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In a coordination construction, which is universally available, two or more syntactic constituents are combined, with or without an overt coordinator. This Element examines how coordinate structures are derived syntactically, focussing on the syntactic operations involved, including constraints on both their operations and the representations they produce. Specifically, considering the recent research development in the syntax of coordination, the Element discusses whether any special syntactic operation is required to derive various coordinate constructions, including constructions in which each conjunct has a gap, whether there is any special functional category heading coordinate constructions in general, what the morphosyntactic statuses of coordinators (i.e., conjunctions and disjunctions) are in some specific languages, whether the structure of a coordinate construction can be beyond the binary complementation structure, and whether the mobility of conjuncts and the mobility of elements in conjuncts require any construction-specific constraint on syntactic operations.
The aims of this study were to examine the spillover effects of violent attacks, coronavirus disease-2019 (COVID-19) exposure, and their interactions on health professionals’ mental health, and the role of organizational support in their relationships in China. A two-phase survey data (n = 10,901) before and after the first outbreak of COVID-19 was integrated with regional macro data on the number of lawsuit cases of violent attacks and COVID-19 cases. Three studies were designed to isolate the general spillover impact of violent attacks on the mental health of health professionals, how COVID-19 affects the mental health of health professionals, and whether organizational support moderates the relationship between violent attacks and mental health through econometric regressions. Violent attacks and COVID-19 are negatively associated with the mental health of health professionals, and the outbreak of COVID-19 adversely deteriorates the spillover effects of violent attacks. Physicians, not nurses, are the most affected group. Better perceived support from hospitals can significantly mitigate the adverse effects of COVID-19, violent attacks, and their interactions on the mental health of health professionals. COVID-19 deteriorates the adverse effects of violent attacks on the mental health of health professionals, while better organizational support is helpful to mitigate these effects.
Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.
A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.
Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen’s Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).
These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.
Compared with nitrogen and argon, helium is lighter and can better reduce the beam loss caused by angular scattering during beam transmission. The molecular dissociation cross-section in helium is high and stable at low energies, which makes helium the prevalent stripping gas in low-energy accelerator mass spectrometry (AMS). To study the stripping behavior of 14C ions in helium at low energies, the charge state distributions of carbon ion beams with −1, +1, +2, +3, and +4 charge states were measured at energies of 70–220 keV with a compact 14C-AMS at Guangxi Normal University (GXNU). The experimental data were used to analyze the stripping characteristics of C-He in the energy range of 70–220 keV, and new charge state yields and exchange cross-sections in C-He were obtained at energies of 70–220 keV.
A single-stage accelerator mass spectrometer (GXNU-AMS) developed for radiocarbon and tritium measurements was installed and commissioned at Guangxi Normal University in 2017. After several years of operational and methodological upgrades, its performance has been continuously improved and applied in multidisciplinary fields. Currently, the measurement sensitivity for radiocarbon and tritium is 14C/12C ∼ (3.14 ± 0.05) ×10–15 and 3H/1H ∼ (1.23 ± 0.17)×10–16, respectively, and the measurement accuracy is ∼0.6%, which can meet the measurement requirements in the nuclear, earth, environmental and life science fields. This study presents the performance characteristics of GXNU-AMS and several interesting application studies.
Although ketamine can rapidly decrease suicidal ideation (SI), its neurobiological mechanism of action remains unclear. Several areas of the cingulate cortex have been implicated in SI; therefore, we aimed to explore the neural correlates of the anti-suicidal effect of ketamine with cingulate cortex functional connectivity (FC) in depression.
Forty patients with unipolar or bipolar depression with SI underwent six infusions of ketamine over 2 weeks. Clinical symptoms and resting-state functional magnetic resonance imaging data were obtained at baseline and on day 13. Remitters were defined as those with complete remission of SI on day 13. Four pairs of cingulate cortex subregions were selected: the subgenual anterior cingulate cortex (sgACC), pregenual anterior cingulate cortex (pgACC), anterior mid-cingulate cortex (aMCC), and posterior mid-cingulate cortex (pMCC), and whole-brain FC for each seed region was calculated.
Compared with non-remitters, remitters exhibited increased FC of the right pgACC–left middle occipital gyrus (MOG) and right aMCC–bilateral postcentral gyrus at baseline. A high area under the curve (0.91) indicated good accuracy of the combination of the above between-group differential FCs as a predictor of anti-suicidal effect. Moreover, the change of SI after ketamine infusion was positively correlated with altered right pgACC–left MOG FC in remitters (r = 0.66, p = 0.001).
Our findings suggest that the FC of some cingulate cortex subregions can predict the anti-suicidal effect of ketamine and that the anti-suicidal mechanism of action of ketamine may involve alteration of FC between the right pgACC and left MOG.
The grey wolf optimizer (GWO) as a new intelligent optimization algorithm has been successfully applied in many fields because of its simple structure, few adjustment parameters and easy implementation. This paper mainly aims at the defects of GWO in path planning application, such as easily falling into local optimization, poor convergence and poor accuracy, and turn point grey wolf optimization (TPGWO) algorithm is proposed. First, the idea of cross-mutation and roulette is used to increase the initial population of GWO and improve the search range. At the same time, the convergence factor function is improved to become a nonlinear update. In the early stage, the search range is expanded, and in the later stage, the convergence speed is increased, while the parameters in the convergence factor function can be adjusted according to the number of obstacles and the map area to change the turning point of the function to improve the convergence speed and accuracy of the algorithm. The turning times and turning angles of the obtained path are added to the fitness function as penalty values to improve the path accuracy. The optimization test is carried out through 16 test functions, and the test results prove the convergence and robustness of TPGWO algorithm. Finally, the TPGWO algorithm is applied to the path planning of patrol robot for simulation experiments. Compared with the GWO algorithm and Particle Swarm Optimization, the simulation results show that the TPGWO algorithm has better convergence, stability and accuracy in the path planning of patrol robot.
Understanding user perceptions of interacting with the virtual world is one of the research focuses in recent years, given the rapid proliferation of virtual reality (VR) and driven to establish the metaverse. Users can generate a familiar connection between their bodies and the virtual world by being embodied in virtual hands, and hand representations can induce users’ embodiment in VR. The sense of embodiment represents the cognitive awareness of one's manifestation and includes three subcomponents: the sense of body ownership, agency and self-location. There is insufficient evidence in the literature about the effects of hand designs on the embodiment, especially based on studying its three subcomponents. This study investigates how virtual hand designs with five realism levels influence the three subcomponents of embodiment in VR. This research employs a self-report questionnaire commonly used in the literature to assess embodiment and evaluates agency and self-location by introducing implicit methods (intentional binding and proprioceptive measurement) derived from psychology. Besides, the objective data of eye tracking is used to explore the connection between embodiment and hand designs, and classifying participants’ eye tracking data to help analyze the link between embodiment and user attention. Overall, this research makes a major contribution through a systematic exploration of users’ embodied experience in VR and offers important evidence of the effects of virtual hand designs on body ownership, agency, and self-location, respectively. In addition, this study provides a valuable reference for further investigation of embodiment through implicit and objective methods, and practical design recommendations for virtual hand design in VR applications.
Slowed information processing speed (IPS) is the core contributor to cognitive impairment in patients with late-life depression (LLD). The hippocampus is an important link between depression and dementia, and it may be involved in IPS slowing in LLD. However, the relationship between a slowed IPS and the dynamic activity and connectivity of hippocampal subregions in patients with LLD remains unclear.
One hundred thirty-four patients with LLD and 89 healthy controls were recruited. Sliding-window analysis was used to assess whole-brain dynamic functional connectivity (dFC), dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic regional homogeneity (dReHo) for each hippocampal subregion seed.
Cognitive impairment (global cognition, verbal memory, language, visual–spatial skill, executive function and working memory) in patients with LLD was mediated by their slowed IPS. Compared with the controls, patients with LLD exhibited decreased dFC between various hippocampal subregions and the frontal cortex and decreased dReho in the left rostral hippocampus. Additionally, most of the dFCs were negatively associated with the severity of depressive symptoms and were positively associated with various domains of cognitive function. Moreover, the dFC between the left rostral hippocampus and middle frontal gyrus exhibited a partial mediation effect on the relationships between the scores of depressive symptoms and IPS.
Patients with LLD exhibited decreased dFC between the hippocampus and frontal cortex, and the decreased dFC between the left rostral hippocampus and right middle frontal gyrus was involved in the underlying neural substrate of the slowed IPS.
A new approach to target development for laboratory astrophysics experiments at high-power laser facilities is presented. With the dawn of high-power lasers, laboratory astrophysics has emerged as a field, bringing insight into physical processes in astrophysical objects, such as the formation of stars. An important factor for success in these experiments is targetry. To date, targets have mainly relied on expensive and challenging microfabrication methods. The design presented incorporates replaceable machined parts that assemble into a structure that defines the experimental geometry. This can make targets cheaper and faster to manufacture, while maintaining robustness and reproducibility. The platform is intended for experiments on plasma flows, but it is flexible and may be adapted to the constraints of other experimental setups. Examples of targets used in experimental campaigns are shown, including a design for insertion in a high magnetic field coil. Experimental results are included, demonstrating the performance of the targets.
The North China Plain is an important summer maize/winter wheat rotation area. However, over the years, continued intensive tillage has destroyed the soil aggregate accelerating the mineralization and decomposition of soil organic carbon (SOC), which plays an important role in soil quality, as increased organic carbon storage improves soil fertility and crop yields. Thus, the objective of this study was to explore the comprehensive impact of tillage methods on soil aggregates, aggregate-associated SOC, and carbon sequestration capacity under a regime of straw return. In 2002, we started a 14-year long-term tillage experiment; then in 2016–2017, we tested the following tillage methods, zero tillage (ZT), rotary tillage (RT), subsoiling (SS), and conventional tillage (CT). The results showed that in the 0–10 cm soil layer, tillage methods significantly reduced the proportion of aggregates in the order of 2–0.25 > 5–2 > 0.25–0.053 mm. Additionally, conservation tillage (i.e., SS and ZT) significantly increased the percentage of macroaggregates (0–40 cm) and their SOC content, compared to CT. Additionally, the contribution rate of macroaggregates to SOC was 17.2% and 30.6% higher under SS and ZT than under CT, respectively. Conservation tillage methods improved the carbon sequestration capacity of soil aggregates. Our study provides a theoretical basis for the development of more suitable tillage methods. Furthermore, long-term conservation tillage seemingly protected large aggregates and, SOC, whereby carbon sequestration was enhanced and soil carbon emissions were effectively reduced.
Relations between China and Latin America date back hundreds of years and have intensified since the founding of the People's Republic of China. Recognizing that meaningful relations with Latin America require an understanding of that varied region, China has established appropriate study and research programs. This essay on current Latin American programs in the People's Republic of China will report on research organizations, research interests of Chinese scholars, and current trends within Latin American studies. The double objectives are to describe China's interest in Latin America and to establish closer contacts between Latin Americanists in China and the United States.
Bragg scattering of nonlinear surface waves over a wavy bottom is studied using two-dimensional fully nonlinear numerical wave tanks (NWTs). In particular, we consider cases of high nonlinearity which lead to complex wave generation and transformations, hence possible multiple Bragg resonances. The performance of the NWTs is well verified by benchmarking experiments. Classic Bragg resonances associated with second-order triad interactions among two surface (linear incident and reflected waves) and one bottom wave components (class I), and third-order quartet interactions among three surface (linear incident and reflected waves, and second-order reflected/transmitted waves) and one bottom wave components (class III) are observed. In addition, class I Bragg resonance occurring for the second-order (rather than linear) transmitted waves, and Bragg resonance arising from quintet interactions among three surface and two bottom wave components, are newly captured. The latter is denoted class IV Bragg resonance which magnifies bottom nonlinearity. It is also found that wave reflection and transmission at class III Bragg resonance have a quadratic rather than a linear relation with the bottom slope if the bottom size increases to a certain level. The surface wave and bottom nonlinearities are found to play opposite roles in shifting the Bragg resonance conditions. Finally, the results indicate that Bragg resonances are responsible for the phenomena of beating and parasitic beating, leading to a significantly large local free surface motion in front of the depth transition.
COVID-19 is erupting globally, and Wuhan successfully controlled it within a month. Infections arose from infectious persons outside hospitals. After data revision, data-based and model-based analyses were implemented, and the conclusions are as follows. The incubation period of most infected people may be 6-7 days. The number of infectious persons outside hospitals in Wuhan on January 20, 2020 was about 10000 and reached more than 20000 on the day of Lockdown; it exceeded 72000 on February 4. Both data-based and model-based analyses gave out the evolution of the reproduction number, which was over 2.5 in early January, went down to 1.62 in late January and 1.20 in early February, with a sudden drop to less than 0.5 due to the strict Stay-at-home management after February 11. Strategies of Stay-at-home, Safe-protective measures, and Ark hospitals were the main contributions to control COVID-19 in Wuhan. In Wuhan, 2 inflection points of COVID-19, exactly correspond to February 5 and February 15, the 2 days when Ark hospitals were introduced, and the complete implementation of Stay-at-home. Based on the expression of the reproduction number, group immunity is also discussed. It shows that only when the group immunization rate is over 75% can COVID-19 be under control; group immunity would be full infection and the total deaths will be 220000 for a city as big as Wuhan. Sensitivity analysis suggests that 30% of people staying at home in combination with better behavior changes, such as social-distancing and frequent handwashing, can effectively contain COVID-19. However, only when this proportion is over 60% can the controlled effect and efficiency like Wuhan be obtained.
A new system for preparing 14C samples was established for a compact accelerator mass spectrometer (GXNU-AMS) at Guangxi Normal University. This sample preparation system consists of three units: a vacuum maintenance unit, a CO2 purification unit, and a CO2 reduction unit, all of which were made of quartz glass. A series of radiocarbon (14C) preparation experiments were conducted to verify the reliability of the system. The recovery rate of graphite obtained was more than 80%. The carbon content in the commercial toner and wood sample was linearly fitted to the CO2 pressure in the measurement unit of the system. The results showed a good linear relationship, indicating that the reliability of the sample preparation system. AMS measurements were conducted on a batch of standard, wood, and dead graphite samples prepared using this system. The results showed that the beam current of 12C- for each sample was more than 40 μA, the carbon contamination introduced during the sample preparation process was ∼ 2 × 10–15, and that the new sample preparation system is compact, low-contamination, and efficient and meets the GXNU-AMS requirements for 14C samples.
Low molecular weight glutenin subunits (LWM-GSs) play a crucial role in determining wheat flour processing quality. In this work, 35 novel LMW-GS genes (32 active and three pseudogenes) from three Aegilops umbellulata (2n = 2x = 14, UU) accessions were amplified by allelic-specific PCR. We found that all LMW-GS genes had the same primary structure shared by other known LMW-GSs. Thirty-two active genes encode 31 typical LMW-m-type subunits. The MZ424050 possessed nine cysteine residues with an extra cysteine residue located in the last amino acid residue of the conserved C-terminal III, which could benefit the formation of larger glutenin polymers, and therefore may have positive effects on dough properties. We have found extensive variations which were mainly resulted from single-nucleotide polymorphisms (SNPs) and insertions and deletions (InDels) among the LMW-GS genes in Ae. umbellulata. Our results demonstrated that Ae. umbellulata is an important source of LMW-GS variants and the potential value of the novel LMW-GS alleles for wheat quality improvement.
Many waterflooding oil fields, injecting water into an oil-bearing reservoir for pressure maintenance, are in their middle to late stages of development. To explore the geological conditions and improve oilfield recovery of the most important well group of the Hu 136 block, located on the border areas of three provinces (Henan, Shandong, and Hebei), Zhongyuan Oilfield, Sinopec, central China, a 14C cross-well tracer monitoring technology was developed and applied in monitoring the development status and recognize the heterogeneity of oil reservoirs. The tracer response in the production well was tracked, and the water drive speed, swept volume of the injection fluid were obtained. Finally, the reservoir heterogeneity characteristics, such as the dilution coefficient, porosity, permeability, and average pore-throat radius, were fitted according to the mathematical model of the heterogeneous multi-layer inter-well theory. The 14C-AMS technique developed in this work is expected to be a potential analytical method for evaluating underground reservoir characteristics and providing crucial scientific guidance for the mid to late oil field recovery process.
Accurate geometrical calibration between the scan coordinates and the camera coordinates is critical in four-dimensional scanning transmission electron microscopy (4D-STEM) for both quantitative imaging and ptychographic reconstructions. For atomic-resolved, in-focus 4D-STEM datasets, we propose a hybrid method incorporating two sub-routines, namely a J-matrix method and a Fourier method, which can calibrate the uniform affine transformation between the scan-camera coordinates using raw data, without a priori knowledge of the crystal structure of the specimen. The hybrid method is found robust against scan distortions and residual probe aberrations. It is also effective even when defects are present in the specimen, or the specimen becomes relatively thick. We will demonstrate that a successful geometrical calibration with the hybrid method will lead to a more reliable recovery of both the specimen and the electron probe in a ptychographic reconstruction. We will also show that, although the elimination of local scan position errors still requires an iterative approach, the rate of convergence can be improved, and the residual errors can be further reduced if the hybrid method can be firstly applied for initial calibration. The code is made available as a simple-to-use tool to correct affine transformations of the scan-camera coordinates in 4D-STEM experiments.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.