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[Display omitted] • AOB and SOB reduced NH 3 and H 2 S by 38.90 % and 46.24 %, respectively. • Combined addition of microbial agents could reduce the sulfur loss by 34.69%. • The abundance of soxB gene was increased by 1.72 times in the coupling treatment. • Microbial inoculation enhanced the correlation between bacteria and soxB gene. Ammonia (NH 3) and hydrogen sulfide (H 2 S) are the main odor components in the composting process. Controlling their emissions is very important to reduce environmental pollution and improve the quality of composting products. This study explored the effects of functional bacteria on nitrogen and sulfur metabolism in the composting process of food waste (FW) by adding ammonia-oxidizing bacteria (AOB, A treatment), sulfur-oxidizing bacteria (SOB, S treatment), and combined AOB and SOB (AS treatment), respectively. The key bacterial species involved in nitrogen and sulfur transformation were identified, and the intrinsic mechanisms by which ammonia oxidation drove sulfur oxidation during composting were deciphered. Compared with control treatment (CK), the combined addition of functional microorganisms increased the maximum of soxB gene abundance by 1.72 times, thus resulting in the increase in the SO 4 2- content by 44.00 %. AS treatment decreased the cumulative H 2 S emission and total sulfur (TS) loss by 40.24 % and 34.69 %, respectively, meanwhile lowering NH 3 emission. Correlation network analysis showed that the simultaneous addition of AOB and SOB enhanced the correlation between microorganisms and sulfur oxidation genes, and Acinetobacter , Aeribacillus , Brevibacterium and Ureibacillus might be involved in the ammonia oxidation-promoted sulfur oxidation process. In summary, the optimized inoculation strategy of AOB and SOB could drive biological transformation of nitrogen and sulfur by regulating microbial community, ultimately reducing odor emissions and improving sulfur conservation. [ABSTRACT FROM AUTHOR]

Background: Studies have proven that individuals with internet gaming disorder (IGD) show impaired cognitive control over game craving; however, the neural mechanism underlying this process remains unclear. Accordingly, the present study aimed to investigate the dynamic features of brain functional networks of individuals with IGD during rest, which have barely been understood until now.Methods: Resting-state fMRI data were collected from 333 subjects (123 subjects with IGD (males/females: 73/50) and 210 healthy controls (males/females: 135/75)). First, the data-driven methodology, named co-activation pattern analysis, was applied to investigate the dynamic features of nucleus accumbens (the core region involved in craving/reward processing and addiction)-centered brain networks in IGD. Further, machine learning analysis was conducted to investigate the prediction effect of the dynamic features on participants' addiction severity.Results: Compared to controls, subjects in the IGD group showed decreased resilience, betweenness centrality and occurrence in the prefrontal-striatal neural circuit, and decreased in-degree in the striatal-default mode network circuit. Moreover, these decreased dynamic features could significantly predict participants' addiction severity.Limitations: The causal relationship between IGD and the abnormal dynamic features cannot be identified in this study. All the subjects were university students.Conclusions: The present results revealed the underlying brain networks of uncontrollable craving and game-seeking behaviors in individuals with IGD during rest. The decreased dynamics of the prefrontal-striatal and striatal-default mode network neural circuits might be potential biomarkers for predicting the addiction severity of IGD and potential targets for effective interventions to reduce game craving of this disorder. [ABSTRACT FROM AUTHOR]

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are two major addiction disorders that result in substantial financial loss. Identifying the similarities and differences between these two disorders is important to understand substance addiction and behavioral addiction. The current study was designed to compare these two disorders utilizing dynamic analysis. Resting-state data were collected from 35 individuals with IGD, 35 individuals with TUD and 35 healthy controls (HCs). Dynamic coactivation pattern analysis was employed to decipher their dynamic patterns. IGD participants showed decreased coactivation patterns within the default mode network (DMN) and between the DMN and the salience network (SN). The SN showed reduced coactivation patterns with the executive control network (ECN) and DMN, and the ECN showed decreased coactivation patterns with the DMN. In the TUD group, the DMN exhibited decreased coactivation patterns with the SN, the SN exhibited reduced coactivation patterns with the DMN and ECN, and the ECN showed decreased coactivation patterns with the DMN and within the ECN. Furthermore, the triple network model was fitted to the dynamic properties of the two addiction disorders. Decoding analysis results indicated that addiction-related memory and memory retrieval displayed similar dysfunctions in both addictions. The dynamic characteristics of IGD and TUD suggest that there are similarities in the dynamic features between the SN and DMN and differences in the dynamic features between the DMN and ECN. Our results revealed that the two addiction disorders have dissociable brain mechanisms, indicating that future studies should consider these two addiction disorders as having two separate mechanisms to achieve precise treatment for their individualized targets. • Internet gaming disorder and tobacco use disorder share similarities and difference among salience network, default mode network and executive control network in dynamic properties. • Internet gaming disorder and tobacco use disorder showed similar dynamic features between salience network and default mode network. • Internet gaming disorder and tobacco use disorder depicted different dynamic properties between default mode network and executive control network. • The coactivation pattern dynamic analysis and independent component analysis were utilized to compare internet gaming addicts, smoking addicts and healthy controls. [ABSTRACT FROM AUTHOR]

Traditional plant protection machinery cannot apply pesticides according to the actual growth demand of crops, which causes a lot of pesticide waste and serious environmental pollution. Based on this, an intelligent variable-rate application system based on 3D LiDAR (light detection and ranging) scanning and PWM (pulse-width modulation) control for maize canopy was developed in this paper. After completing the performance testing, the system was mounted on a lightweight high-clearance self-propelled sprayer by remote controlling with an operating width of 6.0 m, and a ground gap of 2.0 m. And the actual operational performance of the sprayer showed that the prediction error of LiDAR for plant height was within 10%, which illustrated the accuracy of the detection system and the reliability of the variable application based on the plant height change. And the variable-rate system could adjust the spray volume in real-time according to the plant height change. The penetration rate of the upper, middle, and bottom layers maintained a relatively stable state (upper > middle > bottom) at variable-rate application and could reach the normal application level. This study can provide new ideas for efficient pests and diseases control of high stalk crops, especially suitable for small fields, and gives a reference for the structural design of new precise variable-rate application machinery and performance optimization of efficient application technology. • A complete intelligent application system has been developed. • A reliable decision model of application quantity is established. • The intelligentsprayer meets the spraying technology requirements. [ABSTRACT FROM AUTHOR]

• Baoyuan decoction (BYD) effectively decreases atherosclerotic lesions in ApoE-/- mice, without affecting plasma lipid levels. • BYD suppresses the elevated levels of 9/13-hydroxyoctadecadienoic acid (9/13-HODE) in mouse feces. • BYD prevents the upregulation of PPARγ mediated CD36 induced by 9/13-HODE, the main peroxidized fatty acid in oxLDL in macrophages. • BYD inhibits the lipid deposition in macrophages through the regulation of the Src/MMK4/JNK pathway. Background: Baoyuan decoction (BYD) has been widely utilized as a traditional prescription for the treatment of various conditions such as coronary heart disease, aplastic anemia, and chronic renal failure. However, its potential efficacy in improving atherosclerosis has not yet been investigated. Purpose : Our research aimed to assess the potential of BYD as an inhibitor of atherosclerosis and uncover the underlying mechanism by which it acts on foam cell formation. Study Design and Methods : High-fat diet-induced ApoE-/- mice were employed to explore the effect of BYD on atherosclerosis. The differential metabolites in feces were identified and analyzed by LC-Qtrap-MS. In addition, we utilized pharmacological inhibition of BYD on foam cell formation induced by oxLDL in THP-1 cells to elucidate the underlying mechanisms specifically in macrophages. Results : The atherosclerotic plaque burden in the aortic sinus of ApoE-/- mice was notably reduced with BYD treatment, despite no significant alterations in plasma lipids. Metabolomic analysis revealed that BYD suppressed the increased levels of peroxidized fatty acids, specifically 9/13-hydroxyoctadecadienoic acid (9/13-HODE), in the feces of mice. As a prominent peroxidized fatty acid found in oxLDL, we confirmed that 9/13-HODE induced the overexpression of CD36 in THP-1 macrophages by upregulating PPARγ. In subsequent experiments, the decreased levels of CD36 triggered by oxLDL were observed after BYD treatment. This decrease occurred through the regulation of the Src/MMK4/JNK pathway, resulting in the suppression of lipid deposition in THP-1 macrophages. Conclusions : These results illustrate that BYD exhibits potential anti-atherosclerotic effects by inhibiting CD36 expression to prevent foam cell formation. [Display omitted] [ABSTRACT FROM AUTHOR]

Border-associated macrophages (BAMs) are tissue-resident macrophages that reside at the border of the central nervous system (CNS). Since BAMs originate from yolk sac progenitors that do not persist after birth, the means by which this population of cells is maintained is not well understood. Using two-photon microscopy and multiple lineage-tracing strategies, we determine that CCR2+ monocytes are significant contributors to BAM populations following disruptions of CNS homeostasis in adult mice. After BAM depletion, while the residual BAMs possess partial self-repopulation capability, the CCR2+ monocytes are a critical source of the repopulated BAMs. In addition, we demonstrate the existence of CCR2+ monocyte-derived long-lived BAMs in a brain compression model and in a sepsis model after the initial disruption of homeostasis. Our study reveals that the short-lived CCR2+ monocytes transform into long-lived BAM-like cells at the CNS border and subsequently contribute to BAM populations. [Display omitted] • Border-associated macrophages (BAMs) partially self-repopulate after acute depletion in mice • CCR2+ monocytes engraft brain border and transform into long-lived BAM-like cells • The BAM-like cells replenish the BAMs under diseased conditions with an initial loss of BAMs • Microglia do not contribute to the BAM repopulation In this study, Wang et al. demonstrate in mouse models that short-lived CCR2+ monocytes engraft the brain border and transform into long-lived BAM (border-associated macrophage)-like cells to replenish the BAMs after acute depletion or in brain diseases where an initial loss of BAMs occurs, such as brain compression and meningitis. [ABSTRACT FROM AUTHOR]

Multifunctional materials with photothermal and electrothermal effects have garnered considerable attention for solving the icing problem. Although great progress has been made in the field of anti-icing/deicing, the low electrothermal performance, complicated fabrication methods, and low durability restrict their widespread application. Here, we fabricate multiscale hybrid-structured femtosecond laser-induced graphene (FsLIG) on polyimide (PI) substrates using femtosecond laser direct writing technology in ambient air, and apply the FsLIG to all-day anti-icing/deicing. With the optimized laser scanning speed, the as-fabricated surface exhibits high light absorption rate (∼98.5%) in the range of 220–1400 nm and low sheet resistance (∼18.2 Ω sq−1), which bestows outstanding photo-electro-thermal effects on the FsLIG surface. Under 1.0 sun illumination or an applied voltage of 4 V, the average surface temperature can rise to ∼69.3 °C or ∼193.1 °C within 30 s. As a result, the FsLIG is successfully applied in anti-icing/deicing. The FsLIG surface realizes anti-icing and deicing when exposed to a sunlight intensity or an applied voltage of 1.0 sun or 2 V. The photo-electro-thermal material developed in this work, along with its simple preparation method, might have broad application prospects in the field of anti-icing/deicing. [Display omitted] • Femtosecond laser-induced graphene (FsLIG) is formed on polyimide film. • Multiscale hybrid-structures provide a high average light absorption rate of 98.5%. • High degree of graphitization of FsLIG delivers a low sheet resistance of 18.2 Ω sq−1. • Anti-Icing/deicing tests are conducted using photothermal and electrothermal effects. • A conceptual schematic of all-day efficient anti-icing/deicing system is proposed. [ABSTRACT FROM AUTHOR]

In recent years, machine learning has emerged as a powerful computational tool and novel problem-solving perspective for physics, offering new avenues for studying strongly interacting QCD matter properties under extreme conditions. This review article aims to provide an overview of the current state of this intersection of fields, focusing on the application of machine learning to theoretical studies in high energy nuclear physics. It covers diverse aspects, including heavy ion collisions, lattice field theory, and neutron stars, and discuss how machine learning can be used to explore and facilitate the physics goals of understanding QCD matter. The review also provides a commonality overview from a methodology perspective, from data-driven perspective to physics-driven perspective. We conclude by discussing the challenges and future prospects of machine learning applications in high energy nuclear physics, also underscoring the importance of incorporating physics priors into the purely data-driven learning toolbox. This review highlights the critical role of machine learning as a valuable computational paradigm for advancing physics exploration in high energy nuclear physics. [ABSTRACT FROM AUTHOR]

An air-stable mononuclear complex of bis(pentamethylcyclopentadienyl) zirconium pentafluorbezenesulfonate was successfully synthesized by treating C 6 F 5 SO 3 Ag with [(CH 3 ) 5 Cp] 2 ZrCl 2 , which showed the cationic uninuclear structure of [{(CH 3 ) 5 Cp} 2 Zr(CH 3 CN) 2 (H 2 O)][OSO 2 C 6 F 5 ] 2 · CH 3 CN ( 1 ) confirmed by the X-ray analysis. Complex 1 was also characterized by other techniques and found to have the good nature of air-stability, water tolerance, thermally-stability and strong Lewis-acidity. Moreover, the complex showed high catalytic activity and recyclability in catalytic epoxide ring-opening reactions by amines or alcohols. This catalytic system affords a simple and efficient approach for synthesis of β -amino alcohols or β -alkoxy alcohols. [ABSTRACT FROM AUTHOR]

• Grocery taxes affect food expenditure allocations and consequently increase body weight. • Increases in grocery taxes relative to restaurant taxes incentivize low-income households to substitute restaurant foods for grocery foods. • The low-income individuals and overweight individuals are the two most vulnerable cohorts of the general population to grocery taxes. • The Supplemental Nutrition Assistance Program shelters its participants from severe influence of grocery taxes on gaining body weight. We examine the impacts of grocery food sales taxes on body weight, grocery food expenditures, and restaurant food expenditures from both a theoretical and empirical perspective. Theoretically, grocery taxes affect food expenditure allocations by changing the prices of grocery foods relative to restaurant foods consequently influencing body weight because restaurant foods are generally higher in calories and less healthy. This theory is tested empirically using six waves of Panel Study Income Dynamics (PSID) panel data conducted from 2007 through 2017. We find that increases in grocery taxes relative to restaurant taxes incentivize low-income households to substitute restaurant foods in place of grocery foods. The results indicate that a one-percentage-point increase in the grocery tax rate relative to the restaurant tax rate leads to an increase in the body mass index (BMI) of 0.061, which translates to a weight gain of about 0.361 lb. This result is largely driven by overweight individuals and low-income individuals who do not participate in the Supplemental Nutrition Assistance Program. These are the two most vulnerable cohorts of the general population to grocery taxes. [ABSTRACT FROM AUTHOR]

Although numerous neuroimaging studies have detected structural and functional abnormality in specific brain regions and connections in subjects with Internet gaming disorder (IGD), the topological organization of the whole-brain network in IGD remain unclear. In this study, we applied graph theoretical analysis to explore the intrinsic topological properties of brain networks in Internet gaming disorder (IGD). 37 IGD subjects and 35 matched healthy control (HC) subjects underwent a resting-state functional magnetic resonance imaging scan. The functional networks were constructed by thresholding partial correlation matrices of 90 brain regions. Then we applied graph-based approaches to analysis their topological attributes, including small-worldness, nodal metrics, and efficiency. Both IGD and HC subjects show efficient and economic brain network, and small-world topology. Although there was no significant group difference in global topology metrics, the IGD subjects showed reduced regional centralities in the prefrontal cortex, left posterior cingulate cortex, right amygdala, and bilateral lingual gyrus, and increased functional connectivity in sensory-motor-related brain networks compared to the HC subjects. These results imply that people with IGD may be associated with functional network dysfunction, including impaired executive control and emotional management, but enhanced coordination among visual, sensorimotor, auditory and visuospatial systems. [ABSTRACT FROM AUTHOR]