* on event horizon scales, captured using the Event Horizon Telescope, a global very long baseline interferometric array operating at a wavelength of 1.3 mm. Here we interpret this image using both simple analytic models and numerical general relativistic magnetohydrodynamic (GRMHD) simulations. The large spatially resolved linear polarization fraction (24%–28%, peaking at ∼40%) is the most stringent constraint on parameter space, disfavoring models that are too Faraday depolarized. Similar to our studies of M87*, polarimetric constraints reinforce a preference for GRMHD models with dynamically important magnetic fields. Although the spiral morphology of the polarization pattern is known to constrain the spin and inclination angle, the time-variable rotation measure (RM) of Sgr A* (equivalent to ≈46° ± 12° rotation at 228 GHz) limits its present utility as a constraint. If we attribute the RM to internal Faraday rotation, then the motion of accreting material is inferred to be counterclockwise, contrary to inferences based on historical polarized flares, and no model satisfies all polarimetric and total intensity constraints. On the other hand, if we attribute the mean RM to an external Faraday screen, then the motion of accreting material is inferred to be clockwise, and one model passes all applied total intensity and polarimetric constraints: a model with strong magnetic fields, a spin parameter of 0.94, and an inclination of 150°. We discuss how future 345 GHz and dynamical imaging will mitigate our present uncertainties and provide additional constraints on the black hole and its accretion flow.

The Event Horizon Telescope observed the horizon-scale synchrotron emission region around the Galactic center supermassive black hole, Sagittarius A* (Sgr A*), in 2017. These observations revealed a bright, thick ring morphology with a diameter of 51.8 ± 2.3 μ as and modest azimuthal brightness asymmetry, consistent with the expected appearance of a black hole with mass M ≈ 4 × 10 ^6 M _⊙ . From these observations, we present the first resolved linear and circular polarimetric images of Sgr A*. The linear polarization images demonstrate that the emission ring is highly polarized, exhibiting a prominent spiral electric vector polarization angle pattern with a peak fractional polarization of ∼40% in the western portion of the ring. The circular polarization images feature a modestly (∼5%–10%) polarized dipole structure along the emission ring, with negative circular polarization in the western region and positive circular polarization in the eastern region, although our methods exhibit stronger disagreement than for linear polarization. We analyze the data using multiple independent imaging and modeling methods, each of which is validated using a standardized suite of synthetic data sets. While the detailed spatial distribution of the linear polarization along the ring remains uncertain owing to the intrinsic variability of the source, the spiraling polarization structure is robust to methodological choices. The degree and orientation of the linear polarization provide stringent constraints for the black hole and its surrounding magnetic fields, which we discuss in an accompanying publication.

Electrical energy is often wasted through human negligence when people do not switch off electrical appliances such as lighting after leaving a place. Such a scenario often happens in a classroom when the last person leaves the class and forgets to switch off the electrical appliances. Such wastage may not be able to be afforded by schools that are limited financially. Therefore, this research proposed a simple and cost-effective system that can analyze whether there is or is not a human presence in the classroom by applying a counter to count the total number of people entering and leaving the classroom based on the sensing signals of a set of dual PIR sensors only and then correlating this to automatically turn on or off the electrical appliances mentioned. The total number of people identified in the classroom is also displayed on an LCD screen. A TRIZ approach is used to support the ideation of the system. The system can switch on several electrical output loads simultaneously when the presence of people is detected and switch them off when there are no people in the classroom. The proposed system can be expanded to be used in homes, offices, and buildings to prevent the high cost of electricity consumption caused by the negligence of people. This enables smarter control of electricity consumption.

Faraday rotation is an important probe of the magnetic fields and magnetized plasma around active galactic nuclei jets. We present a Faraday rotation measure (RM) image of the M87 jet between 85.2 and 101.3 GHz with a resolution of ∼2″ with the Atacama Large Millimeter/submillimeter Array. We found that the RM of the M87 core is (4.5 ± 0.4) × 10 ^4 rad m ^−2 with a low linear polarization fraction of (0.88 ± 0.08)%. The spatial RM gradient in the M87 jet spans a wide range from ∼ −2 × 10 ^4 rad m ^−2 to ∼3 × 10 ^4 rad m ^−2 with a typical uncertainty of 0.3 × 10 ^4 rad m ^−2 . A comparison with previous RM measurements of the core suggests that the Faraday rotation of the core may originate very close to the supermassive black hole. Both an internal origin and an external screen with a rapidly varying emitting source could be possible. As for the jet, the RM gradient indicates a helical configuration of the magnetic field that persists up to the kiloparsec scale. Combined with the kiloparsec-scale RM measurements at lower frequencies, we found that RM is frequency-dependent in the jet. One possible scenario to explain this dependence is that the kiloparsec-scale jet has a trumpet-like shape, and the jet coil unwinds near its end.

Soil seed banks are the main seed reservoirs globally and are critical for the regeneration of grassland plant populations. Grazing often affects the density and diversity of grassland soil seed banks; however, it is not clear how these effects vary on a global scale with grazing intensity, grazing duration, and climatic conditions. Here, we screened 92 independent published articles and performed a meta-analysis of the extracted data. The effects of grazing on four soil seed bank density and diversity indices were analyzed. Four alpha diversity indices, namely Shannon–Wiener, Margalef, Pielou, and Simpson indices, were selected in this study. The Shannon–Wiener index reflects the species complexity of the community. The Margalef index reflects species richness of the seed bank. The Pielou index reflects whether the number of seeds of all species in the seed bank is evenly distributed, and the Simpson’s index reflects the status of dominant plants in the seed bank. We found that grazing significantly decreased the total density of soil seed banks. Perennial plant seed banks were more affected by grazing than annual plant seed banks. Heavy grazing significantly decreased the Margalef index of seed banks, while moderate grazing significantly decreased the Simpson’s alpha diversity index. Long-term grazing (>10 years) had the greatest impact on Simpson’s alpha diversity index, while medium-term grazing (5–10 years) had a significant negative impact on Shannon–Wiener, Margalef, and Pielou indices. In addition, our results show that grazing has a greater effect on seed banks in arid areas than those in temperate areas. Knowledge of climate-specific effects will contribute to understanding the risk of local extinctions in grassland populations and help decision-makers maintain the health of grassland ecosystems.

The properties of the galaxies are tightly connected to their host halo mass and halo assembly history. Accurate measurement of the halo assembly history in observation is challenging but crucial to the understanding of galaxy formation and evolution. The stellar-to-halo mass ratio ( M _* / M _h ) for the centrals has often been used to indicate the halo assembly time t _h,50 of the group, where t _h,50 is the lookback time at which a halo has assembled half of its present-day virial mass. Using mock data from the semi-analytic models, we find that M _* / M _h shows a significant scatter with t _h,50 , with a strong systematic difference between the group with a star-forming central (blue group) and passive central (red group). To improve the accuracy, we develop machine learning models to estimate t _h,50 for galaxy groups using only observable quantities in the mocks. Since star formation quenching will decouple the co-growth of the dark matter and baryon, we train our models separately for blue and red groups. Our models have successfully recovered t _h,50 , within an accuracy of ∼1.09 Gyr. With careful calibrations of individual observable quantities in the mocks with Sloan Digital Sky Survey (SDSS) observations, we apply the trained models to the SDSS Yang et al. groups and derive the t _h,50 for each group for the first time. The derived SDSS t _h,50 distributions are in good agreement with that in the mocks, in particular for blue groups. The derived halo assembly history, together with the halo mass, make an important step forward in studying the halo–galaxy connections in observation.

The first very long baseline interferometry (VLBI) detections at 870 μ m wavelength (345 GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on intercontinental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in 2018 October. The longest-baseline detections approach 11 G λ , corresponding to an angular resolution, or fringe spacing, of 19 μ as. The Allan deviation of the visibility phase at 870 μ m is comparable to that at 1.3 mm on the relevant integration timescales between 2 and 100 s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870 μ m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time.

Quasars are generally divided into jetted radio-loud and nonjetted radio-quiet ones, but why only 10% of quasars are radio-loud has been puzzling for decades. Other than jet-induced phenomena, black hole mass, or Eddington ratio, a prominent difference between jetted and nonjetted quasars has scarcely been detected. Here we show a unique distinction between them, and the mystery of jet launching could be disclosed by a prominent excess of radio emission in extremely stable quasars (ESQs; i.e., type 1 quasars with extremely weak variability in UV/optical over 10 yr). Specifically, we find that >25% of the ESQs are detected by the FIRST/VLASS radio survey, while only ∼6%–8% of the control sample, matched in redshift, luminosity, and Eddington ratio, are radio-detected. The excess of radio detection in ESQs has a significance of 4.4 σ (99.9995%) and predominantly occurs at intermediate radio loudness with R ∼ 10–60. The radio detection fraction of ESQs also tends to increase in the ESQ samples selected with more stringent thresholds. Our results are in contrast to the common view that radio-loud quasars are likely more variable in UV/optical due to jet contribution. New clues/challenges posed by our findings highlight the importance of extensive follow-up observations to probe the nature of jets in ESQs and theoretical studies on the link between jet launching and ESQs. Moreover, our results make ESQs, an essential population that has never been explored, unique targets in the burgeoning era of time domain astronomy, like their opposite counterparts of quasars exhibiting extreme variability or changing-look features.

Supermassive black holes in galaxies spend the majority of their lifetime in the low-luminosity regime, powered by hot accretion flow. Strong winds launched from the hot accretion flow have the potential to play an important role in active galactic nuclei (AGN) feedback. Direct observational evidence for these hot winds with temperatures around 10 keV, has been obtained through the detection of highly ionized iron emission lines with Doppler shifts in two prototypical low-luminosity AGNs, namely M81* and NGC 7213. In this work, we further identify blueshifted H-like O/Ne emission lines in the soft X-ray spectra of these two sources. These lines are interpreted to be associated with additional outflowing components possessing velocity around several 10 ^3 km s ^−1 and lower temperature (∼0.2–0.4 keV). Blueshifted velocity and the X-ray intensity of these additional outflowing components are hard to explain by previously detected hot wind freely propagating to larger radii. Through detailed numerical simulations, we find the newly detected blueshifted emission lines would come from circumnuclear gas shock-heated by the hot wind instead. Hot wind can provide a larger ram pressure force on the clumpy circumnuclear gas than the gravitational force from the central black hole, effectively impeding the black hole accretion of gas. Our results provide strong evidence for the energy and momentum feedback by the hot AGN wind.

We present the first results from the Revealing Low-Luminosity Active Galactic Nuclei (ReveaLLAGN) survey, a JWST survey of seven nearby LLAGNs. We focus on two observations with the Mid-Infrared Instrument (MIRI)’s Medium-Resolution Spectrometer of the nuclei of NGC 1052 and Sombrero (NGC 4594/M104). We also compare these data to public JWST data of higher-luminosity AGNs, NGC 7319 and NGC 7469. JWST clearly separates the AGN spectrum from the galaxy light even in Sombrero, the faintest target in our survey; the AGN components have very red spectra. We find that the emission-line widths in both NGC 1052 and Sombrero increase with increasing ionization potential, with FWHM > 1000 km s ^−1 for lines with ionization potential ≳ 50 eV. These lines are also significantly blueshifted in both LLAGNs. The high-ionization-potential lines in NGC 7319 show neither broad widths nor significant blueshifts. Many of the lower-ionization-potential emission lines in Sombrero show significant blue wings extending >1000 km s ^−1 . These features and the emission-line maps in both galaxies are consistent with outflows along the jet direction. Sombrero has the lowest-luminosity high-ionization-potential lines ([Ne v ] and [O iv ]) ever measured in the mid-infrared, but the relative strengths of these lines are consistent with higher-luminosity AGNs. On the other hand, the [Ne v ] emission is much weaker relative to the [Ne iii ] and [Ne ii ] lines of higher-luminosity AGNs. These initial results show the great promise that JWST holds for identifying and studying the physical nature of LLAGNs.

Electronic tickets (e-tickets) are gradually being adopted as a substitute for paper-based tickets to bring convenience to customers, corporations, and governments. However, their adoption faces a number of practical challenges, such as flexibility, privacy, secure storage, and inability to deploy on IoT devices such as smartphones. These concerns motivate the current research on e-ticket systems, which seeks to ensure the unforgeability and authenticity of e-tickets while simultaneously protecting user privacy. Many existing schemes cannot fully satisfy all these requirements. To improve on the current state-of-the-art solutions, this paper constructs a blockchain-enhanced privacy-preserving e-ticket system for IoT devices, dubbed PriTKT, which is based on blockchain, structure-preserving signatures (SPS), unlinkable redactable signatures (URS), and zero-knowledge proofs (ZKP). It supports flexible policy-based ticket purchasing and ensures user unlinkability. According to the data minimization and revealing principle of GDPR, PriTKT empowers users to selectively disclose subsets of (necessary) attributes to sellers as long as the disclosed attributes satisfy ticket purchasing policies. In addition, benefiting from the decentralization and immutability of blockchain, effective detection and efficient tracing of double spending of e-tickets are supported in PriTKT. Considering the impracticality of existing e-tickets schemes with burdensome ZKPs, we replace them with URS/SPS or efficient ZKP to significantly improve the efficiency of ticket issuing and make it suitable for use on smartphones.