66 research outputs found
A real-world observation of antipsychotic effects on brain volumes and intrinsic brain activity in schizophrenia
Background: The confounding effects of antipsychotics that led to the inconsistencies of neuroimaging findings have long been the barriers to understanding the pathophysiology of schizophrenia (SZ). Although it is widely accepted that antipsychotics can alleviate psychotic symptoms during the early most acute phase, the longer-term effects of antipsychotics on the brain have been unclear. This study aims to look at the susceptibility of different imaging measures to longer-term medicated status through real-world observation.
Methods: We compared gray matter volume (GMV) with amplitude of low-frequency fluctuations (ALFFs) in 89 medicated-schizophrenia (med-SZ), 81 unmedicated-schizophrenia (unmed-SZ), and 235 healthy controls (HC), and the differences were explored for relationships between imaging modalities and clinical variables. We also analyzed age-related effects on GMV and ALFF values in the two patient groups (med-SZ and unmed-SZ).
Results: Med-SZ demonstrated less GMV in the prefrontal cortex, temporal lobe, cingulate gyri, and left insula than unmed-SZ and HC (
Conclusion: GMV loss appeared to be pronounced to longer-term antipsychotics, whereby imbalanced alterations in regional low-frequency fluctuations persisted unaffected by antipsychotic treatment. Our findings may help to understand the disease course of SZ and potentially identify a reliable neuroimaging feature for diagnosis
Decreased Functional Connectivity in Insular Subregions in Depressive Episodes of Bipolar Disorder and Major Depressive Disorder
Objective: Clinically, it is very difficult to distinguish between major depressive disorder (MDD) and bipolar disorder (BD) in the period of depression. Increasing evidence shows that the insula plays an important role in depression. We aimed to compare the resting-state functional connectivity (rsFC) of insular subregions in patients with MDD and BD in depressive episodes (BDD), who had never experienced manic or hypomanic episodes when they were scanned to identify biomarkers for the identification of two diseases.Methods: We recruited 21 BDD patients, 40 MDD patients and 70 healthy controls (HC). Resting-state functional magnetic resonance imaging (rs-fMRI) was performed. BDD patients had never had manic or hypomanic episodes when they were scanned, and the diagnoses were determined by follow-up. We divided the insula into three parts including the ventral anterior insular cortex (v-AIN), dorsal anterior insular cortex (d-AIN), and posterior insula (PI). The insular-based rsFC was compared among the three groups, and an analysis of the correlation between the rsFC value and Hamilton depression and anxiety scales was carried out.Results: BDD and MDD patients demonstrated decreased rsFC from the v-AIN to the left superior/middle frontal gyrus compared with the HC group. Versus MDD and HC groups, BDD patients exhibited decreased rsFC from the v-AIN to the area in the left orbital frontal gyrus and left superior temporal gyrus (included temporal pole), from the PI to the right lateral postcentral gyrus and from all three insular subregions to the somatosensory and motor cortex. Meanwhile, a correlation between the rsFC value of the PI-right lateral postcentral gyrus and anxiety score was observed in patients.Conclusion: Our findings show BDD and MDD patients have similar decreases in insular connectivity in the dorsal lateral frontal regions, and BDD patients have specific decreased insular connectivity, especially in the somatosensory and motor cortex, which may be used as imaging evidence for clinical identification
Liquid metal embrittlement of a dual-phase Al0.7CoCrFeNi high-entropy alloy exposed to oxygen-saturated lead-bismuth eutectic
This paper reports a new liquid metal embrittlement (LME) system in which a dual-phase Al0.7CoCrFeNi (equimolar fraction) high-entropy alloy (HEA) is embrittled by lead-bismuth eutectic (LBE) at 350 and 500°C. At 350°C, (Ni, Al)-rich BCC phase is embrittled, leading to intragrain cracking within this phase, while the predominant cracking mode changes to BCC/FCC phase boundary decohesion at 500°C. At both temperatures, cracks are rarely seen in the (Co, Cr, Fe)-rich FCC phase, indicating that this phase is immune to LME. Furthermore, the results suggest a transition from an adsorption-dominated LME mechanism at 350°C to a phase boundary wetting-dominated LME mechanism at 500°C
The Relationship Between Cognitive Dysfunction and Symptom Dimensions Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder
Background: Cognitive dysfunction is considered a core feature among schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Despite abundant literature comparing cognitive dysfunction among these disorders, the relationship between cognitive dysfunction and symptom dimensions remains unclear. The study aims are a) to identify the factor structure of the BPRS-18 and b) to examine the relationship between symptom domains and cognitive function across SZ, BD, and MDD.Methods: A total of 716 participants [262 with SZ, 104 with BD, 101 with MDD, and 249 healthy controls (HC)] were included in the study. One hundred eighty participants (59 with SZ, 23 with BD, 24 with MDD, and 74 HC) completed the MATRICS Consensus Cognitive Battery (MCCB), and 507 participants (85 with SZ, 89 with BD, 90 with MDD, and 243 HC) completed the Wisconsin Card Sorting Test (WCST). All patients completed the Brief Psychiatric Rating Scale (BPRS).Results: We identified five BPRS exploratory factor analysis (EFA) factors (“affective symptoms,” “psychosis,” “negative/disorganized symptoms,” “activation,” and “noncooperation”) and found cognitive dysfunction in all of the participant groups with psychiatric disorders. Negative/disorganized symptoms were the most strongly associated with cognitive dysfunctions across SZ, BD, and MDD.Conclusions: Our findings suggest that cognitive dysfunction severity relates to the negative/disorganized symptom domain across SZ, BD, and MDD, and negative/disorganized symptoms may be an important target for effective cognitive remediation in SZ, BD, and MDD
Precise Measurements of Branching Fractions for Meson Decays to Two Pseudoscalar Mesons
We measure the branching fractions for seven two-body decays to
pseudo-scalar mesons, by analyzing data collected at
GeV with the BESIII detector at the BEPCII collider. The branching fractions
are determined to be ,
,
,
,
,
,
,
where the first uncertainties are statistical, the second are systematic, and
the third are from external input branching fraction of the normalization mode
. Precision of our measurements is significantly improved
compared with that of the current world average values
Effect of Chickpea Flour on Noodle Quality and Glycemic Index
To improve the application scope and economic value of chickpea, chickpea flour with different additions (0%, 10%, 20%, 30%, and 40%) was mixed with wheat flour to make noodles. Texture quality, cooking quality, microstructure, and glycemic index (GI) were used to explore the effects of chickpea flour on noodles' processing quality and functional quality. The results showed that the addition of chickpea flour in the range of 0% to 20% had no significant effect on the texture quality, cooking quality, and microstructure of noodles. However, the texture quality and cooking quality of noodles were significantly reduced and the microstructure was significantly damaged when the addition amount was in the range of 20%~40%. The higher addition amount of chickpea flour deteriorated the processing quality of noodles. 0%, 10%, 20%, 30%, and 40% additions of chickpea flour noodles in vitro enzymatic method of the GI values were 76.97±0.49, 67.19±0.84, 64.95±0.71, 63.24±0.29 and 61.84±0.55, respectively. All belonged to middle GI food. The order of postprandial blood glucose in mice after gavage was wheat flour noodles>10% added chickpea flour noodles>20% added chickpea flour noodles>30% added chickpea flour noodles>40% added chickpea flour noodles. It was consistent with the results of in vitro enzymatic method. In summary, the addition of chickpea flour below 20% could improve the processing quality of noodles. The addition of chickpea flour could significantly reduce the digestive properties of starch. It would provide more choices for the diet of special populations such as diabetes
BBDetector: A Precise and Scalable Third-Party Library Detection in Binary Executables with Fine-Grained Function-Level Features
Third-party library (TPL) reuse may introduce vulnerable or malicious code and expose the software, which exposes them to potential risks. Thus, it is essential to identify third-party dependencies and take immediate corrective action to fix critical vulnerabilities when a damaged reusable component is found or reported. However, most of the existing methods only rely on syntactic features, which results in low recognition accuracy and significantly discounts the detection performance by obfuscation techniques. In addition, a few semantic-based approaches face the efficiency problem. To resolve these problems, we propose and implement a more precise and scalable TPL detection method BBDetector. In addition to syntactic features, we consider the rich function-level semantic features and form a feature vector for each function. Moreover, we design a scalable function vector similarity search method to identify anchor functions and the candidate libraries, based upon which we carry out TPL detection. The experiment results demonstrate that BBDetector outperforms B2SFinder and ModX in terms of effectiveness, efficiency, and obfuscation-resilient capability. For the nix binaries, the F1-score of BBDetector is 1.11% and 11.21% higher than that of ModX and B2SFinder, respectively. Moreover, for the Ubuntu binaries, the F1-score of BBDetector is 1.32% and 14.93% is higher than that of ModX and B2SFinder, respectively. And in terms of efficiency, the detection time of BBDetector is only 30.02% of ModX. Besides, for the obfuscation-resilient capability, BBDetector is much stronger than B2SFinder. BBDetector achieves a F1-score of 71%, slightly lower than the F1-score of 77% achieved with the non-obfuscated binary programs. However, B2SFinder only achieves an F1-score of 28%, much lower than that of 67% achieved with the non-obfuscated binary programs
PEGG-Net: Background Agnostic Pixel-Wise Efficient Grasp Generation Under Closed-Loop Conditions
Performing closed-loop grasping at close proximity to an object requires a
large field of view. However, such images will inevitably bring large amounts
of unnecessary background information, especially when the camera is far away
from the target object at the initial stage, resulting in performance
degradation of the grasping network. To address this problem, we design a novel
PEGG-Net, a real-time, pixel-wise, robotic grasp generation network. The
proposed lightweight network is inherently able to learn to remove background
noise that can reduce grasping accuracy. Our proposed PEGG-Net achieves
improved state-of-the-art performance on both Cornell dataset (98.9%) and
Jacquard dataset (93.8%). In the real-world tests, PEGG-Net can support
closed-loop grasping at up to 50Hz using an image size of 480x480 in dynamic
environments. The trained model also generalizes to previously unseen objects
with complex geometrical shapes, household objects and workshop tools and
achieved an overall grasp success rate of 91.2% in our real-world grasping
experiments.Comment: there are some authorship to be handle
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