The fundamental plane of blazars based on the black hole spin-mass energy

We examine the fundamental plane of 91 Blazars which include FSRQs and BL Lacs with known X-ray luminosity ($L_{R}$), radio luminosity ($L_X$), and black hole mass measurements ($M$) to reflect the relationship between jet and accretion for blazars. The fundamental plane of Blazars are log$L_{R}$=${0.273}_{+0.059}^{-0.059}$log$L_X$+${0.695}_{+0.191}^{-0.191}$log$M$+${25.457}_{+2.728}^{-2.728}$ and log$L_{R}$=${0.190}_{+0.049}^{-0.049}$log$L_X$+${0.475}_{+0.157}^{-0.157}$log$M$+${28.568}_{+2.245}^{-2.245}$ after considering the effect of beam factor. Our results suggest that the jet of blazars has connection with accretion. We set the black hole spin energy as a new variable to correct the black hole mass and explore the effect of black hole spin on the fundamental relationship. We find that the fundamental plane of Blazars is effected by the black hole spin, which is similar to the previous work for AGNs. We additionally examine a new fundamental plane which is based on the black hole spin-mass energy ($M_{spin}$). The new fundamental plane (log$L_{R}$=${0.332}_{+0.081}^{-0.081}$log$L_X$+${0.502}_{+0.091}^{-0.091}$log$M_{spin}$+${22.606}_{+3.346}^{-3.346}$ with R-Square=0.575) shows that $M_{spin}$ has a better correlation coefficient comparing to the $M$ for fundamental plane of Blazars. These results support that the black hole spin should be considered as a important factor for the study of fundamental plane for Blazars. And these may further our understanding of the Blandford-Znajek process in blazars.Comment: Accepted for publication in MNRA

Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling

Weakly-supervised action localization aims to recognize and localize action instancese in untrimmed videos with only video-level labels. Most existing models rely on multiple instance learning(MIL), where the predictions of unlabeled instances are supervised by classifying labeled bags. The MIL-based methods are relatively well studied with cogent performance achieved on classification but not on localization. Generally, they locate temporal regions by the video-level classification but overlook the temporal variations of feature semantics. To address this problem, we propose a novel attention-based hierarchically-structured latent model to learn the temporal variations of feature semantics. Specifically, our model entails two components, the first is an unsupervised change-points detection module that detects change-points by learning the latent representations of video features in a temporal hierarchy based on their rates of change, and the second is an attention-based classification model that selects the change-points of the foreground as the boundaries. To evaluate the effectiveness of our model, we conduct extensive experiments on two benchmark datasets, THUMOS-14 and ActivityNet-v1.3. The experiments show that our method outperforms current state-of-the-art methods, and even achieves comparable performance with fully-supervised methods.Comment: Accepted to ICCV 2023. arXiv admin note: text overlap with arXiv:2203.15187, arXiv:2003.12424, arXiv:2104.02967 by other author

Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach

MTHFR Gene Polymorphism Association With Psoriatic Arthritis Risk and the Efficacy and Hepatotoxicity of Methotrexate in Psoriasis.

Aims To assess whether MTHFR rs1801131 and rs1801133 SNPs are associated with concomitant psoriatic arthritis (PsA) and investigate the efficacy and hepatotoxicity of MTX in patients with psoriasis in the Han Chinese population. Methods This prospective, single-arm, interventional study recruited a total of 309 patients with psoriasis, 163 with psoriatic arthritis and 146 without psoriatic arthritis, who completed a 12-week MTX treatment and 1,031 healthy controls. Patients' characteristics including age, gender, disease duration, height, weight, smoking status, alcohol consumption, medical history, disease severity and liver function test results were accessed and recorded. Single nucleotide polymorphism (SNP) genotyping of rs1801131 and rs1801133 in the MTHFR gene was performed. Results The rs1801133 CC genotype was more frequent in patients with PsA than those with PsO and healthy controls (42.3% vs. 28.8% vs. 33.1%, p < 0.05). The 90% reduction from baseline PASI score (PASI 90) response rates to MTX were significantly higher in patients with the rs1801133 TT genotype than those with the CT and CC genotype (33.96% vs. 19.31% vs. 14.41%, OR = 2.76, p = 0.006). The rs1801133 CT+TT genotype was more frequent in PsA patients with abnormal liver function than in those with normal liver function (p < 0.05). In addition, patients with the rs1801131 CT genotype had lower PASI 75 response rates to MTX (OR = 0.49, p = 0.01), and lower risk of ALT elevation (OR = 0.46, p = 0.04). Conclusions This study provided some evidence for MTHFR polymorphism association with the risk of PsA and the efficacy and hepatotoxicity of the low-dose MTX in the Chinese population. Given the relatively small sample size and potentially missed diagnosis of PsA, the results from this study warrant further investigation

DNA Polymorphism of Insulin-like Growth Factor-binding Protein-3 Gene and Its Association with Cashmere Traits in Cashmere Goats

Insulin-like growth factor binding protein-3 (IGFBP-3) gene is important for regulation of growth and development in mammals. The present investigation was carried out to study DNA polymorphism by PCR-RFLP of IGFBP-3 gene and its effect on fibre traits of Chinese Inner Mongolian cashmere goats. The fibre traits data investigated were cashmere fibre diameter, combed cashmere weight, cashmere fibre length and guard hair length. Four hundred and forty-four animals were used to detect polymorphisms in the hircine IGFBP-3 gene. A 316-bp fragment of the IGFBP-3 gene in exon 2 was amplified and digested with HaeIII restriction enzyme. Three patterns of restriction fragments were observed in the populations. The frequency of AA, AB and BB genotypes was 0.58, 0.33 and 0.09 respectively. The allelic frequency of the A and B allele was 0.75 and 0.25 respectively. Nucleotide sequencing revealed a C>G transition in the exon 2 region of the IGFBP-3 gene resulting in R158G change which caused the polymorphism. Least squares analysis revealed a significant effect of genotypes on cashmere weight (p0.05). The animals of AB and BB genotypes showed higher cashmere weight, cashmere fibre length and hair length than the animals possessing AA genotype. These results suggested that polymorphisms in the hircine IGFBP-3 gene might be a potential molecular marker for cashmere weight in cashmere goats

Advances in artificial intelligence in thyroid-associated ophthalmopathy

Thyroid-associated ophthalmopathy (TAO), also referred to as Graves’ ophthalmopathy, is a medical condition wherein ocular complications arise due to autoimmune thyroid illness. The diagnosis of TAO, reliant on imaging, typical ocular symptoms, and abnormalities in thyroid function or thyroid-associated antibodies, is generally graded and staged. In recent years, Artificial intelligence(AI), particularly deep learning(DL) technology, has gained widespread use in the diagnosis and treatment of ophthalmic diseases. This paper presents a discussion on specific studies involving AI, specifically DL, in the context of TAO, highlighting their applications in TAO diagnosis, staging, grading, and treatment decisions. Additionally, it addresses certain limitations in AI research on TAO and potential future directions for the field

Urban vegetable production in Beijing, China: current progress, sustainability, and challenges

Urbanization in China has entered a stage of accelerated development that is accompanied by a range of issues concerning resource, ecological and society. Urban vegetable production (UVP), an important part of urban agriculture, has the potential to be an effective countermeasure for dealing with these problems. Here, we review the current state of UVP with its related technology and equipment, and show the major models of UVP in China with three representative implementation cases in Beijing. Through this review, we found the impact of UVP on urban vegetable supply should not be underestimated, while it is still considered as an urban entertainment by public now. Moreover, UVP extension is still limited when compared with China’s urbanization process. We analyze the possible reasons that restrict the development of UVP and give corresponding suggestions to improve it. Considering the scale of urbanization in China, and the potential contribution of UVP to food supply, environmental sustainability and social harmony, there is still much room for UVP development, which will bring opportunities and challenges to the government and scientific researchers

Radiotherapy Suppresses Bone Cancer Pain through Inhibiting Activation of cAMP Signaling in Rat Dorsal Root Ganglion and Spinal Cord

Radiotherapy is one of the major clinical approaches for treatment of bone cancer pain. Activation of cAMP-PKA signaling pathway plays important roles in bone cancer pain. Here, we examined the effects of radiotherapy on bone cancer pain and accompanying abnormal activation of cAMP-PKA signaling. Female Sprague-Dawley rats were used and received tumor cell implantation (TCI) in rat tibia (TCI cancer pain model). Some of the rats that previously received TCI treatment were treated with X-ray radiation (radiotherapy). Thermal hyperalgesia and mechanical allodynia were measured and used for evaluating level of pain caused by TCI treatment. PKA mRNA expression in dorsal root ganglion (DRG) was detected by RT-PCR. Concentrations of cAMP, IL-1β, and TNF-α as well as PKA activity in DRG and the spinal cord were measured by ELISA. The results showed that radiotherapy significantly suppressed TCI-induced thermal hyperalgesia and mechanical allodynia. The level of PKA mRNA in DRG, cAMP concentration and PKA activity in DRG and in the spinal cord, and concentrations of IL-1β and TNF-α in the spinal cord were significantly reduced by radiotherapy. In addition, radiotherapy also reduced TCI-induced bone loss. These findings suggest that radiotherapy may suppress bone cancer pain through inhibition of activation of cAMP-PKA signaling pathway in DRG and the spinal cord

An ensemble deep learning diagnostic system for determining Clinical Activity Scores in thyroid-associated ophthalmopathy: integrating multi-view multimodal images from anterior segment slit-lamp photographs and facial images

BackgroundThyroid-associated ophthalmopathy (TAO) is the most prevalent autoimmune orbital condition, significantly impacting patients’ appearance and quality of life. Early and accurate identification of active TAO along with timely treatment can enhance prognosis and reduce the occurrence of severe cases. Although the Clinical Activity Score (CAS) serves as an effective assessment system for TAO, it is susceptible to assessor experience bias. This study aimed to develop an ensemble deep learning system that combines anterior segment slit-lamp photographs of patients with facial images to simulate expert assessment of TAO.MethodThe study included 156 patients with TAO who underwent detailed diagnosis and treatment at Shanxi Eye Hospital Affiliated to Shanxi Medical University from May 2020 to September 2023. Anterior segment slit-lamp photographs and facial images were used as different modalities and analyzed from multiple perspectives. Two ophthalmologists with more than 10 years of clinical experience independently determined the reference CAS for each image. An ensemble deep learning model based on the residual network was constructed under supervised learning to predict five key inflammatory signs (redness of the eyelids and conjunctiva, and swelling of the eyelids, conjunctiva, and caruncle or plica) associated with TAO, and to integrate these objective signs with two subjective symptoms (spontaneous retrobulbar pain and pain on attempted upward or downward gaze) in order to assess TAO activity.ResultsThe proposed model achieved 0.906 accuracy, 0.833 specificity, 0.906 precision, 0.906 recall, and 0.906 F1-score in active TAO diagnosis, demonstrating advanced performance in predicting CAS and TAO activity signs compared to conventional single-view unimodal approaches. The integration of multiple views and modalities, encompassing both anterior segment slit-lamp photographs and facial images, significantly improved the prediction accuracy of the model for TAO activity and CAS.ConclusionThe ensemble multi-view multimodal deep learning system developed in this study can more accurately assess the clinical activity of TAO than traditional methods that solely rely on facial images. This innovative approach is intended to enhance the efficiency of TAO activity assessment, providing a novel means for its comprehensive, early, and precise evaluation