Machine learning (ML) models have been developed to identify randomised controlled trials (RCTs) to accelerate systematic reviews (SRs). However, their use has been limited due to concerns about their performance and practical benefits. We developed a high-recall ensemble learning model using Cochrane RCT data to enhance the identification of RCTs for rapid title and abstract screening in SRs and evaluated the model externally with our annotated RCT datasets. Additionally, we assessed the practical impact in terms of labour time savings and recall improvement under two scenarios: ML-assisted double screening (where ML and one reviewer screened all citations in parallel) and ML-assisted stepwise screening (where ML flagged all potential RCTs, and at least two reviewers subsequently filtered the flagged citations). Our model achieved twice the precision compared to the existing SVM model while maintaining a recall of 0.99 in both internal and external tests. In a practical evaluation with ML-assisted double screening, our model led to significant labour time savings (average 45.4%) and improved recall (average 0.998 compared to 0.919 for a single reviewer). In ML-assisted stepwise screening, the model performed similarly to standard manual screening but with average labour time savings of 74.4%. In conclusion, compared with existing methods, the proposed model can reduce workload while maintaining comparable recall when identifying RCTs during the title and abstract screening stages, thereby accelerating SRs. We propose practical recommendations to effectively apply ML-assisted manual screening when conducting SRs, depending on reviewer availability (ML-assisted double screening) or time constraints (ML-assisted stepwise screening).

The study aims were to present in vitro susceptibilities of clinical isolates from Gram-negative bacteria bloodstream infections (GNBSI) collected in China. GNBSI isolates were collected from 18 tertiary hospitals in 7 regions of China from 2018 to 2020. Minimum inhibitory concentrations were assessed using a Trek Diagnostic System. Susceptibility was determined using CLSI broth microdilution, and breakpoints were interpreted using CLSI M100 (2021). A total of 1,815 GNBSI strains were collected, with E. coli (42.4%) and Klebsiella pneumoniae (28.6%) being the most prevalent species, followed by P. aeruginosa (6.7%). Susceptibility analyses revealed low susceptibilities (<40%) of ESBL-producing E. coli and K. pneumonia to third-/fourth-generation cephalosporins, monobactamases, and fluoroquinolones. High susceptibilities to colistin (95.0%) and amikacin (81.3%) were found for K. pneumoniae, while Acinetobacter baumannii exhibited a high susceptibility (99.2%) to colistin but a low susceptibility to other antimicrobials (<27.5%). Isolates from ICUs displayed lower drug susceptibility rates of K. pneumoniae and A. baumannii than isolates from non-ICUs (all P < 0.05). Carbapenem-resistant and ESBL-producing K. pneumoniae detection was different across regions (both P < 0.05). E. coli and K. pneumoniae were major contributors to GNBSI, while A. baumannii exhibited severe drug resistance in isolates obtained from ICU departments.

The aerodynamic deformation and breakup of wall-attached droplets in axisymmetric stagnation flow are investigated experimentally. A vertical shock tube is used to generate the shock wave accompanying the post-wave airflow, and the axisymmetric stagnation flow is formed through the impingement of an air stream on a solid wall. For the wall-attached droplets with initially hemispherical profile, four typical droplet deformation and breakup modes can be identified with the continuous increase of the droplet local Weber number, which are the vibrating mode, the compressing mode, the sheet thinning mode and the shear-induced entrainment mode. Quantitative analyses of droplet evolution dynamics are also conducted for the compressing mode and the sheet thinning mode, and the significant differences of air flow separation at the droplet lateral surface between these two modes are revealed. The potential flow model and the energy conservation model are further developed to predict the entire droplet deformation processes. The vibrating frequency and amplitude of droplets under the vibrating mode are predicted by a spring-mass model, and the surface perturbation wavelengths of droplets under the shear-induced entrainment mode are estimated based on the dispersion relation of Kelvin–Helmholtz instability. This work is proposed to give potential guidance for regulating the aerodynamic fragmentation of wall-attached droplets in practical engineering applications.

Although it is well established that gestational diabetes mellitus (GDM) is associated with fetal overgrowth in singleton pregnancies, little is known about its role in twins. We aimed to explore the relationship between GDM and the longitudinal fetal growth in twin pregnancies. This was a retrospective matched cohort study of GDM and non-GDM twin pregnancies delivered ≥36 weeks without other complications. All the women performed ≥3 ultrasounds after 22 weeks. Linear mixed models (LMMs) were used to explore the relationships between longitudinal fetal growth trajectories and GDM. Group-based trajectory modeling (GBTM) and generalized estimating equation (GEE) were applied to identify the latent growth patterns and investigate their relationships with GDM. In total, 215 GDM and 645 non-GDM twins were included, the majority of the patients did not require medication therapy (n = 202, GDMA1). LMM revealed that, compared with non-GDM, GDM was associated with an average increase in fetal weight of 4.36 g (95% CI [1.25, 7.48]) per week. GBTM and GEE further revealed that GDM increased the odds of fetal weight trajectory to nearly 40% of the total fetal weight trajectory, classified into the high-speed group (aOR = 1.39, 95% CI [1.03, 1.88]), associating with a 49.44 g (95% CI [11.41, 87.48]) increase in birth weight. Subgroup analysis revealed that all these differences were only significant among the GDMA1 pregnancies (p < .05). GDM (GDMA1) is significantly associated with an increase in fetal weight during gestation in twin pregnancies. However, this acceleration is mild, and its significance requires further exploration.

Motion primitives play an important role in motion planning for autonomous vehicles, as they effectively address the sampling challenges inherent in nonholonomic motion planning. Employing motion primitives (MPs) is a widely accepted approach in nonholonomic motion planning based on sampling. This study specifically addresses the problem of learning from human-driving data to create human-like trajectories from predefined start-to-end states, which then serve as MP within the sampling-based nonholonomic motion planning framework. In this paper, we propose a deep learning-based method for generating MP that capture human-driving trajectory data features. By processing human-driving trajectory data, we create a Motion Primitive dataset that uniformly covers typical urban driving scenarios. Based on this dataset, a vehicle model long short-term memory neural network model is constructed to learn the features of the human-driving trajectory data. Finally, a framework for the generation of MP for practical applications is given based on this neural network. Our experiments, which focus on the dataset, the MMP generation network, and the generation process, demonstrate that our method significantly improves the training efficacy of the MP generation network. Additionally, the MP generated by our method exhibit higher accuracy compared to traditional methods.

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.

This study aims to investigate the effects of the vine of Lonicera japonica Thunb (VLT) and marine-derived Bacillus amyloliquefaciens-9 (BA-9) supplementation on the growth performance, antioxidant capacity, and gut microbiota of goat kids. A total of 32 4-week-old kids were randomly assigned into four groups: a control group (CON), a group supplemented with 0.3% BA-9 (BA-9), a group supplemented with 2% VLT (VLT), and a group supplemented with both 0.3% BA-9 and 2% VLT (MIX). The results indicated that VLT supplementation significantly increased both average daily (P < 0.001) and total weight gain (TWG) (P < 0.001), while BA-9 alone had no significant effect (P > 0.05) on the average daily and TWG. Biomarker analysis of oxidative stress revealed that supplementation of VLT or BA-9 alone enhanced antioxidant capacity. The MIX group showing a higher total antioxidant capacity (T-AOC) compared with the CON, VLT, and BA-9 groups (P < 0.05). Plasma albumin (ALB) levels were significantly increased in the both VLT and BA-9 groups. Microbiota analysis revealed significant differences in α-diversity and β-diversity between the MIX and CON groups, with specific genera such as Prevotellaceae_UCG.004 and Rikenellaceae_RC9_gut_group negatively correlated with average daily gain (ADG), while Alistipes was positively correlated with T-AOC. These findings suggest that the combined supplementation of VLT and BA-9 can significantly enhance growth performance and antioxidant capacity in goat kids by modulating the composition of gut microbiota and reducing oxidative stress.

A high-energy pulsed vacuum ultraviolet (VUV) solid-state laser at 177 nm with high peak power by the sixth harmonic of a neodymium-doped yttrium aluminum garnet (Nd:YAG) amplifier in a KBe2BO3F2 prism-coupled device was demonstrated. The ultraviolet (UV) pump laser is a 352 ps pulsed, spatial top-hat super-Gaussian beam at 355 nm. A high energy of a 7.12 mJ VUV laser at 177 nm is obtained with a pulse width of 255 ps, indicating a peak power of 28 MW, and the conversion efficiency is 9.42% from 355 to 177 nm. The measured results fitted well with the theoretical prediction. It is the highest pulse energy and highest peak power ever reported in the VUV range for any solid-state lasers. The high-energy, high-peak-power, and high-spatial-uniformity VUV laser is of great interest for ultra-fine machining and particle-size measurements using UV in-line Fraunhofer holography diagnostics.

We present the generation of high-repetition-rate strong-field terahertz (THz) pulses from a thin 4-N,N-dimethylamino-4’-N’-methyl-stilbazolium 2,4,6-trimethylbenzenesulfonate (DSTMS) organic crystal pumped by an ytterbium-doped yttrium aluminum garnet laser. The generated THz pulse energy reaches 932.8 nJ at 1 kHz repetition rate, with a conversion efficiency of 0.19% and a peak electric field of 819 kV/cm. At a repetition rate of 10 kHz, it is able to maintain a peak electric field of 236 kV/cm and an average THz power of 0.77 mW. The high-repetition-rate, strong-field THz source provides a convenient tool for the study of THz matter manipulation and THz spectroscopy.

Nontuberculous mycobacteria (NTM) is a large group of mycobacteria other than the Mycobacterium tuberculosis complex and Mycobacterium leprae. Epidemiological investigations have found that the incidence of NTM infections is increasing in China, and it is naturally resistant to many antibiotics. Therefore, studies of NTM species in clinical isolates are useful for understanding the epidemiology of NTM infections. The present study aimed to investigate the incidence of NTM infections and types of NTM species. Of the 420 samples collected, 285 were positive for M. tuberculosis, 62 samples were negative, and the remaining 73 samples contained NTM, including 35 (8.3%) only NTM and 38 (9%) mixed (M. tuberculosis and NTM). The most prevalent NTM species were Mycobacterium intracellulare (30.1%), followed by Mycobacterium abscessus (15%) and M. triviale (12%). M. gordonae infection was detected in 9.5% of total NTM-positive cases. Moreover, this study reports the presence of Mycobacterium nonchromogenicum infection and a high prevalence of M. triviale for the first time in Henan. M. intracellulare is the most prevalent, accompanied by some emerging NTM species, including M. nonchromogenicum and a high prevalence of M. triviale in Henan Province. Monitoring NTM transmission and epidemiology could enhance mycobacteriosis management in future.

In the current study, cryoconite samples were collected from six glaciers on the Tibetan Plateau to analyze n-alkanes and n-alkenes. The findings revealed that the concentrations of n-alkanes and n-alkenes varied from 40.1 to 496.1 μg g−1 and from 4.6 to 13.8 μg g−1, respectively. The carbon preference index of the long-chain n-alkanes ranged from 3.3 to 8.4, and the average chain length ranged from 28.7 to 29.3. Moreover, the δ13C of the n-alkanes in cryoconites were within the range of C3 plants, demonstrating that the n-alkanes in cryoconites were only derived from vascular plants. However, the δDmean were more negative than that of C3 plants, which could be caused by dry and humid conditions of glaciers. Unlike n-alkanes, n-alkenes ranged from C17:1 to C30:1 and showed a weak even-over-odd carbon number preference in the Dongkemadi, Yuzhufeng, Laohugou and Tianshan glacier, but a weak odd carbon preference in the Qiyi glacier. The n-alkenes in the YL Snow Mountains showed an obvious odd-over-even carbon number predominance from C17:1 to C22:1 with Cmax at C19:1, and the even-over-odd carbon number preference from C23:1 to C30:1 with Cmax at C28:1. This demonstrated that the n-alkenes of cryoconites may be mainly derived from in situ production in glaciers.

Seven accelerator mass spectrometry radiocarbon (AMS 14C) dates (7260±106∼7607±95 BP averaged 7444±103 BP) on a giant oyster shell, collected from an ancient shore of the Taipei Basin, are similar to the LSC (liquid scintillation counting) 14C age (7260±46 BP) of a grass sample inside the shell. The calibrated 14C ages of the C. gigas by Marine20 are 7490±240∼7805±230 cal BP (average 7660±96 cal BP), generally agreed with the calibrated LSC 14C ages of the grass and the oyster shell. Combined with other 14C ages of shoreline samples in the Taipei Basin, it is evident that sea level rose from 8600 to 7600 cal BP and reached a stand higher than modern sea level. During this marine transgression, the sedimentation rate along the shoreline was very high because 14C dating was not able to detect age differences for 4–5 m thick sediment sequences. Sixty-nine analyses of δ18O and δ13C from the oldest part of the shell exhibit clear seasonal cycles, with a 4-year period of growth in the 5.5-cm section. According to the δ18O values, the ancient oyster grew in a warmer-than-present shoreline environment, suggesting that the current absence of the giant oyster in Taiwan is not due to warming conditions.

Few studies have evaluated the joint effect of trace elements on spontaneous preterm birth (SPTB). This study aimed to examine the relationships between the individual or mixed maternal serum concentrations of Fe, Cu, Zn, Se, Sr and Mo during pregnancy, and risk of SPTB. Inductively coupled plasma MS was employed to determine maternal serum concentrations of the six trace elements in 192 cases with SPTB and 282 controls with full-term delivery. Multivariate logistic regression, weighted quantile sum regression (WQSR) and Bayesian kernel machine regression (BKMR) were used to evaluate the individual and joint effects of trace elements on SPTB. The median concentrations of Sr and Mo were significantly higher in controls than in SPTB group (P < 0·05). In multivariate logistic regression analysis, compared with the lowest quartile levels of individual trace elements, the third- and fourth-quartile Sr or Mo concentrations were significantly associated with reduced risk of SPTB with adjusted OR (aOR) of 0·432 (95 CI < 0·05). In multivariate logistic regression analysis, compared with the lowest quartile levels of individual trace elements, the third- and fourth-quartile Sr or Mo concentrations were significantly associated with reduced risk of SPTB with adjusted aOR of 0·432 (95 % CI 0·247, 0·756), 0·386 (95 % CI 0·213, 0·701), 0·512 (95 % CI 0·297, 0·883) and 0·559 (95 % CI 0·321, 0·972), respectively. WQSR revealed the inverse combined effect of the trace elements mixture on SPTB (aOR = 0·368, 95 % CI 0·228, 0·593). BKMR analysis confirmed the overall mixture of the trace elements was inversely associated with the risk of SPTB, and the independent effect of Sr and Mo was significant. Our findings suggest that the risk of SPTB decreased with concentrations of the six trace elements, with Sr and Mo being the major contributors.

Dual-robot system has been widely applied to the field of handling and palletizing for its high efficiency and large workspace. It is one of the key problems of the trajectory planning to determine the collision avoidance method of the dual-robot system. In the present study, a collision avoidance trajectory planning method for the dual-robot system was proposed on the basis of a modified artificial potential field (APF) algorithm. The interference and collision criterion of the dual-robot system was given firstly, which was established based on the method of kinematic analysis in robotics. And then, in consideration of the problem of excessive virtual potential field force induced by using the traditional APF algorithm in the process of dual-robot trajectory planning, a modified APF algorithm was proposed. Finally, the modified APF algorithm was used for motion control of a dual-robot palletizing process, and the collision avoidance performance of the proposed collision avoidance algorithm was studied through a dual-robot palletizing simulation and experiment. The results have shown that with the proposed collision avoidance trajectory planning algorithm, the two robots in dual-robot system can maintain a safe distance at all times during palletizing process. Compared with the traditional APF and rapidly-exploring random tree (RRT) algorithm, the trajectory solution time of the modified APF algorithm is greatly reduced. And the modified APF algorithm’s convergence time is 14.2% shorter than that of the traditional APF algorithm.

With the development of high-power microwave technology, the output power of the pulse generator is required more and more higher. In this paper, it is realized by increasing the output power of the module while the output impedance of the module changes little. The module of the generator is based on pulse forming network (PFN) and linear transformer (LT). Four Blumlein PFNs with arc-type configuration and 24 Ω characteristic impedance were connected symmetrically to the primary coil of the LTD and driven by two identical laser triggered spark switches to ensure four Blumlein PFNs synchronizing operation. On this basis, a two-stage high-power pulse generator based on PFN-LT is developed. The following technical parameters of the generator were achieved on a 12 Ω high-power solid resistor: output voltage amplitude of ∼250 kV and output power of ∼5.2 GW at a repetition rate of 5 Hz.

The state of iron in coal gangue minerals is an important factor in determining the potential for value-added utilization of this solid waste; this is especially true for the coal gangue coming from the Pingshuo open-pit mine in China. The objective of the present study was to characterize the petrological, mineralogical, and chemical states of Fe in the coal gangue from the Carboniferous Taiyuan Formation. Methods used included polarizing microscopy, X-ray diffraction (XRD), scanning electron microscopy–energy-dispersive spectroscopy (SEM–EDS), X-ray fluorescence, micro-Fourier-transform infrared (micro-FTIR) spectroscopy, and Mössbauer spectroscopy. The coal gangues are mudstones, silty mudstones, and pelitic siltstones, which are composed primarily of kaolinite, quartz, feldspar, pyrite, illite, and magnesite. In coal gangue, the Fe was found to occur in ferruginous minerals, in crystal-lattice substitutions, or in a colloidal state. The ferruginous minerals in the coal gangue are pyrite and marcasite, and the pyrite morphologies are framboidal, euhedral octahedral crystals, subhedral granular crystals, and irregular crystals. The results of SEM–EDS and micro-FTIR confirmed that the lattice substitution of Fe in the coal gangue minerals occurred mainly in kaolinite, resulting in two types of kaolinite: iron-containing and iron-free kaolinite. The former may be transformed from volcanic biotite and the latter from volcanic feldspar. The Mössbauer spectra of kaolinite showed intense doublets with isomer shift and quadrupole splitting values consistent with tetrahedrally coordinated Fe3+ and ocahedrally coordinated Fe2+, suggesting the presence of two types of substitution sites: (1) Fe2+ replacing Al3+ in the octahedral sheet; and (2) Fe3+ replacing Si4+ in the tetrahedral sheet. This study has important theoretical significance for the high-value utilization of coal gangue.

Previous literature attempted to gain insight into financial abuse involving people with dementia by analysing court cases, but these studies were limited in sample size or scope. This study collected 214 court rulings directly related to the financial decisions of people with dementia to identify characteristics of the financial abuse victim, perpetrators and the types of assets. The models of bystander intervention and routine activity theory were used as conceptual models to guide analysis regarding the role of bank staff as well as the court's decision in cases of financial abuse. The majority of financial abuse perpetrators were family members (73.8%), as opposed to outsiders (19.2%). Transfer of real estate was the most common legal issue, and land was the most common financial asset involved. Difficult intra-family relationships seem to pose a great risk of financial abuse involving people with dementia since adult children were found to be the most likely perpetrators (52.7%) but also plaintiffs accusing financial abuse (57.6%). In accordance with the bystander intervention model, bank staff were more likely to be suspicious of financial abuse when an outsider was regarded as the perpetrator. In accordance with the routine activity theory model, the court was more likely to acknowledge the case as an invalid financial decision when an outsider was regarded as the perpetrator in financial abuse cases. Since people with dementia suffer from greater losses due to their family members, future policies should establish guidelines for front-line bank staff to identify warning signs to reduce the risk of financial abuse involving people with dementia, not only to prevent fraud by outsiders but also exploitation by family members.