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A novel entomopathogenic nematode (EPN) species, Steinernema tarimense n. sp., was isolated from soil samples collected in a Populus euphratica forest located in Yuli County within the Tarim Basin of Xinjiang, China. Integrated morphological and molecular analyses consistently place S. tarimense n. sp. within the ‘kushidai-clade’. The infective juvenile (IJ) of new species is characterized by a body length of 674–1010 μm, excretory pore located 53–80 μm from anterior end, nerve ring positioned 85–131 μm from anterior end, pharynx base situated 111–162 μm from anterior end, a tail length of 41–56 μm, and the ratios D% = 42.0–66.6, E% = 116.2–184.4, and H% = 25.5–45.1. The first-generation male of the new species is characterized by a curved spicule length of 61–89 μm, gubernaculum length of 41–58 μm, and ratios D% = 36.8–66.2, SW% = 117.0–206.1, and GS% = 54.8–82.0. Additionally, the tail of first-generation female is conoid with a minute mucron. Phylogenetic analyses of ITS, 28S, and mt12S sequences demonstrated that the three isolates of S. tarimense n. sp. are conspecific and form a sister clade to members of the ‘kushidai-clade’ including S. akhursti, S. anantnagense, S. kushidai, and S. populi. Notably, the IJs of the new species exhibited faster development at 25°C compared to other Steinernema species. This represents the first described of an indigenous EPN species from Xinjiang, suggesting its potential as a novel biocontrol agent against local pests.
The dynamics of ice basal melting in seawater is one of the key factors in understanding and modelling the ice–seawater interaction in the polar oceans. In this work we study the basal melting of solid ice in seawater, and focus on the interaction between the melting process and the double diffusive convection developed in the seawater layer. Different temperatures and salinity differences are systematically simulated, and two different flow regimes are identified. For a relatively weak salinity difference, the convection layer occupies most of the liquid layer and grows in height as the ice melts. When the salinity difference is strong enough, the convection layer shrinks with time and a stably stratified layer grows between the ice layer and convection layer. When the dynamics is dominated by the convection layer, the global heat and salinity transfer rates follow a power-law scaling. Theoretical models are developed for the local mean salinity at the ice–water interface and the melting rates, and the critical density ratio corresponding to the transition between the two regimes, which all agree with the numerical results. Density inversion happens consistently adjacent to the ice–seawater interface, which has a profound influence on the ice surface shape. All these findings provide useful insights into the detailed dynamics of ice basal melting in oceans.
While there is evidence that childhood maltreatment (CM) is positively associated with drug use (DU), the strength and difference of the association between CM and its subtypes (hereafter CM + ST) and DU remains to be further explored. A multilevel meta-analysis was conducted on 101 independent studies reporting 333 effect sizes (N = 132,341; Mage = 24.65; 43.80%males). Results showed significantly positive correlations between CM + ST and DU (range from 0.109 to 0.185). The results of the subgroup analysis revealed notable disparities in the correlations between distinct CM subtypes and DU (F = 5.358, P<0.01). Specifically, the effect size for childhood sexual abuse (CSA) was significantly lower than childhood emotional maltreatment (CEM) and childhood physical maltreatment (CPM), while no significant difference was noted between the CEM and CPM groups. These effect sizes also varied across regions, drug types, gender, detection rate of CM, the presence or absence of alcohol in substances, publication status and measurement method. The significant yet differing correlations between different subtypes of CM and DU to some extent support the principle of equality in psychopathology. These findings help explain the relationship between CM + ST and DU laying the groundwork for further research into the intricate and complex associations between CM and DU.
Screw theory serves as an influential mathematical tool, significantly contributing to mechanical engineering, with particular relevance to mechanism science and robotics. The instantaneous screw and the finite displacement screw have been used to analyse the degree of freedom and perform kinematic analysis of linkage mechanisms with only lower pairs. However, they are not suitable for higher pair mechanisms, which can achieve complex motions with a more concise structure by reasonably designing contact contours, and they possess advantages in some particular areas. Therefore, to improve the adaptability of screw theory, this paper aims to analyse higher kinematic pair (HKP) mechanisms and proposes a method to extend instantaneous screw and finite displacement screw theory. This method can not only analyse the instantaneous degree of freedom of HKP mechanisms but also determine the relationships between the motion variables of HKP mechanisms. Furthermore, this method is applied to calculate the degree of freedom and the relationships between the motion angles in both planar and spatial cam mechanisms, thereby demonstrating its efficiency and advantages.
This paper is focused on the existence and uniqueness of nonconstant steady states in a reaction–diffusion–ODE system, which models the predator–prey interaction with Holling-II functional response. Firstly, we aim to study the occurrence of regular stationary solutions through the application of bifurcation theory. Subsequently, by a generalized mountain pass lemma, we successfully demonstrate the existence of steady states with jump discontinuity. Furthermore, the structure of stationary solutions within a one-dimensional domain is investigated and a variety of steady-state solutions are built, which may exhibit monotonicity or symmetry. In the end, we create heterogeneous equilibrium states close to a constant equilibrium state using bifurcation theory and examine their stability.
Recent studies have increasingly utilized gradient metrics to investigate the spatial transitions of brain organization, enabling the conversion of macroscale brain features into low-dimensional manifold representations. However, it remains unclear whether alterations exist in the cortical morphometric similarity (MS) network gradient in patients with schizophrenia (SCZ). This study aims to examine potential differences in the principal MS gradient between individuals with SCZ and healthy controls and to explore how these differences relate to transcriptional profiles and clinical phenomenology.
Methods
MS network was constructed in this study, and its gradient of the network was computed in 203 patients with SCZ and 201 healthy controls, who shared the same demographics in terms of age and gender. To examine irregularities in the MS network gradient, between-group comparisons were carried out, and partial least squares regression analysis was used to study the relationships between the MS network gradient-based variations in SCZ, and gene expression patterns and clinical phenotype.
Results
In contrast to healthy controls, the principal MS gradient of patients with SCZ was primarily significantly lower in sensorimotor areas, and higher in more areas. In addition, the aberrant gradient pattern was spatially linked with the genes enriched for neurobiologically significant pathways and preferential expression in various brain regions and cortical layers. Furthermore, there were strong positive connections between the principal MS gradient and the symptomatologic score in SCZ.
Conclusions
These findings showed changes in the principal MS network gradient in SCZ and offered potential molecular explanations for the structural changes underpinning SCZ.
This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.
Systematically monitoring the baseline sensitivity of troublesome weeds to herbicides is a crucial step in the early detection of their market lifespan. Florpyrauxifen-benzyl is one of the most important herbicides used in rice production throughout the world, and has been used for 5 yr in China. Barnyardgrass is one of the main targeted weed species of florpyrauxifen-benzyl. In total, 114 barnyardgrass populations were collected from rice fields in Jiangsu Province, China, and using whole-plant bioassays they were screened for susceptibility to florpyrauxifen-benzyl. The GR50 values (representing the dose that causes a 50% reduction in fresh weight of aboveground parts) of florpyrauxifen-benzyl for all populations ranged from 1.0 to 34.5 g ai ha−1, with an average of 6.8 g ai ha−1, a baseline sensitivity dose of 3.3 g ai ha−1, and a baseline sensitivity index of 34.5. Twenty-one days after treatment with florpyrauxifen-benzyl at the labeled dose (36 g ai ha−1), 90% of the barnyardgrass populations exhibited >95% reductions in fresh weight of aboveground parts. Compared with the baseline sensitivity dose, 63, 44, and 7 populations had, respectively, no resistance (55%), low resistance (39%), and moderate resistance (6%) to florpyrauxifen-benzyl. Furthermore, the GR50 distribution of barnyardgrass populations did not show a significant correlation with collection location, planting method (direct-seeding or transplanting), or rice species (Oryza sativa L. ssp. indica or ssp. japonica) at any of rice fields where seeds had been collected (P > 0.05). In conclusion, florpyrauxifen-benzyl remains effective for barnyardgrass control in rice fields despite serious resistance challenges.
The betatron radiation source features a micrometer-scale source size, a femtosecond-scale pulse duration, milliradian-level divergence angles and a broad spectrum exceeding tens of keV. It is conducive to the high-contrast imaging of minute structures and for investigating interdisciplinary ultrafast processes. In this study, we present a betatron X-ray source derived from a high-charge, high-energy electron beam through a laser wakefield accelerator driven by the 1 PW/0.1 Hz laser system at the Shanghai Superintense Ultrafast Laser Facility (SULF). The critical energy of the betatron X-ray source is 22 ± 5 keV. The maximum X-ray flux reaches up to 4 × 109 photons for each shot in the spectral range of 5–30 keV. Correspondingly, the experiment demonstrates a peak brightness of 1.0 × 1023 photons·s−1·mm−2·mrad−2·0.1%BW−1, comparable to those demonstrated by third-generation synchrotron light sources. In addition, the imaging capability of the betatron X-ray source is validated. This study lays the foundation for future imaging applications.
Previous research has shown abnormal functional network gradients in Alzheimer’s disease (AD). Structural network gradient is capable of capturing continuous changes in brain morphology and has the ability to elucidate the underlying processes of neurodevelopment. However, it remains unclear whether structural network gradients are altered in AD and what associations exist between these changes and cognitive function, and gene expression profiles.
Methods
By constructing an individualized structural network gradient decomposition framework, we calculated the morphological similarity network (MSN) gradients for 404 subjects (186 AD patients and 218 normal controls). We investigated AD-related alterations in MSN gradients, along with the associations between MSN gradients and cognitive function, MSN topological properties, and gene expression profiles.
Results
Our findings indicated that the principal MSN gradient alterations in AD were primarily characterized by an increase in the primary and secondary sensory cortices and a decrease in the association cortex 1. The primary and higher-order cortices exhibited opposite associations with cognition, including executive function, language skills, and memory processes. Moreover, the principal MSN gradients were found to significantly predict cognitive function in AD. The altered gradient pattern was 14.8% attributable to gene expression profiles, and the genes demonstrating the highest correlation are involved in metabolic activity and synaptic signaling.
Conclusions
Our results offered novel insights into the underlying mechanisms of structural brain network impairment in AD patients, enhancing our understanding of the neurobiological processes responsible for impaired cognition in patients with AD, and offering a new dimensional structural biomarker for AD.
Laser-driven inertial confinement fusion (ICF) diagnostics play a crucial role in understanding the complex physical processes governing ICF and enabling ignition. During the ICF process, the interaction between the high-power laser and ablation material leads to the formation of a plasma critical surface, which reflects a significant portion of the driving laser, reducing the efficiency of laser energy conversion into implosive kinetic energy. Effective diagnostic methods for the critical surface remain elusive. In this work, we propose a novel optical diagnostic approach to investigate the plasma critical surface. This method has been experimentally validated, providing new insights into the critical surface morphology and dynamics. This advancement represents a significant step forward in ICF diagnostic capabilities, with the potential to inform strategies for enhancing the uniformity of the driving laser and target surface, ultimately improving the efficiency of converting laser energy into implosion kinetic energy and enabling ignition.
Attention-deficit/hyperactivity disorder (ADHD) patients exhibit characteristics of impaired working memory (WM) and diminished sensory processing function. This study aimed to identify the neurophysiologic basis underlying the association between visual WM and auditory processing function in children with ADHD.
Methods
The participants included 86 children with ADHD (aged 6–15 years, mean age 9.66 years, 70 boys, and 16 girls) and 90 typically developing (TD) children (aged 7–16 years, mean age 10.30 years, 66 boys, and 24 girls). Electroencephalograms were recorded from all participants while they performed an auditory discrimination task (oddball task). The visual WM capacity and ADHD symptom severity were measured for all participants.
Results
Compared with TD children, children with ADHD presented a poorer visual WM capacity and a smaller mismatch negativity (MMN) amplitude. Notably, the smaller MMN amplitude in children with ADHD predicted a less impaired WM capacity and milder inattention symptom severity. In contrast, the larger MMN amplitude in TD children predicted a better visual WM capacity.
Conclusions
Our results suggest an intimate relationship and potential shared mechanism between visual WM and auditory processing function. We liken this shared mechanism to a total cognitive resource limit that varies between groups of children, which could drive correlated individual differences in auditory processing function and visual WM. Our findings provide a neurophysiological correlate for reports of WM deficits in ADHD patients and indicate potential effective markers for clinical intervention.
The emerging era of big data in radio astronomy demands more efficient and higher-quality processing of observational data. While deep learning methods have been applied to tasks such as automatic radio frequency interference (RFI) detection, these methods often face limitations, including dependence on training data and poor generalisation, which are also common issues in other deep learning applications within astronomy. In this study, we investigate the use of the open-source image recognition and segmentation model, Segment Anything Model (SAM), and its optimised version, HQ-SAM, due to their impressive generalisation capabilities. We evaluate these models across various tasks, including RFI detection and solar radio burst (SRB) identification. For RFI detection, HQ-SAM (SAM) shows performance that is comparable to or even superior to the SumThreshold method, especially with large-area broadband RFI data. In the search for SRBs, HQ-SAM demonstrates strong recognition abilities for Type II and Type III bursts. Overall, with its impressive generalisation capability, SAM (HQ-SAM) can be a promising candidate for further optimisation and application in RFI and event detection tasks in radio astronomy.
Glaciers play a crucial role in the Asian Water Tower, underscoring the necessity of accurately assessing their mass balance and ice volume to evaluate their significance as sustainable freshwater resources. In this study, we analyzed ground-penetrating radar (GPR) measurements from a 2020 survey of the Xiao Dongkemadi Glacier (XDG) to determine ice thickness, and we extended the glacier’s volume-change record to 2020 by employing multi-source remote-sensing data. Our findings show that the GPR-derived mean ice thickness of XDG in 2020 was 54.78 ± 3.69 m, corresponding to an ice volume of 0.0811 ± 0.0056 km3. From 1969 to 2020, the geodetic mass balance was −0.19 ± 0.02 m w.e. a−1, and the glacier experienced area and ice volume losses of 16.38 ± 4.66% and 31.01 ± 4.59%, respectively. The long-term mass-balance reconstruction reveals weak fluctuations occurred from 1967 to 1993 and that overall mass losses have occurred since 1994. This ongoing shrinkage and ice loss are mainly associated with the temperature increases in the warm season since the 1960s. If the climate trend across the central Tibetan Plateau follows to the SSP585 scenario, then XDG is at risk of disappearing by the end of the century.
Developing large-eddy simulation (LES) wall models for separated flows is challenging. We propose to leverage the significance of separated flow data, for which existing theories are not applicable, and the existing knowledge of wall-bounded flows (such as the law of the wall) along with embedded learning to address this issue. The proposed so-called features-embedded-learning (FEL) wall model comprises two submodels: one for predicting the wall shear stress and another for calculating the eddy viscosity at the first off-wall grid nodes. We train the former using the wall-resolved LES (WRLES) data of the periodic hill flow and the law of the wall. For the latter, we propose a modified mixing length model, with the model coefficient trained using the ensemble Kalman method. The proposed FEL model is assessed using the separated flows with different flow configurations, grid resolutions and Reynolds numbers. Overall good a posteriori performance is observed for predicting the statistics of the recirculation bubble, wall stresses and turbulence characteristics. The statistics of the modelled subgrid-scale (SGS) stresses at the first off-wall grids are compared with those calculated using the WRLES data. The comparison shows that the amplitude and distribution of the SGS stresses and energy transfer obtained using the proposed model agree better with the reference data when compared with the conventional SGS model.
This study demonstrates a kilowatt-level, spectrum-programmable, multi-wavelength fiber laser (MWFL) with wavelength, interval and intensity tunability. The central wavelength tuning range is 1060–1095 nm and the tunable number is controllable from 1 to 5. The wavelength interval can be tuned from 6 to 32 nm and the intensity of each channel can be adjusted independently. Maximum output power up to approximately 1100 W has been achieved by master oscillator power amplifier structures. We also investigate the wavelength evolution experimentally considering the difference of gain competition, which may give a primary reference for kW-level high-power MWFL spectral manipulation. To the best of our knowledge, this is the highest output power ever reported for a programmable MWFL. Benefiting from its high power and flexible spectral manipulability, the proposed MWFL has great potential in versatile applications such as nonlinear frequency conversion and spectroscopy.
This study aimed to assess the relationship between COVID-19 infection-related conditions and depressive symptoms among medical staff after easing the zero-COVID policy in China, and to further examine the mediating role of professional burnout.
Methods
A total of 1716 medical staff from all levels of health care institutions in 16 administrative districts of Beijing, China, were recruited to participate at the end of 2022 in this cross-sectional study. Several multiple linear regressions and mediating effects tests were performed to analyze the data.
Results
At the beginning of the end of the zero-COVID policy in China, 91.84% of respondents reported infection with COVID-19. After adjusting for potential confounding variables, the severity of infection symptoms was significantly positively associated with high levels of depressive symptoms (β = 0.06, P < 0.001), and this association was partially mediated by professional burnout. Specifically, emotional exhaustion (95% CI, 0.131, 0.251) and depersonalization (95% CI, 0.009, 0.043) significantly mediated the association between the severity of infection symptoms and depressive symptoms.
Conclusions
The mental health of medical staff with more severe symptoms of COVID-19 infection should be closely monitored. Also, interventions aimed at reducing emotional exhaustion and depersonalization may effectively reduce their risk of developing depressive symptoms.
Care of the dying is an essential part of holistic cancer nursing. Improving nurses’ attitudes and behaviors regarding care of the dying is one of the critical factors in increasing the quality of nursing service. This study aims to examine the impact of an educational program based on the CARES tool on nurses’ attitudes and behaviors toward care of the dying.
Methods
A quasi-experimental study with pre- and post-intervention measures was conducted. A total of 222 oncology nurses from 14 hospitals in Beijing, China, were enrolled using a convenient sampling method. This online educational course developed based on the CARES framework comprised 7 modules and 10 sessions. Each session was carried out twice a week over 30–60 min. Data were collected using a sociodemographic characteristics questionnaire, the Frommelt Attitude Towards Care of the Dying Scale (FATCOD) and the Nurses’ Practice Behavior Toward Care of the Dying Questionnaire (NPBTCOD). Reassessment of attitudes and behaviors was conducted when completed the learning and 6 months after the learning, respectively. The sociodemographic characteristics of the nurses were analyzed using descriptive statistics, and differences in attitudes and behaviors were reported and compared by the paired t-test.
Results
All the 222 oncology nurses completed educational courses, and 218 nurses (98.20%) completed the pre- and post-attitudes evaluation and 213 (95.9%) nurses completed the pre- and post-behaviors evaluation. The mean (SD) FATCOD score before and after the educational program was 108.83 (12.07) versus 115.09 (14.91), respectively (t = −8.546, p ≥ 0.001). The mean (SD) NPBTCOD score before and after the educational program was 69.14 (17.56) versus 73.40 (18.96), respectively (t = −3.231, p = 0.001).
Significance of results
This educational intervention was found to be an effective method for improving oncology nurses’ attitudes and behaviors toward caring for dying patients.
Ridge B is one of the least studied areas in Antarctica but has been considered to be a potential location for the oldest ice on Earth. Among important parameters for calculating where very old ice may exist, geothermal heat flux (GHF) is critical but poorly understood. Here, GHF is determined by quantifying the transitions between dry and wet basal conditions using a radioglaciological method applied to airborne radio-echo sounding data. GHF is then constrained by a thermodynamic model matched to the transitions. The results show that GHF in Ridge B varies locally and ranges from 48.5 to 65.1 mW m−2, with an average value of 58.0 mW m−2, which is consistent with the current known GHF constrained by subglacial lakes and derived from Vostok ice core temperature measurements. Our work highlights the value of considering local GHF when locating the oldest ice in this potential region or other regions.
There is an unavoidable time offset between the camera stream and the inertial measurement unit (IMU) data due to the sensor triggering and transmission delays, which will seriously affect the accuracy of visual-inertial odometry (VIO). A novel online time calibration framework via double-stage EKF for VIO is proposed in this paper. First, the first-stage complementary Kalman filter is constructed by adapting the complementary characteristics between the accelerometer and the gyroscope in the IMU, where the rotation result predicted by the gyroscope is corrected through the measurement of the accelerometer so that the IMU can output a more accurate initial pose. Second, the unknown time offset is added to the state vector of the VIO system. The estimated pose of IMU is used as the prediction information, and the reprojection error of multiple cameras on the same feature point is used as the constraint information. During the operation of the VIO system, the time offset is continuously calculated and superimposed on the IMU timestamp to obtain the data synchronized by the IMU and the camera. The Schur complement model is used to marginalize the camera state that carries less information in the system state, avoiding the loss of prior information between images, and improving the accuracy of camera pose estimation. Finally, the effectiveness of proposed algorithm is verified using the EuRoC dataset and the real experimental data.