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Abstract The C-reactive protein-albumin-lymphocyte (CALLY) index, which integrates albumin, lymphocytes, and C-reactive protein levels, has emerged as a novel method to assess nutritional and inflammatory statuses in patients. This study examined the correlation between the CALLY index and sarcopenia risk using two cohorts: 1804 community dwellers from the NHANES database in the United States and 139 patients from the Department of Gerontology at Kunshan Hospital, China. In the US community cohort, RCS curve analysis was used to examine the non-linear relationship between inflammatory/nutritional markers and sarcopenia, subgroup analysis was also conducted. Logistic regression was employed to evaluate the association between the CALLY index and the risk of sarcopenia in both cohorts. Results demonstrated a significant non-linear relationship between the CALLY index and the risk of sarcopenia (P

We investigated Alongshan virus infection in reindeer in northeastern China. We found that 4.8% of the animals were viral RNA–positive, 33.3% tested positive for IgG, and 19.1% displayed neutralizing antibodies. These findings suggest reindeer could serve as sentinel animal species for the epidemiologic surveillance of Alongshan virus infection.

Malignant tumors are a category of diseases that possess invasive and metastatic capabilities, with global incidence and mortality rates remaining high. In recent years, the pivotal role of fibrosis in tumor progression, drug resistance, and immune evasion has increasingly been acknowledged. Fibrosis enhances the proliferation, migration, and invasion of tumor cells by modifying the composition and structure of the extracellular matrix, thereby offering protection for immune evasion by tumor cells. The activation of cancer-associated fibroblasts (CAFs) plays a significant role in this process, as they further exacerbate the malignant traits of tumors by secreting a variety of cytokines and growth factors. Anti-fibrotic tumor treatment strategies, including the use of anti-fibrotic drugs and inhibition of fibrosis-related signaling pathways such as Transforming Growth Factor-β (TGF-β), have demonstrated potential in delaying tumor progression and improving the effectiveness of chemotherapy, targeted therapy, and immunotherapy. In the future, by developing novel drugs that target the fibrotic microenvironment, new therapeutic options may be available for patients with various refractory tumors.

Abstract Background The incidence of Talaromyces marneffei (T. marneffei) infection has increased in recent years with the development of organ transplantation and the widespread use of immunosuppressive agents. However, the lack of clinical suspicion leading to delay or misdiagnosis is an important reason for the high mortality rate in non-human immunodeficiency virus (HIV) and non-endemic population. Herein, we report a case of disseminated T. marneffei infection in a non-HIV and non-endemic recipient after renal transplant, who initially presented with skin rashes and subcutaneous nodules and developed gastrointestinal bleeding. Case presentation We describe a 54-year-old renal transplantation recipient presented with scattered rashes, subcutaneous nodules and ulcerations on the head, face, abdomen, and right upper limb. The HIV antibody test was negative. The patient had no obvious symptoms such as fever, cough, etc. Histopathological result of the skin lesion sites showed chronic suppurative inflammation with a large number of fungal spores. Subsequent fungal culture suggested T. marneffei infection. Amphotericin B deoxycholate was given for antifungal treatment, and there was no deterioration in the parameters of liver and kidney function. Unfortunately, the patient was soon diagnosed with gastrointestinal bleeding, gastrointestinal perforation and acute peritonitis. Then he rapidly developed multiple organ dysfunction syndrome and abandoned treatment. Conclusions The risk of fatal gastrointestinal bleeding can be significantly increased in kidney transplant patients with T. marneffei infection because of the long-term side effects of post-transplant medications. Strengthening clinical awareness and using mNGS or mass spectrometry technologies to improve the detection rate and early diagnosis of T. marneffei are crucial for clinical treatment in non-HIV and non-endemic population.

Abstract Sarcopenia greatly reduces the quality of life of the elderly, and iron metabolism plays an important role in muscle loss. This study aimed to investigate the association between iron status and sarcopenia. A total of 286 adult patients hospitalized between 2019 and 2021 were included in this study, of which 117 were diagnosed with sarcopenia. Serum iron, total iron binding capacity (TIBC), transferrin, and transferrin saturation levels were compared between groups with and without sarcopenia and were included in the logistic analyses, with significant variables further included in the logistic regression model for the prediction of sarcopenia. Serum iron, TIBC, and transferrin levels decreased significantly in the sarcopenia group (p 65 years (OR 5.40, 95% CI 2.25–12.95), BMI

BackgroundWhen individuals infected with human immunodeficiency virus (HIV) experience pulmonary infections, they often exhibit severe symptoms and face a grim prognosis. Consequently, early, rapid, and accurate pathogen diagnosis is vital for informing effective treatment strategies. This study aimed to use metagenomic next-generation sequencing (mNGS) and targeted mNGS (tNGS) to elucidate the characteristics of pulmonary infections in HIV and non-HIV individuals.MethodsThis study enrolled 90 patients with pulmonary infection at the Department of Infectious Diseases of The First Hospital of Jilin University from June 2022 to May 2023, and they were divided into HIV (n=46) and non-HIV (n=44) infection groups. Their bronchoalveolar lavage fluid (BALF) was collected for mNGS analysis to evaluate the differences in pulmonary infection pathogens, and tNGS detection was performed on BALF samples from 15 HIV-infected patients.ResultsA total of 37 pathogens were identified in this study, including 21 bacteria, 5 fungi, 5 viruses, 5 mycobacteria, and 1 mycoplasma. The sensitivity of mNGS was 78.9% (71/90), which is significantly higher than that of conventional methods (CTM) (39/90, P=1.5E-8). The combination of mNGS with CTM can greatly enhance the sensitivity of pathogen detection. The prevalence of Pneumocystis jirovecii (82.6% vs. 9.1%), cytomegalovirus (CMV) (58.7% vs. 0%), and Epstein-Barr virus (EBV) (17.4% vs. 2.3%) was significantly higher in the HIV infection group than in the non-HIV infection group (P

Abstract Dynamic failure widely exists in rock engineering, such as excavation, blasting, and rockburst. However, the quantitative measurement of the dynamic damage process using experimental methods remains a challenge. In this study, a SHPB modeling technique is established based on Voronoi-based DDA to study the damage evolution of Fangshan granite under dynamic loading. The assessment of cracking along the artificial joints among Voronoi sub-blocks is conducted using the modified contact constitutive law. A calibration procedure has been implemented to investigate the rock dynamic properties quantitatively. The dispersion and damping effect can be effectively eliminated by regular discretization in SHPB bars, based on which the dynamic stress equilibrium can be satisfied. To reproduce the loading rate effect of the dynamic compressive strength, which has been observed in the experiment, a modification strategy considering the influence of the rate effect on the strength meso-parameters is proposed. Using this strategy, the peak stresses of the transmitted waves predicted by DDA match well with those obtained from experiments conducted at different loading rates. The simulation results show that more microcracks are generated and the proportion of tensile cracks decreases as the loading rate increases. Furthermore, the dynamic mechanical behavior and fracturing process have also been discussed and compared with the experiments. The results show that the established SHPB system is a powerful tool for quantitative analysis of rock dynamics problems and can handle more complex problems in the future.

Summary: Background: GST-HG171 is a potent, broad-spectrum, orally bioavailable small-molecule 3C like protease inhibitor that has demonstrated greater potency and efficacy compared to Nirmatrelvir in pre-clinical studies. We aimed to evaluate the efficacy and safety of orally administered GST-HG171 plus Ritonavir in patients with coronavirus disease 2019 (COVID-19) infected with emerging XBB and non-XBB variants. Methods: This randomised, double-blind, placebo-controlled phase 2/3 trial was conducted in 47 sites in China among adult patients with mild-to-moderate COVID-19 with symptoms onset ≤72 h. Eligible patients were randomised 1:1 to receive GST-HG171 (150 mg) plus Ritonavir (100 mg) or corresponding placebo tablets twice daily for 5 days, with stratification factors including the risk level of disease progression and vaccination status. The primary efficacy endpoint was time to sustained recovery of clinical symptoms within 28 days, defined as a score of 0 for 11 COVID-19-related target symptoms for 2 consecutive days, assessed in the modified intention-to-treat (mITT) population. This trial was registered at ClinicalTrials.gov (NCT05656443) and Chinese Clinical Trial Registry (ChiCTR2200067088). Findings: Between Dec 19, 2022, and May 4, 2023, 1525 patients were screened. Among 1246 patients who underwent randomisation, most completed basic (21.2%) or booster (74.9%) COVID-19 immunization, and most had a low risk of disease progression at baseline. 610 of 617 who received GST-HG171 plus Ritonavir and 603 of 610 who received placebo were included in the mITT population. Patients who received GST-HG171 plus Ritonavir showed shortened median time to sustained recovery of clinical symptoms compared to the placebo group (13.0 days [95.45% confidence interval 12.0–15.0] vs. 15.0 days [14.0–15.0], P = 0.031). Consistent results were observed in both SARS-CoV-2 XBB (45.7%, 481/1053 of mITT population) and non-XBB variants (54.3%, 572/1053 of mITT population) subgroups. Incidence of adverse events was similar in the GST-HG171 plus Ritonavir (320/617, 51.9%) and placebo group (298/610, 48.9%). The most common adverse events in both placebo and treatment groups were hypertriglyceridaemia (10.0% vs. 14.7%). No deaths occurred. Interpretation: Treatment with GST-HG171 plus Ritonavir has demonstrated benefits in symptom recovery and viral clearance among low-risk vaccinated adult patients with COVID-19, without apparent safety concerns. As most patients were treated within 2 days after symptom onset in our study, confirming the potential benefits of symptom recovery for patients with a longer duration between symptom onset and treatment initiation will require real-world studies. Funding: Fujian Akeylink Biotechnology Co., Ltd.

When we complete sequential movements with different intentions, we plan our movements and adjust ahead. Such a phenomenon is called anticipatory planning for prior intentions and is known to decline with age. In daily life activities, we often need to consider and plan for multiple demands in one movement sequence. However, previous studies only considered one dimension of prior intentions, either different types of onward actions or different precisions of fit or placement. Therefore, in this study, we investigated anticipatory planning for both extrinsic (movement direction) and intrinsic (fit precision) target-related properties in a computer-based movement task and analyzed the computer cursor movement kinematics of both young and older adults. We found that older people consider and adjust for different properties step-by-step, with movement direction being considered as a prior intention during reach movement and fit precision as a motor constraint during drop movement. The age-related changes in the completion of onward actions are constrained by one’s general cognitive ability, sensorimotor performance and effective motor planning for prior intentions. Age-related decline in motor planning can manifest as counterproductive movement profiles, resulting in suboptimal performance of intended actions.

Abstract Sarcopenia has become a heavy disease burden among the elderly. Lipid metabolism was reported to be involved in many degenerative diseases. This study aims to investigate the association between dysregulated lipid metabolism and sarcopenia in geriatric inpatients. This cross-sectional study included 303 patients aged ≥ 60, of which 151 were diagnosed with sarcopenia. The level of total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY), BMI, and fat percentage, were compared between sarcopenia and non-sarcopenia patients. The Spearman correlation coefficient was used to estimate the association between sarcopenia and the level of lipid metabolism. To determine risk factors related to sarcopenia, a multivariate logistic regression analysis was carried out. Risk prediction models were constructed based on all possible data through principal component analysis (PCA), Logistic Regression (LR), Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGboost). We observed rising prevalence of sarcopenia with increasing age, decreasing BMI, and fat percentage (p

Since its introduction, discontinuous deformation analysis (DDA) has been widely used in different areas of rock mechanics. By dividing large blocks into subblocks and introducing artificial joints, DDA can be applied to rock fracture simulation. However, parameter calibration, a fundamental issue in discontinuum methods, has not received enough attention in DDA. In this study, the parameter calibration of DDA for intact rock is carefully studied. To this end, a subblock DDA with Voronoi tessellation is presented first. Then, a modified contact constitutive law is introduced, in which the tensile and shear meso-strengths are modified to be independent of the bond lengths. This improvement can prevent the unjustified preferential failure of short edges. A method for imposing confining pressure is also introduced. Thereafter, sensitivity analysis is performed to investigate the influence of the calculated parameters and meso-parameters on the mechanical properties of modeled rock. Based on the sensitivity analysis, a unified calibration procedure is suggested for both cases with and without confining pressure. Finally, the calibration procedure is applied to two examples, including a biaxial compression test. The results show that the proposed Voronoi-based DDA can simulate rock fracture with and without confining pressure very well after careful parameter calibration.

Abstract Aiming at the problem of long time‐consuming and low accuracy of existing age estimation approaches, a new age estimation method using Gabor feature fusion, and an improved atomic search algorithm for feature selection is proposed. Firstly, texture features of five scales and eight directions in the face region are extracted by Gabor wavelet transform. The statistical histogram is introduced to encode and fuse the directional index with the largest feature value on Gabor scales. Secondly, a new hybrid feature selection algorithm chaotic improved atom search optimisation with simulated annealing (CIASO‐SA) is presented, which is based on an improved atomic search algorithm and the simulated annealing algorithm. Besides, the CIASO‐SA algorithm introduces a chaos mechanism during atomic initialisation, significantly improving the convergence speed and accuracy of the algorithm. Finally, a support vector machine (SVM) is used to get classification results of the age group. To verify the performance of the proposed algorithm, face images with three resolutions in the Adience dataset are tested. Using the Gabor real part fusion feature at 48 × 48 resolution, the average accuracy and 1‐off accuracy of age classification exhibit a maximum of 60.4% and 85.9%, respectively. Obtained results prove the superiority of the proposed algorithm over the state‐of‐the‐art methods, which is of great referential value for application to the mobile terminals.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron strain was first detected in South Africa in November 2021. Although clinical responses to SARS-CoV-2 depend on host immunity, it remains uncertain how immunosuppression affects subsequent coronavirus disease 2019-related (COVID-19-related) incidence, severity, and mortality, especially with respect to the omicron strain. Conversely, immunosuppressants are often thought to predispose to infection. To explore the associations between host immunity and infection with SARS-CoV-2 omicron variants, here we discuss two groups of immunosuppressed patients: organ transplant recipients, who generally receive exogenous immunosuppressants, and Human Immunodeficiency Virus (HIV)-infected patients, who often have disease-related immunosuppression. In summarizing the clinical features and prognoses of HIV-infected patients and human organ transplant recipients infected with SARS-CoV-2 omicron variants, we provide new insights into the pathogenesis of omicron SARS-CoV-2 and provide a framework for the management of these patients now and in the future.

ABSTRACTIt is critical to determine the real-world performance of vaccines against coronavirus disease 2019 (COVID-19) so that appropriate treatments and policies can be implemented. There was a rapid wave of infections by the Omicron variant in Jilin Province (China) during spring 2022. We examined the effectiveness of inactivated vaccines against Omicron using real-world data from this epidemic. This retrospective case-case study of vaccine effectiveness (VE) examined infected patients who were quarantined and treated from April 16 to June 8, 2022 and responded to an electronic questionnaire. Data were analyzed by univariable and multivariable analyses. A total of 2968 cases with SARS-CoV-2 infections (asymptomatic: 1061, mild disease: 1763, pneumonia: 126, severe disease: 18) were enrolled in the study. Multivariable regression indicated that the risk for pneumonia or severe disease was greater in those who were older or had underlying diseases, but was less in those who received COVID-19 vaccines. Relative to no vaccination, VE against the composite of pneumonia and severe disease was significant for those who received 2 doses (60.1%, 95%CI: 40.0%, 73.5%) or 3 doses (68.1%, 95%CI: 44.6%, 81.7%), and VE was similar in the subgroups of males and females. However, VE against the composite of all three classes of symptomatic diseases was not significant overall, nor after stratification by sex. There was no statistical difference in the VE of vaccines from different manufacturers. The inactivated COVID-19 vaccines protected patients against pneumonia and severe disease from Omicron infection, and booster vaccination enhanced this effect.

Abstract Balance is a common performance but nevertheless an essential part of performance analysis investigations in ski. Many skier pay attention to the training of balance ability in training. Inertial Measurement Unit, as a kind of Multiplex-type human motion capture system, is widely used because of its humanized human-computer interaction design, low energy consumption and more freedom provided by the environment. The purpose of this research is to use sensor to establish a kinematics dataset of balance test tasks extracted from skis to help quantify skier’ balance ability. Perception Neuron Studio motion capture device is used in present. The dataset contains a total of 20 participants’ data (half male) of the motion and sensor data, which is collected at a 100 Hz sampling frequency. To our knowledge, this dataset is the only one that uses a BOSU ball in the balance test. We hope that this dataset will contribute to multiple fields of cross-technology integration in physical training and functional testing, including big-data analysis, sports equipment design and sports biomechanical analysis.

Metasurface holograms, with the capability to manipulate spatial light amplitudes and phases, are considered next-generation solutions for holographic imaging. However, conventional fabrication approaches for meta-atoms are heavily dependent on electron-beam lithography (EBL), a technique known for its expensive and time-consuming nature. In this paper, a polarization-insensitive metasurface hologram is proposed using a cost-effective and rapid nanoimprinting method with titanium dioxide (TiO2) nanoparticle loaded polymer (NLP). Based on a simulation, it has been found that, despite a reduction in the aspect ratio of meta-atoms of nearly 20%, which is beneficial to silicon master etching, NLP filling, and the mold release processes, imaging efficiency can go up to 54% at wavelength of 532 nm. In addition, it demonstrates acceptable imaging quality at wavelengths of 473 and 671 nm. Moreover, the influence of fabrication errors and nanoimprinting material degradation in terms of residual layer thickness, meta-atom loss or fracture, thermal-induced dimensional variation, non-uniform distribution of TiO2 particles, etc., on the performance is investigated. The simulation results indicate that the proposed device exhibits a high tolerance to these defects, proving its applicability and robustness in practice.

We present a dispersion-independent phase stabilized distribution architecture for broadband signal based on photonic microwave phase conjugation. RoF signals are distributed from the central station to each base station via a fiber ring network. The elimination of dispersion-induced optical phase decorrelation is achieved because the backward transmission of the phase-conjugated signal, thus the EVM of the RoF signal is optimized. A proof-of-concept experiment is demonstrated. A distribution of QPSK modulated 23-GHz, 400M Baud RoF signals from the central station to a remote base station is obtained via a fiber optic loop. The demodulated constellation and error vector magnitude with and without dispersion compensation are measured at the remote base station. When we set the length of the fiber loop to 58 km, the EVM is reduced by 8% after dispersion compensation, and the compensated EVM can reach the threshold value of 17.5% specified by 3 GPP for 5G when the received optical power of PD is 4 dBm.

Small magnetic fluctuations ( $B_1/B_0 \sim 10^{-4}$ ) are intrinsically present in a magnetic confinement plasma due to turbulent currents. While the perpendicular transport of particles and heat is typically dominated by fluctuations of the electric field, the parallel stream of plasma is affected by fluttering magnetic field lines. In particular through electrons, this indirectly impacts the turbulence dynamics. Even in low beta conditions, we find that E × B turbulent transport can be reduced by more than a factor 2 when magnetic flutter is included in our validated edge turbulence simulations of L-mode ASDEX Upgrade. The primary reason for this is the stabilization of drift-Alfvén-waves, which reduces the phase shifts of density and temperature fluctuations with respect to potential fluctuations. This stabilization can be qualitatively explained by linear analytical theory and appreciably reinforced by the flutter nonlinearity. As a secondary effect, the steeper temperature gradients and thus higher η _i increase the impact of the ion-temperature-gradient mode on overall turbulent transport. With increasing beta, the stabilizing effect on E × B turbulence increases, balancing the destabilization by induction, until direct electromagnetic perpendicular transport is triggered. We conclude that including flutter is crucial for predictive edge turbulence simulations.

The design of commercially feasible magnetic confinement fusion reactors strongly relies on the reduced turbulent transport in the plasma edge during operation in the high confinement mode (H-mode). We present first global turbulence simulations of the ASDEX Upgrade tokamak edge and scrape-off layer in ITER baseline H-mode conditions. Reasonable agreement with the experiment is obtained for outboard mid-plane measurements of plasma density, electron and ion temperature, as well as the radial electric field. The radial heat transport is underpredicted by roughly 1/3. These results were obtained with the GRILLIX code implementing a transcollisional, electromagnetic, global drift-fluid plasma model, coupled to diffusive neutrals. The transcollisional extensions include neoclassical corrections for the ion viscosity, as well as either a Landau-fluid or free-streaming limited model for the parallel heat conduction. Electromagnetic fluctuations are found to play a critical role in H-mode conditions. We investigate the structure of the significant E × B flow shear, finding both neoclassical components as well as zonal flows. But unlike in L-mode, geodesic acoustic modes are not observed. The turbulence mode structure is mostly that of drift-Alfvén waves. However, in the upper part of the pedestal, it is very weak and overshadowed by neoclassical transport. At the pedestal foot, on the other hand, we find instead the (electromagnetic) kinetic ballooning mode, most clearly just inside the separatrix. Our results pave the way towards predictive simulations of fusion reactors.

The utilisation of numerical process simulation has greatly facilitated the challenging task of liquid composite moulding (LCM) process optimisation, providing ease of solution evaluation at a significantly reduced cost compared to complete reliance on physical prototyping. However, due to the process complexity, such process simulation is still considerably expensive at present. In this paper, cost-saving approaches to minimising the computational cost of simulation-based optimisation for LCM processes are compiled and discussed. Their specific applicability, efficacy, and suitability for various optimisation/moulding scenarios are extensively explored in detail. The comprehensive analysation and assimilation of their operation alongside applicability for the problem domain of interest are accomplished in this paper to further complement and contribute to future simulation-based optimisation capabilities for composite moulding processes. The importance of balancing the cost-accuracy trade-off is also repeatedly emphasised, allowing for substantial cost reductions while ensuring a desirable level of optimization reliability.

Abstract An accurate estimation of schedulable capacity (SC) is especially crucial given the rapid growth of electric vehicles, their new energy charging stations, and the promotion of vehicle‐to‐grid (V2G) technology. In this study, an evaluation approach for a photovoltaic (PV) and storage‐integrated fast charging station is established. The energy relationship between the SC of electric vehicles (EVs), the SC of centralized energy storage, and the PV power generation is constructed to solve for the upward SC and downward SC of the entire charging station based on the detailed explanation of the electrical structure of the PV and storage integrated fast charging station. To facilitate the grid to improve the dispatching efficiency, a strategy for solving the daytime SC is developed. This work uses an actual charging station as the research object for case analysis, and fine‐grained modeling of its component characteristics is finished in order to test the validity and robustness of the model. Four views are used to examine the variable properties and affecting elements of the schedulable capacity: light circumstances, EV load typical scenarios, dispatching interval length, and centralized energy storage configuration.

We proposed an all-optical Ka-band microwave long-distance dissemination system based on an optoelectronic oscillator (OEO). In this system, a single tone with high spectrum purity and low phase noise is excited by an injection-locked OEO, and distributed to the remote site through the fiber loop of the OEO at the same time. The second harmonic of the reference signal modulates the round-tripping optical signal at the local site, which achieves the phase conjugator at the optical domain. At the remote end, the phase-conjugated signal is photomixed with the OEO signal to eliminated the phase offset. The proposed scheme improves the phase noise of the high frequency signal received at the remote site and reduces the photoelectric conversion loss. We demonstrated the transmissions of a 36 GHz frequency-quadrupled RF signal along a 6 km optical fiber loop, and the frequency stability is 1.069 × 10−14/1 s and 3.3 × 10−16/1000 s. The single-sideband (SSB) phase noise of the received signal at the remote site is up to −130 dBc/Hz at 10 kHz offset frequency.

BackgroundCombination therapy of α-receptor blockers (α-RBs) and traditional Chinese medicine external therapy can serve as a treatment of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). α-RBs includes tamsulosin, terazosin and so on and the traditional Chinese medicine external therapy includes needling, moxibustion, acupoint catgut embedding, acupoint application, auricular point sticking and hot medicated compress and so forth. Currently, there is no study in which Bayesian network meta-analysis is applied to making a comparative analysis of efficacy of different combination therapies of α-RBs and traditional Chinese medicine external therapy in the treatment of CP/CPPS. Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.MethodsA document retrieval was conducted in the databases PubMed, Cochrane Library, Embase, Web of science, China National Knowledge Infrastructure, WanFang Data Dissertations of China database, VIP China Science and Technology Journal Database, SinoMed. Literatures were searched for published in biomedical journals concerning clinical study on α-RBs combined with various traditional Chinese medicine external therapies in the treatment of CP/CPPS from inception of database to July 2022. Newest version risks of bias assessment tool (RoB2) was used to assess the risks of bias of studies included in this analysis. Stata 16.0 software and R4.1.3 software were used to make a Bayesian network meta-analysis and charts.Results19 literatures were included involving 1739 patients concerning 12 interventions which were used in the treatment of CP/CPPS. With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. Pain score, voiding score and quality-of-life score are subdomains of the NIH-CPSI total score. With regard to pain score, α-RBs+ moxibustion was most likely to be optimal treatment. In reference to voiding and quality-of-life score, there was no statistically significant difference between the efficacy of various interventions.Conclusionsα-RBs+ needling, α-RBs+ moxibustion and α-RBs+ moxibustion+ auricular point sticking provided relatively good efficacy in the treatment of CP/CPPS. In these treatments, attention should be paid on α-RBs+ needling and α-RBs+ moxibustion which ranked higher many times in the evaluation of various outcome indicators. However, there still were certain limitations in this study, so large-sample clinical randomized control trials with a rigor design following the evidence-based medicine standards need to be conducted to justify the results of this study.Systematic review registration[https://www.crd.york.ac.uk/prospero/], identifier: [CRD42022341824].

BackgroundUnder the wave of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) variant Omicron epidemic, the number of infectious cases has increased dramatically in Jilin Province, China since March 2022.The clinical features and severity of SARS-CoV-2 Omicron variant infection in tuberculosis (TB) patients are not yet clear.MethodsData were obtained from 153 patients with the Omicron variant and TB coinfection and 153 non-TB COVID-19 patients who had been hospitalized at Changchun Infectious Disease Hospital from March to June 2022.ResultsAmong these coinfection patients, 17 patients showed COVID-19-related pneumonia on chest imaging and 11 were diagnosed with severe COVID-19. The median duration of SARS-CoV-2 clearance was 13 days. The negative conversion time was associated with age, COVID-19-related pneumonia and antibody IgG. A higher white blood cell count, a lower lymphocyte percentage, a higher CRP level, and a higher D-dimer level were found in the severe group. Age and increased PCT were individual risk factors for the severity of COVID-19. Compared with the non-TB patients, the coinfection patients had higher severity of COVID-19 and the elder coinfection patients had a longer negative conversion time.ConclusionThis study found an association between age, pneumonia, antibody IgG and RNA negative conversion time in COVID-19 and TB coinfection patients, and age and increased PCT were risk factors for the severity of COVID-19.

Abstract Background This study aimed to assess the accuracy of virtual surgical planning (VSP) in segmental osteotomy in combination with bimaxillary orthognathic surgery with surgery first approach (SFA) by means of three-dimensional (3D) measuring and superimposition, so as to promote the application of digital technology in combined orthodontic-orthognathic treatment. Methods 20 patients treated with segmental osteotomy in combination with bimaxillary orthognathic surgery with SFA from 2018 to 2020 were included. All of them acquired VSP performed by ProPlan CMF 3.0 software (Materialise Corporation, Belgium). The preoperative (T0) 3D model of VSP and the postoperative (T1) 3D model, reconstructed by the cone-beam computed tomography (CBCT) data acquired one week after surgery, were compared by measuring the 3D coordinates of the landmarks as well as 3D model superimposition for deviation analysis. The deviation analysis was achieved by Geomagic Studio 2013 (3D Systems Corporation, USA). The differences which represented the accuracy of VSP were evaluated by the root mean square deviation (RMSD) and the Bland–Altman method. Results There was no statistically significant difference between the 3D coordinates of T1 and T0 (P > 0.05), and the mean overall RMSD was 1.37 mm, within the clinical relevance of 2 mm. The RMSD of sagittal direction (1.76 mm) was greater than that of coronal and vertical directions (1.09 mm and 1.24 mm), and the RMSD of maxillary and mandibular aspects were basically equal (1.30 mm and 1.45 mm). The Bland–Altman method showed the T0 and T1 measurements were in good agreement. The mean RMSD obtained from the deviation analysis was 1.85 mm, within the clinical relevance. Conclusions VSP in segmental osteotomy in combination with bimaxillary orthognathic surgery with SFA proved to acquire accurate outcome in this study.

In recent years, due to the development and widespread utilization of metagenomic sequencing and metabolomics, the relationship between gut microbiota and human cardiovascular diseases (CVDs) has received extensive attention. A growing number of studies have shown a strong relationship between gut microbiota and CVDs, such as coronary atherosclerosis, hypertension (HTN) and heart failure (HF). It has also been revealed that intestinal flora-related metabolites, such as trimethylamine-N-oxide (TMAO), short-chain fatty acids (SCFA) and bile acids (BAs), are also related to the development, prevention, treatment and prognosis of CVDs. In this review, we presented and summarized the recent findings on the relationship between gut microbiota and CVDs, and concluded several currently known gut microbiota-related metabolites and the occurrence and development of CVDs.

Addressing the challenges posed by Saline-Alkali land holds significant promise for optimizing agricultural resources and fostering sustainable agricultural development in affected areas. This study explores the efficacy of coal-based solid waste soil conditioner and vermicompost as mixed-component soil amendments in varying proportions. Through comprehensive field experiments, we investigate the impact of these amendments on soil physicochemical properties, microbial diversity, and the growth of L. chinensis, a grass species native to saline areas. Our findings reveal that the application of vermicompost-based soil amendments effectively reduced soil conductivity and led to noteworthy improvements in the pH of Saline-Alkali soil. Moreover, these amendments demonstrated a marked capacity to enhance soil organic matter and available nutrients, most notably available phosphorus. Concurrently, the introduced soil amendments exhibited a positive influence on soil microbial diversity. A correlation analysis underscores the pivotal roles of soil pH and organic matter in shifting soil microbial communities. In response to amendments, L. chinensis exhibited varying degrees of growth enhancement, with biomass increments ranging from 6.37% to 19.91%. In summary, vermicompost and soil conditioner can improve Saline-Alkali land by supplementing organic matter and effective nutrients, improving pH and conductivity, and regulating microbial community, so as to realize the restoration and improvement of Saline-Alkali land; the greatest improvement was achieved with soil conditioner and vermicompost application rates of 30,000 kg·ha−1 and 15,000 kg·ha−1, respectively. Our results provide robust support for advocating for the integration of vermicompost-based soil amendments in Saline-Alkali land management strategies.

H-enhanced slip planarity is generally explained in terms of H-reducing stacking fault energy in fcc systems. Here, we showed that H-decreasing dislocation line energies can enhance the tendency toward slip planarity in bcc Fe through systematically studying the interaction between H and 1/2 {110} dislocations using the EAM potential for Fe-H systems. It was found that the binding energy of H, the excess H in the atmosphere, and the interaction energy of H increased with edge components, leading to larger decrements in the line energies of the edge and increased mixed dislocations than those of a screw dislocation. The consequence of such interaction patterns is an increment in the energy change in the system when the edge and mixed dislocations are converted to screw dislocations as compared to the H-free cases. The cross-slip in bcc Fe is thus suppressed by H, increasing the tendency toward slip planarity.

Bipolar membranes integrated water dissociation and acid-base generations have great potential in emerging sustainable technologies but remains inefficient. Here, the authors circumvent this inefficiency and instability of the membranes by developing polyaniline shielded catalytic bipolar membranes.

Since its outbreak in Wuhan, Hubei Province China, 2019-coronavirus infected disease (COVID-19) had been widely spread all over the world, the control of which calls for a better understanding of its epidemiology and clinical characteristics. We included 12 confirmed cases of COVID-19 in First Affiliated Hospital of Jilin University from 23 January 2020 to 11 February 2020, which were retrospectively analyzed for epidemiological, demographic, clinical, laboratory, and radiological features. All the patients were confirmed by nucleic acid detection, the average age of whom was 45.25 years (range, 23–79 years). Most patients had a history of Wuhan traveling or had contact with Wuhan travelers or infected cases. Obvious family cluster was observed. Clinical manifestations included fever (12/12), fatigue (10/12), cough (6/12), sore throat (4/12), headache (3/12), and diarrhea (2/12). Only three out of eight patients had pneumonia manifestation on radiography. Most patients had a normal white blood cell (WBC) count and normal or reduced lymphocyte (LY) count. Pneumonia changes were observed in all the four patients who underwent a chest CT scan. Only one elderly patient developed severe pneumonia, while all the rest were mild disease and had a self-limiting course.

This study aimed to analyze the clinical significance of serum ferritin, procalcitonin (PCT), and C-reactive protein (CRP) in patients with hemorrhagic fever with renal syndrome (HFRS). The demographical, clinical, and laboratory data of 373 patients with HFRS in northeastern China were retrospectively analyzed. The levels of serum ferritin and PCT in severe patients (n = 108) were significantly higher than those in mild patients (n = 265, p < 0.001) and associated with HFRS severity. The area under the receiver operating characteristic curve (AUC) values of serum ferritin and PCT for predicting the severity of HFRS were 0.732 (95% CI 0.678–0.786, p < 0.001) and 0.824 (95% CI 0.773–0.875, p < 0.001), respectively, showing sensitivity and specificity of 0.75 and 0.88 for serum ferritin, and 0.76 and 0.60 for PCT. The CRP level in HFRS with bacterial co-infection (n = 115) was higher than that without bacterial co-infection (n = 258, p < 0.001). The AUC value of CRP for predicting bacterial co-infection was 0.588 (95% CI 0.525–0.652, p < 0.001), showing sensitivity and specificity of 0.43 and 0.76, respectively. The serum ferritin level in non-survivors (n = 14) was significantly higher than in survivors (n = 359, p < 0.001). The AUC value of serum ferritin for predicting mortality was 0.853 (95% CI 0.774–0.933, p < 0.001), showing sensitivity and specificity of 0.933 and 0.739. Serum ferritin and PCT have a robust association with HFRS severity and mortality, which may be promising predictors, and CRP is an effective biomarker to assess bacterial co-infection in HFRS.

Abstract Background Invasive fungal pneumonia is a severe infectious disease with high mortality in immunocompromised patients. However, the clinical diagnosis of the pathogen(s) remains difficult since microbiological evidence is difficult to acquire. Case presentation Here, we report a case of pulmonary fungal infection detected by next-generation sequencing (NGS) of bronchoalveolar lavage fluid (BALF) in a 61-year-old male with corticosteroid-treated dermatomyositis. Cytomegalovirus and influenza A virus infections were confirmed by nucleic acid detection and treated with antiviral medicine. The patient had been diagnosed with severe pneumonia and treated with empiric broad-spectrum antibacterial and antifungal drugs before bronchoscopy was performed. The patient responded poorly to those empiric treatments. Three fungi were found by NGS in the BALF, namely, Pneumocystis jirovecii, Aspergillus fumigatus and Rhizopus oryzae. After adjusting the patient’s treatment plan according to the NGS results, he improved significantly. Conclusions This case highlights the combined application of NGS and traditional tests in the clinical diagnosis of pulmonary invasive fungal disease. NGS is proposed as an important adjunctive diagnostic approach for identifying uncommon pathogens.

Abstract The potential of random pattern based computational ghost imaging (CGI) for real-time applications has been offset by its long image reconstruction time and inefficient reconstruction of complex diverse scenes. To overcome these problems, we propose a fast image reconstruction framework for CGI, called “DeepGhost”, using deep convolutional autoencoder network to achieve real-time imaging at very low sampling rates (10–20%). By transferring prior-knowledge from STL-10 dataset to physical-data driven network, the proposed framework can reconstruct complex unseen targets with high accuracy. The experimental results show that the proposed method outperforms existing deep learning and state-of-the-art compressed sensing methods used for ghost imaging under similar conditions. The proposed method employs deep architecture with fast computation, and tackles the shortcomings of existing schemes i.e., inappropriate architecture, training on limited data under controlled settings, and employing shallow network for fast computation.

Convolutional neural networks (CNN) with their deep feature extraction capability have recently been applied in numerous image fusion tasks. However, the image fusion of infrared and visible images leads to loss of fine details and degradation of contrast in the fused image. This deterioration in the image is associated with the conventional “averaging” rule for base layer fusion and relatively large feature extraction by CNN. To overcome these problems, an effective fusion framework based on visual saliency weight map (VSWM) combined with CNN is proposed. The proposed framework first employs VSWM method to improve the contrast of an image under consideration. Next, the fine details in the image are preserved by applying multi-resolution singular value decomposition (MSVD) before further processing by CNN. The promising experimental results show that the proposed method outperforms state-of-the-art methods by scoring the highest over different evaluation metrics such as Q0, multiscale structural similarity (MS_SSIM), and the sum of correlations of differences (SCD).

Recent advances in training monitoring are centered on the statistical indicators of the concentric phase of the movement. However, those studies lack consideration of the integrity of the movement. Moreover, training performance evaluation needs valid data on the movement. Thus, this study presents a full-waveform resistance training monitoring system (FRTMS) as a whole-movement-process monitoring solution to acquire and analyze the full-waveform data of resistance training. The FRTMS includes a portable data acquisition device and a data processing and visualization software platform. The data acquisition device monitors the barbell’s movement data. The software platform guides users through the acquisition of training parameters and provides feedback on the training result variables. To validate the FRTMS, we compared the simultaneous measurements of 30–90% 1RM of Smith squat lifts performed by 21 subjects with the FRTMS to similar measurements obtained with a previously validated three-dimensional motion capture system. Results showed that the FRTMS produced practically identical velocity outcomes, with a high Pearson’s correlation coefficient, intraclass correlation coefficient, and coefficient of multiple correlations and a low root mean square error. We also studied the applications of the FRTMS in practical training by comparing the training results of a six-week experimental intervention with velocity-based training (VBT) and percentage-based training (PBT). The current findings suggest that the proposed monitoring system can provide reliable data for refining future training monitoring and analysis.

Synthetic aperture radar (SAR) image change detection is one of the most important applications in remote sensing. Before performing change detection, the original SAR image is often cropped to extract the region of interest (ROI). However, the size of the ROI often affects the change detection results. Therefore, it is necessary to detect changes using local information. This paper proposes a novel unsupervised change detection framework based on deep learning. The specific method steps are described as follows: First, we use histogram fitting error minimization (HFEM) to perform thresholding for a difference image (DI). Then, the DI is fed into a convolutional neural network (CNN). Therefore, the proposed method is called HFEM-CNN. We test three different CNN architectures called Unet, PSPNet and the designed fully convolutional neural network (FCNN) for the framework. The overall loss function is a weighted average of pixel loss and neighborhood loss. The weight between pixel loss and neighborhood loss is determined by the manually set parameter λ. Compared to other recently proposed methods, HFEM-CNN does not need a fragment removal procedure as post-processing. This paper conducts experiments for water and building change detection on three datasets. The experiments are divided into two parts: whole data experiments and random cropped data experiments. The complete experiments prove that the performance of the method in this paper is close to other methods on complete datasets. The random cropped data experiment is to perform local change detection using patches cropped from the whole datasets. The proposed method is slightly better than traditional methods in the whole data experiments. In experiments with randomly cropped data, the average kappa coefficient of our method on 63 patches is over 3.16% compared to other methods. Experiments also show that the proposed method is suitable for local change detection and robust to randomness and choice of hyperparameters.

Balance ability is one of the important factors in measuring human physical fitness and a common index for evaluating sports performance. Its quality directly affects the coordination ability of human movements and plays an important role in human productive activities. In the field of sports, balance ability is an important indicator of athletes’ selection and training. How to objectively analyze balance performance becomes a problem for every non-professional sports enthusiast. Therefore, in this paper, we used a dataset of lower limb collected by inertial sensors to extract the feature parameters, then designed a RUS Boost classifier for unbalanced data whose basic classifier was SVM model to predict three classifications of balance degree, and, finally, evaluated the performance of the new classifier by comparing it with two basic classifiers (KNN, SVM). The result showed that the new classifier could be used to evaluate the balanced ability of lower limb, and performed higher than basic ones (RUS Boost: 72%; KNN: 60%; SVM: 44%). The results meant the established classification model could be used for and quantitative assessment of balance ability in initial screening and targeted training.

Abstract Background The SK-PN-DW cell line was established in 1979 and is commercially available. Despite the use of this cell line as an in vitro model for functional and therapeutic studies of malignant primitive neuroectodermal tumor (PNET), there is a lack of complete information about the genetic alterations that are present at the cytogenetic level. Thus, the current study aimed to characterize the cytogenetic profile of this cell line. Methods Routine G-banded chromosome analysis, fluorescence in situ hybridization, and oligonucleotide array comparative genomic hybridization assays were performed to characterize the chromosomal changes in this cell line. Results The G-banded karyotype analysis showed that the number of chromosomes in this cell line ranged between 36 and 41. Importantly, all cells displayed a loss of chromosomes Y, 11, 13, and 18. However, some cells showed an additional loss of chromosome 10. Additionally, the observed structural changes indicated: a) unbalanced translocation between chromosomes 1 and 7; b) translocation between chromosomes 11 and 22 at breakpoints 11q24 and 22q12, which is a classical translocation that is associated with Ewing sarcoma; c) a derivative chromosome due to a whole arm translocation between chromosomes 16 and 17 at likely breakpoints 16p10 and 17q10; and d) possible rearrangement in the short arm of chromosome 18. Moreover, a variable number of double minutes were also observed in each metaphase cell. Furthermore, the microarray assay results not only demonstrated genomic-wide chromosomal imbalance in this cell line and precisely placed chromosomal breakpoints on unbalanced, rearranged chromosomes, but also revealed information about subtle chromosomal changes and the chromosomal origin of double minutes. Finally, the fluorescence in situ hybridization assay confirmed the findings of the routine cytogenetic analysis and microarrays. Conclusion The accurate determination of the cytogenetic profile of the SK-PN-DW cell line is helpful in enabling the research community to utilize this cell line for future identity and comparability studies, in addition to demonstrating the utility of the complete cytogenetic profile, as a public resource.

A Fourier single-pixel imaging technique based on lateral inhibition is proposed to improve the reconstruction contrast and quality for low-contrast scenes. The mathematical models are developed, and corresponding simulations and experiments are conducted to verify and evaluate the features. Results show that this strategy strengthens the image contrast and structural similarity index mainly under low sampling ratios compared with the traditional Fourier single-pixel imaging. It offers an optional solution for various Fourier single-pixel imaging applications at low sampling ratios for low-contrast scenes.

Depth edge represents contours of depth images. However, captured images often have low resolution. Furthermore, conventional edge detection methods fail to handle depth images with low resolution. To cater depth images with low resolution, we propose a novel edge detection method with high accuracy and computational speed. The proposed method modifies the local binary pattern and selects an adaptive threshold to obtain a rough edge map. Then, it removes irrelevant edges to obtain the result. Experimental results show that the proposed method can rapidly acquire accurate depth edge maps and is applicable to depth images with low resolution. The proposed method is compared with and outperforms other renowned edge detection methods.

A retina-like 3-D (three-dimensional) computational ghost imaging (R-3DCGI) is proposed to obtain high resolution while maintaining high imaging efficiency. R-3DCGI models are developed, and corresponding simulations are conducted to verify and evaluate the accuracy and features of the R-3DCGI. Results show that the models obtain rotation and scaling invariances and compress redundant information, thereby improving imaging efficiency over the traditional computational ghost imaging. The relationships between parameters of the retina-like models and signal-noise ratio are discussed to optimize the retina-like structures in various applications.

Highly conductive anion-exchange membranes (AEMs) are desirable for applications in various energy storage and conversion technologies. However, conventional AEMs with bulky HCO3- or Br- as counterion generally exhibit low conductivity because the covalent bonding restrains the tethered cationic group’s mobility and rotation. Here, we report an alternative polyrotaxane AEM with nontethered and free-shuttling phosphonium cation. As proved by temperature-dependent NMR, solid-state NMR, and molecular dynamics simulation, the phosphonium cation possesses a thermally trigged shuttling behavior, broader extension range, and greater mobility, thus accelerating the diffusion conduction of bulky anions. Owing to this striking feature, high HCO3- conductivity of 105 mS cm-1 at 90°C was obtained at a relatively lower ion-exchange capacity of 1.17 mmol g-1. This study provides a new concept for developing highly conductive anion-exchange membranes and will catalyze the exploration of new applications for polyrotaxanes in ion conduction processes.

Antimicrobial peptides are a type of small-molecule peptide that widely exist in nature and are components of the innate immunity of almost all living things. They play an important role in resisting foreign invading microorganisms. Antimicrobial peptides have a wide range of antibacterial activities against bacteria, fungi, viruses and other microorganisms. They are active against traditional antibiotic-resistant strains and do not easily induce the development of drug resistance. Therefore, they have become a hot spot of medical research and are expected to become a new substitute for fighting microbial infection and represent a new method for treating drug-resistant bacteria. This review briefly introduces the source and structural characteristics of antimicrobial peptides and describes those that have been used against common clinical microorganisms (bacteria, fungi, viruses, and especially coronaviruses), focusing on their antimicrobial mechanism of action and clinical application prospects.

Biofilms are communities of microorganisms that are attached to a biological or abiotic surface and are surrounded by a self-produced extracellular matrix. Cells within a biofilm have intrinsic characteristics that are different from those of planktonic cells. Biofilm resistance to antimicrobial agents has drawn increasing attention. It is well-known that medical device- and tissue-associated biofilms may be the leading cause for the failure of antibiotic treatments and can cause many chronic infections. The eradication of biofilms is very challenging. Many researchers are working to address biofilm-related infections, and some novel strategies have been developed and identified as being effective and promising. Nevertheless, more preclinical studies and well-designed multicenter clinical trials are critically needed to evaluate the prospects of these strategies. Here, we review information about the mechanisms underlying the drug resistance of biofilms and discuss recent progress in alternative therapies and promising strategies against microbial biofilms. We also summarize the strengths and weaknesses of these strategies in detail.

Building change detection using remote sensing images is significant to urban planning and city monitoring. The height information extracted from very high resolution (VHR) satellite stereo images provides valuable information for the detection of 3D changes in urban buildings. However, most existing 3D change detection algorithms are based on the independent segmentation of two-temporal images and the feature fusion of spectral change and height change. These methods do not consider 3D change information and spatial context information simultaneously. In this paper, we propose a novel building change detection algorithm based on 3D Co-segmentation, which makes full use of the 3D change information contained in the stereoscope data. An energy function containing spectral change information, height change information, and spatial context information is constructed. Image change feature is extracted using morphological building index (MBI), and height change feature is obtained by robust normalized digital surface models (nDSM) difference. 3D Co-segmentation divides the two-temporal images into the changed foreground and unchanged background through the graph-cut-based energy minimization method. The object-to-object detection results are obtained through overlay analysis, and the quantitative height change values are calculated according to this correspondence. The superiority of the proposed algorithm is that it can obtain the changes of buildings in planar and vertical simultaneously. The performance of the algorithm is evaluated in detail using six groups of satellite datasets. The experimental results prove the effectiveness of the proposed building change detection algorithm.

Abstract Background Bacterial small regulatory RNAs (sRNAs) play important roles in sensing environment changes through sRNA-target mRNA interactions. However, the current strategy for detecting sRNA-mRNA interactions usually combines bioinformatics prediction and experimental verification, which is hampered by low prediction accuracy and low-throughput. Additionally, among the 4736 sequenced bacterial genomes, only about 2164 sRNAs from 319 strains have been described. Furthermore, target mRNAs of only 157 sRNAs have been uncovered. Obviously, highly efficient methods were required to detect sRNA-mRNA interactions in the sequenced genomes. This study aimed to apply a modified CLASH (cross-linking, ligation and sequencing hybrids) method to detect RNA-RNA interactions in E. coli, a model bacterial organism. Results Statistically significant interactions were detected in 29 transcript pairs. To the best of our knowledge, 24 pairs were reported for the first time and were novel RNA interactions, including tRNA-tRNA, tRNA-ncRNA (non-coding RNA), tRNA-rRNA, rRNA-mRNA, rRNA-ncRNA, rRNA-rRNA, rRNA-IGT (intergenic transcript), and tRNA-IGT interactions. Conclusions Discovery of novel RNA-RNA interactions in the present study demonstrates that RNA-RNA interactions might be far more complicated than ever expected. New methods may be required to help discover more novel RNA-RNA interactions. The present work describes a high-throughput protocol not only for discovering new RNA interactions, but also directly obtaining base-pairing sequences, which should be useful in assessing RNA structure and interactions.

Condensed matter physics: intrinsic magnetism emerges in graphene quantum dots A local magetic moment emerges in nanoscale high purity graphene quantum dots, probably resulting from edge passivation. A team led by Nujiang Tang at Nanjing University synthesized high purity graphene quantum dots with an average diameter of about 2.04 nm and average height of about 0.52 nm. They found that a local moment of 1.2 µB were carried by spin polarized edge state appearing in a small number of quantum dots at 2K, with the likely origin from hydroxyl passivation on carbon. The majority dots are nonmagnetic due to the suppression of edge magnetism by defects or reconstruction at the edge. These results may provide insights into the intrinsic magnetism of graphene quantum dots and pave a way towards edge magnetism by various chemical passivation.

The road extraction task is mainly composed of two subtasks, namely, road detection and road centerline extraction. As the road detection task and road centerline extraction task are strongly correlated, in this paper, we introduce a multitask learning framework to detect roads and extract road centerlines simultaneously. For the road centerline extraction problem, existing works rely either on regression-based methods, or classification-based methods. The regression-based methods suffer from slow convergence and unsatisfactory local solutions. The classification-based methods ignore the fact that the closer the pixel is to the centerline, the higher our tolerance for its misclassification. To overcome these problems, we first convert the road centerline extraction problem into the problem of discrete normalized distance label prediction, which can be resolved by training an ordinal regressor. For the road extraction task, most of the previous studies apply pixel-wise loss function, for example, Cross-Entropy loss, which is not sufficient, as the road has special topology characteristics such as connectivity. Therefore, we propose a road-topology loss function to improve the connectivity and completeness of the extracted road. The road-topology loss function has two key characteristics: (i) The road-topology loss function combines road detection prediction and road centerline extraction prediction to promote the two subtasks to each other by using the correlation between the two subtasks; (ii) The road-topology loss can emphatically penalize gaps that often appear in road detection results and spurious segments that easily appear in centerline extraction results. In this paper, we select the AdamW optimizer to minimize the road-topology loss. Since there is no public dataset, we build a road extraction dataset to evaluate our method. State-of-the-art semantic segmentation networks (LinkNet34, DLinkNet34, DeeplabV3plus) are used as baseline methods to compare with two kinds of method. The first kind of method modifies the baseline method by adding the road centerline extraction task branch based on ordinal regression. The second kind of method uses the road topology loss and has the same network architecture as the first kind of method. For the road detection task, the two kinds of methods improve the baseline methods by up to 3.51% and 11.98% in IoU metric on our test dataset, respectively. For the road centerline extraction task, the two kinds of methods improve the baseline methods by up to 8.22% and 10.9% in the Quality metric on our test dataset.

Building change detection using remote sensing images is essential for various applications such as urban management and marketing planning. However, most change detection approaches can only detect the intensity or type of change. The aim of this study is to dig for more change information from time-series synthetic aperture radar (SAR) images, such as the change frequency and the change moments. This paper proposes a novel multitemporal building change detection framework that can generate change frequency map (CFM) and change moment maps (CMMs) from multitemporal SAR images. We first give definitions of CFM and CMMs. Then we generate change feature using four proposed generators. After that, a new cosegmentation method combining raw images and change feature is proposed to divide time-series images into changed and unchanged areas separately. Secondly, the proposed cosegmentation and the morphological building index (MBI) are combined to extract changed building objects. Then, the logical conjunction between the cosegmentation results and the binarized MBI is performed to recognize every moment of change. In the post-processing step, we use fragment removal to increase accuracy. Finally, we propose a novel accuracy assessment index for CFM. We call this index average change difference (ACD). Compared to the traditional multitemporal change detection methods, our method outperforms other approaches in terms of both qualitative results and quantitative indices of ACD using two TerraSAR-X datasets. The experiments show that the proposed method is effective in generating CFM and CMMs.