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The multi-robot path planning problem is an NP-hard problem. The coati optimization algorithm (COA) is a novel metaheuristic algorithm and has been successfully applied in many fields. To solve multi-robot path planning optimization problems, we embed two differential evolution (DE) strategies into COA, a self-adaptive differential evolution-based coati optimization algorithm (SDECOA) is proposed. Among these strategies, the proposed algorithm adaptively selects more suitable strategies for different problems, effectively balancing global and local search capabilities. To validate the algorithm’s effectiveness, we tested it on CEC2020 benchmark functions and 48 CEC2020 real-world constrained optimization problems. In the latter’s experiments, the algorithm proposed in this paper achieved the best overall results compared to the top five algorithms that won in the CEC2020 competition. Finally, we applied SDECOA to optimization multi-robot online path planning problem. Facing extreme environments with multiple static and dynamic obstacles of varying sizes, the SDECOA algorithm consistently outperformed some classical and state-of-the-art algorithms. Compared to DE and COA, the proposed algorithm achieved an average improvement of 46% and 50%, respectively. Through extensive experimental testing, it was confirmed that our proposed algorithm is highly competitive. The source code of the algorithm is accessible at: https://ww2.mathworks.cn/matlabcentral/fileexchange/164876-HDECOA.
This study aimed to demonstrate the utilization value of 1PN embryos. The 1PN zygotes collected from December 2021 to September 2022 were included in this study. The embryo development, the pronuclear characteristics, and the genetic constitutions were investigated. The overall blastocyst formation and good-quality blastocyst rates in 1PN zygotes were 22.94 and 16.24%, significantly lower than those of 2PN zygotes (63.25 and 50.23%, respectively, P = 0.000). The pronuclear characteristics were found to be correlated with the developmental potential. When comparing 1PN zygotes that developed into blastocysts to those that arrested, the former exhibited a significantly larger area (749.49 ± 142.77 vs. 634.00 ± 119.05, P = 0.000), a longer diameter of pronuclear (29.81 ± 3.08 vs. 27.30 ± 3.00, P = 0.000), and a greater number of nucleolar precursor body (NPB) (11.56 ± 3.84 vs. 7.19 ± 2.73, P = 0.000). Among the tested embryos, the diploidy euploidy rate was significantly higher in blastocysts in comparison with the arrested embryos (66.67 vs. 11.76%, P = 0.000), which was also significantly higher in IVF-1PN blastocysts than in ICSI-1PN blastocysts (75.44 vs. 25.00%, P = 0.001). However, the pronuclear characteristics were not found to be linked to the chromosomal ploidy once they formed blastocysts.
In summary, while the developmental potential of 1PN zygotes is reduced, our study shows that, in addition to the reported pronuclear area and diameter, the number of NPB is also associated with their developmental potential. The 1PN blastocysts exhibit a high diploidy euploidy rate, are recommend to be clinically used post genetic testing, especially for patients who do not have other 2PN embryos available.
This paper presents a three-stage E-band low-noise amplifier (LNA) fabricated in a 28-nm Complementary Metal Oxide Semiconductor High-Performance Compact Plus process. The proposed E-band LNA achieves a peak gain of 16.8 dB, exhibiting a gain variation of less than ±0.5 dB across the frequency range of 67.8–90.4 GHz. The measured 3-dB gain bandwidth spans from 64 to 93.8 GHz, and the minimum measured noise figure (NF) is 3.8 dB. By employing a one-stage common-source with a two-stage cascode topology, the proposed E-band LNA demonstrates competitiveness in terms of gain flatness and NF when compared to recently published E-band CMOS LNAs.
Introduction: Late-life depression (LLD) is associated with cognitive deficit with risk of future dementia. By examining the entropy of the spontaneous brain activity, we aimed to understand the neural mechanism pertaining to cognitive decline in LLD.
Methods: We collected MRI scans in older adults with LLD (n = 32), mild cognitive impairment [MCI (n = 25)] and normal cognitive function [NC, (n = 47)]. Multiscale entropy analysis (MSE) was applied to resting-state fMRI data. Under the scale factor (tau) 1 and 2, reliable separation of fMRI data and noise was achieved. We calculated the brain entropy in 90 brain regions based on automated anatomical atlas (AAL). Due to exploratory nature of this study, we presented data of group-wise comparison in brain entropy between LLD vs. NC, MCI vs. NC, and LLD and MCD with a p-value below 0.001.
Results: The mean Mini-Mental State Examination (MMSE) score of LLD and MCI was 27.9 and 25.6. Under tau 2, we found higher brain entropy of LLD in left globus pallidus than MCI (p = 0.002) and NC (p = 0,009). Higher brain entropy of LLD than NC was also found in left frontal superior gyrus, left middle superior gyrus, left amygdala and left inferior parietal gyrus. The only brain region with higher brain entropy in MCI than control was left posterior cingulum (p-value = 0.015). Under tau 1, higher brain entropy was also found in LLD than in MCI in right orbital part of medial frontal gyrus and left globus pallidus (p-value = 0.007 and 0.005).
Conclusions: Our result is consistent with prior hypothesis where higher brain entropy was found during early aging process as compensation. We found such phenomenon particular in left globus pallidus in LLD, which could be served as a discriminative brain region. Being a key region in reward system, we hypothesis such region may be associated with apathy and with unique pathway of cognitive decline in LLD. We will undertake subsequent analysis longitudinally in this cohort
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
Psychiatric diagnosis is based on categorical diagnostic classification, yet similarities in genetics and clinical features across disorders suggest that these classifications share commonalities in neurobiology, particularly regarding neurotransmitters. Glutamate (Glu) and gamma-aminobutyric acid (GABA), the brain's primary excitatory and inhibitory neurotransmitters, play critical roles in brain function and physiological processes.
Methods
We examined the levels of Glu, combined glutamate and glutamine (Glx), and GABA across psychiatric disorders by pooling data from 121 1H-MRS studies and further divided the sample based on Axis I disorders.
Results
Statistically significant differences in GABA levels were found in the combined psychiatric group compared with healthy controls (Hedge's g = −0.112, p = 0.008). Further analyses based on brain regions showed that brain GABA levels significantly differed across Axis I disorders and controls in the parieto-occipital cortex (Hedge's g = 0.277, p = 0.019). Furthermore, GABA levels were reduced in affective disorders in the occipital cortex (Hedge's g = −0.468, p = 0.043). Reductions in Glx levels were found in neurodevelopmental disorders (Hedge's g = −0.287, p = 0.022). Analysis focusing on brain regions suggested that Glx levels decreased in the frontal cortex (Hedge's g = −0.226, p = 0.025), and the reduction of Glu levels in patients with affective disorders in the frontal cortex is marginally significant (Hedge's g = −0.172, p = 0.052). When analyzing the anterior cingulate cortex and prefrontal cortex separately, reductions were only found in GABA levels in the former (Hedge's g = − 0.191, p = 0.009) across all disorders.
Conclusions
Altered glutamatergic and GABAergic metabolites were found across psychiatric disorders, indicating shared dysfunction. We found reduced GABA levels across psychiatric disorders and lower Glu levels in affective disorders. These results highlight the significance of GABA and Glu in psychiatric etiology and partially support rethinking current diagnostic categories.
This study aimed to understand the potassium voltage-gated channel KQT-like subfamily, member 1 gene polymorphism in a rural elderly population in a county in Guangxi and to explore the possible relationship between its gene polymorphism and blood sugar. The 6 SNP loci of blood DNA samples from 4355 individuals were typed using the imLDRTM Multiple SNP Typing Kit from Shanghai Tianhao Biotechnology Co. The data combining epidemiological information (baseline questionnaire and physical examination results) and genotyping results were statistically analyzed using GMDR0.9 software and SPSS22.0 software. A total of 4355 elderly people aged 60 years and above were surveyed in this survey, and the total abnormal rate of glucose metabolism was 16·11 % (699/4355). Among them, male:female ratio was 1:1·48; the age group of 60–69 years old accounted for the highest proportion, with 2337 people, accounting for 53·66 % (2337/4355). The results of multivariate analysis showed that usually not doing farm work (OR 1·26; 95 % CI 1·06, 1·50), TAG ≥ 1·70 mmol/l (OR 1·19; 95 % CI 1·11, 1·27), hyperuricaemia (OR 1·034; 95 % CI 1·01, 1·66) and BMI ≥ 24 kg/m2 (OR 1·06; 95 % CI 1·03, 1·09) may be risk factors for abnormal glucose metabolism. Among all participants, rs151290 locus AA genotype, A allele carriers (AA+AC) were 0.70 times more likely (0.54 to 0.91) and 0.82 times more likely (0.70 to 0.97) to develop abnormal glucose metabolism than CC genotype carriers, respectively. Carriers of the T allele at the rs2237892 locus (CT+TT) were 0.85 times more likely to have abnormal glucose metabolism than carriers of the CC genotype (0.72 to 0.99); rs2237897 locus CT gene. The possibility of abnormal glucose metabolism in the carriers of CC genotype, TT genotype and T allele (CT + TT) is 0·79 times (0·67–0·94), 0·74 times (0·55–0·99) and 0·78 times (0·66, 0·92). The results of multifactor dimensionality reduction showed that the optimal interaction model was a three-factor model consisting of farm work, TAG and rs2237897. The best model dendrogram found that the interaction between TAG and rs2237897 had the strongest effect on fasting blood glucose in the elderly in rural areas, and they were mutually antagonistic. Environment–gene interaction is an important factor affecting abnormal glucose metabolism in the elderly of a county in Hechi City, Guangxi.
The influence of outer large-scale motions (LSMs) on near-wall structures in compressible turbulent channel flows is investigated. To separate the compressibility effects, velocity fluctuations are decomposed into solenoidal and dilatational components using the Helmholtz decomposition method. Solenoidal velocity fluctuations manifest as near-wall streaks and outer large-scale structures. The spanwise drifting of near-wall solenoidal streaks is found to be driven by the outer LSMs, while LSMs have a trivial influence on the spanwise density of solenoidal streaks, consistent with the outer LSM impacts found in incompressible flows (Zhou et al., J. Fluid Mech., vol. 940, 2022, p. A23). Dilatational motions are characterized by the near-wall small-scale travelling-wave packets and the large-scale parts in the outer region. The streamwise advection velocity of the near-wall structures remains at $16 \sim 18u_{\tau }$, hardly influenced by Mach numbers, Reynolds numbers and wall temperatures. The spanwise drifting of near-wall dilatational structures, quantified by the particle image velocimetry method, follows a mechanism distinct from solenoidal streaks. This drifting velocity is notably larger than those of the solenoidal streaks, and the influence of outer LSMs is not the primary trigger for this drifting.
The practical implementation of machine learning in flow control is limited due to its significant training expenses. In the present study the convolutional neural network (CNN) trained with the data of the restricted nonlinear (RNL) model is used to predict the normal velocity on a detection plane at $y^+=10$ in a turbulent channel flow, and the predicted velocity is used as wall blowing and suction for drag reduction. An active control test is carried out by using the well-trained CNN in direct numerical simulation (DNS). Substantial drag reduction rates up to 19 % and 16 % are obtained based on the spanwise and streamwise wall shear stresses, respectively. Furthermore, we explore the online control of wall turbulence by combining the RNL model with reinforcement learning (RL). The RL is constructed to determine the optimal wall blowing and suction based on its observation of the wall shear stresses without using the label data on the detection plane for training. The controlling and training processes are conducted synchronously in a RNL flow field. The control strategy discovered by RL has similar drag reduction rates with those obtained previously by the established method. Also, the training cost decreases by over thirty times at $Re_{\tau }=950$ compared with the DNS-RL model. The present results provide a perspective that combining the RNL model with machine learning control for drag reduction in wall turbulence can be effective and computationally economical. Also, this approach can be easily extended to flows at higher Reynolds numbers.
Whether material deprivation-related childhood socio-economic disadvantages (CSD) and care-related adverse childhood experiences (ACE) have different impacts on depressive symptoms in middle-aged and older people is unclear.
Methods
In the Guangzhou Biobank Cohort Study, CSD and ACE were assessed by 7 and 5 culturally sensitive questions, respectively, on 8,716 participants aged 50+. Depressive symptoms were measured by 15-item Geriatric Depression Scale (GDS). Multivariable linear regression, stratification analyses, and mediation analyses were done.
Results
Higher CSD and ACE scores were associated with higher GDS score in dose-response manner (P for trend <0.001). Participants with one point increment in CSD and ACE had higher GDS score by 0.11 (95% confidence interval [CI], 0.09–0.14) and 0.41 (95% CI, 0.35–0.47), respectively. The association of CSD with GDS score was significant in women only (P for sex interaction <0.001; women: β (95% CI)=0.14 (0.11–0.17), men: 0.04 (−0.01 to 0.08)). The association between ACE and GDS score was stronger in participants with high social deprivation index (SDI) (P for interaction = 0.01; low SDI: β (95% CI)=0.36 (0.29–0.43), high SDI: 0.64 (0.48–0.80)). The proportion of association of CSD and ACE scores with GDS score mediated via education was 20.11% and 2.28%.
Conclusions
CSD and ACE were associated with late-life depressive symptoms with dose-response patterns, especially in women and those with low adulthood socio-economic status. Education was a major mediator for CSD but not ACE. Eliminating ACE should be a top priority.
The measurement of X-ray continuous emission from laser-driven plasma was achieved through multiple monochromatic imaging utilizing a multilayer mirror array. This methodology was exemplified by the development of an eight-channel X-ray imaging system, capable of operating in the energy range of several keV with a spatial resolution of approximately 3 μm. By integrating this system with a streak camera, the temperature and trajectory of imploding capsules were successfully measured at the kJ-class Shenguang III prototype laser facility. This approach provides a synchronous diagnostic method for the spatial, temporal and spectral analysis of laser-driven plasma, characterized by its high efficiency and resolution.
Sleep disturbance and impulsivity are key components of mood vulnerability in bipolar disorder (BD), but few studies have assessed the association between these two symptoms among patients with BD.
Methods
Forty-seven euthymic patients with bipolar I disorder (BDI) or bipolar II disorder (BDII) and 58 age- and sex-matched healthy controls were enrolled in this cross-sectional study. Trait impulsivity was measured using the Barratt Impulsiveness Scale Version 11 (BIS-11), which yielded 3 second-order factors: attention, motor, and non-planning. Subjective sleep quality was assessed using the self-reported Pittsburgh Sleep Quality Index (PSQI). General linear models (GLMs) were used to assess the associations between subjective poor sleep and trait impulsivity with multiple testing corrections.
Results
Patients with BD scored higher in BIS-11 and PSQI than healthy controls. PSQI total scores positively correlated with BIS-11 total scores, while sleep disturbance and daytime dysfunction were associated with attentional impulsiveness after controlling for covariates. Participants with higher PSQI total scores (>10) had higher scores in BIS-11 total, attention, and non-planning than those with low PSQI scores (≤5).
Conclusion
These findings support the hypothesis that poor sleep quality might lead to impulsivity and add to the growing evidence that improving sleep quality may be a therapeutic target for patients with BD.
To investigate the rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody among unvaccinated voluntary blood donors in Chongqing, and to provide evidence for epidemic surveillance.
Methods:
A total of 10,208 voluntary blood donors from January 5 to January 20, 2021, in the Chongqing area were collected, and the SARS-CoV-2 immunoglobulin (Ig) G and IgM antibodies were detected by chemiluminescence, and the differences of antibody-positive rate in different gender, age, ABO blood group, and different risk areas were analyzed.
Results:
Among 10208 blood donors, 10 were found to be positive for SARS-COV-2 IgG antibody, giving a positivity rate of SARS-COV-2 IgG at 0.10%, and 29 were positive for SARS-CoV-2 IgM antibody, with a positivity rate of SARS-CoV-2 IgM at 0.28%. There was no statistical difference in the positive rate of antibody among different genders, ages, and ABO blood types, but it was related to the number of confirmed coronavirus disease 2019 (COVID-19) cases in each city.
Conclusions:
The SARS-CoV-2 seroprevalence rate in Chongqing was low and correlated with the number of confirmed COVID-19 cases.
Numerical simulations are carried out on the vortex-induced rotations of a freely rotatable rigid square cylinder in a two-dimensional uniform cross-flow. A range of Reynolds numbers between 40 and 150 and density ratios between 0.1 and 10 are considered. Results show eight different characteristic regimes, expanding the classification of Ryu & Iaccarino (J. Fluid Mech., vol. 813, 2017, pp. 482–507). New regimes include the transition and wavy rotation regimes; in the ${\rm \pi}$-limited oscillation regime we observe multipeak subregimes. Moment-generating mechanisms of these regimes and subregimes are further elucidated. A phenomenon related to the influence of density ratio is the tooth-like shape of the ${\rm \pi} /2$-limit oscillation regime observed in the regime map, which is explained as a result of the imbalance relation between the main frequencies of rotation response and the vortex shedding frequency. In addition, existence of multiple regimes and multistable states are discussed, indicating multiple stable attractive structures in phase space.
We report an experimental study of the formation and evolution of laminar thermal structures generated by a small heat source, with a focus on their correlation to the thermal boundary layer and effects of heating time $t_{heat}$. The experiments are performed over the flux Rayleigh number ($Ra_f$) range $2.1\times 10^6 \leq Ra_f \leq 3.6\times 10^{7}$ and the Prandtl number ($Pr$) range $28.6 \leq Pr \leq 904.7$. The corresponding Rayleigh number ($Ra= t_{heat}\,Ra_{f}/\tau _0\,Pr$) range is $900 \leq Ra \leq 4\times 10^{4}$, where $\tau _0$ is a diffusion time scale. For thermal structures generated by continuous heating (i.e. starting plumes), their formation process exists three characteristic times that are well reflected by changes in the thermal boundary layer thickness. These characteristic times, denoted as $t_{emit}$, $t_{recover}$ and $t_{static}$, correspond to the moments when the plume emission begins and completes, and when the thermal boundary layer becomes quasi-static, respectively. Their $Ra_f$–$Pr$ dependencies are found to be $t_{emit}/\tau _0\sim Ra_f^{-0.41}\,Pr^{0.41}$, $t_{recover}/\tau _0\sim Ra_f^{-0.48}\,Pr^{0.48}$ and $t_{static}/\tau _0\sim Ra_f^{-0.49}\,Pr^{0.33}$, respectively. Thermal structures generated by finite $t_{heat}$ exhibit similar evolution dynamics once $t_{heat} \ge t_{emit}$, with the accelerating stage behaving like starting plumes and the decay stage like thermals (i.e. a finite amount of buoyant fluids). It is further found that their maximum rising velocity experiences a transition in the $Ra$-dependence from $Ra$ to $(Ra\ln Ra)^{0.5}$ at $Ra \simeq 6000$; and their maximum acceleration reaches the value of starting plumes at $t_{heat}\simeq t_{recover}$, and remains unchanged for larger $t_{heat}$. In particular, the maximum rising velocity for the cases with $t_{heat} = t_{recover}$ follows a scaling relation $Ra_f^{0.37}\,Pr^{-0.37}$, in contrast to the relation $Ra_f^{0.48}\,Pr^{-0.48}$ for starting plumes. This study provides a more comprehensive understanding of laminar thermal structures, which are relevant to a range of processes in nature and laboratory systems such as Rayleigh–Bénard convection.
Stress affects executive functions and exploring the association between stress-induced physiological reactivity and executive functions could highlight the potential mechanism of the stress-cognitive function link. Our study examined the linear and nonlinear associations between cardiovascular stress reactivity and cool and hot executive functions among adolescents. In November 2021 (T1), 273 Chinese adolescents between 11 and 14 (Mage = 12.93, SDage = 0.79) underwent a speech task during which their cardiovascular data were recorded, and they completed a Flanker task and an Emotional Stroop task. In May 2023 (T2), 253 adolescents again completed the Flanker and Emotional Stroop tasks. Cool and hot executive functions were assessed using the intra-individual reaction time variability of the Flanker task and Emotional Stroop task, respectively. Results showed that cardiovascular stress reactivity was positively linearly associated with cool executive functions at T1 and quadratically (inverted U-shaped) associated with cool executive functions at T1 and hot executive functions at T1 and T2. These findings suggest that compared to very high and very low cardiovascular reactivity, moderate to high cardiovascular reactivity to a structured social challenge is associated with better cool and hot executive functions.
The iron-rich calcareous soil (Typic Rhodustalf) from the Penghu island group represents a volcanic area. The black soils (Typic Haplustert, Vertic Endoaquoll, Typic Hapludolls) are typical of eastern Taiwan. Four A horizons and a pedon from the iron-rich calcareous soil and four pedons from the black soils were studied to analyze soil properties and clay compositions. The objective was to compare the properties of smectites developed from different parent materials. The materials were studied by using conventional X-ray diffraction (XRD) of K- and Mg-saturated clays and involved the alkylam-monium (C = 12) method and the Greene-Kelly test. The mean-layer charge of smectites (0.48–0.52 cmol(c)/O10(OH)2) in the iron-rich calcareous soil was found to be higher than the black soils (0.43–0.48 cmol(c)/O10(OH)2). A smectite of higher charge developed from the basalts. This smectite is enriched in Fe and Mg, and lacks Si, thereby forming beidellite and/or nontronite. In contrast, under high precipitation, elevated temperature, base saturation (e.g., Na, K, Ca, Mg), and about equal wet and dry cycles per year in the black soil environments, smectites developed from the complicated geologic site of eastern Taiwan. These smectites transformed to smectite-kaolinite mixed-layer clay and thus, resulted in lower-charge smectites. The K fixation capacity of the iron-rich calcareous soil was higher than the black soils.
Comparative lawyers are interested in similarities between legal systems. Artificial intelligence offers a new approach to understanding legal families. This chapter introduces machine-learning methods useful in empirical comparative law, a nascent field. This chapter provides a step-by-step guide to evaluating and developing legal family theories using machine-learning algorithms. We briefly survey existing empirical comparative law data sets, and then demonstrate how to visually explore these using a data set one of us compiled. We introduce popular and powerful algorithms of service to comparative law scholars, including dissimilarity coefficients, dimension reduction, clustering, and classification. The unsupervised machine-learning method enables researchers to develop a legal family scheme without the interference from existing schemes developed by human intelligence, thus providing a powerful tool to test comparative law theories. The supervised machine-learning method enables researchers to start with a baseline scheme (developed by human or artificial intelligence) and then extend it to previously unstudied jurisdictions.