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Cu–Fe composite is a promising candidate for electromagnetic shielding material, while it exhibits poor corrosion resistance due to the different corrosion potential of Fe particles and Cu matrix. In this study, a Cu–Fe composite was processed by multi-directional compression. The effect of multi-directional compression on the mechanical properties of the Cu–Fe composite was evaluated by the tensile test, and the effect of multi-directional compression on the corrosion properties was evaluated by the weight loss test and electrochemical measurement. After 12 compression passes, the yield strength of the Cu–Fe composite is more than two times higher than that of the initial state, and the corrosion rate decreases to nearly half compared to the initial state. Microstructure examination reveals that high density of twin boundaries were generated by multi-directional compression, which could effectively refine the grain size of Cu matrix and improve the strength of Cu–Fe composite. In addition, twin boundaries would reduce the Volta potential difference between Cu matrix and Fe particles, which could effectively inhibit galvanic corrosion, finally leading to a high corrosion resistance of the Cu–Fe composite.

Abstract Modern data center topologies often take the form of a multi-rooted tree with rich parallel paths to provide high bandwidth. However, various path diversities caused by traffic dynamics, link failures and heterogeneous switching equipment widely exist in the production datacenter network. Therefore, the multi-path load balancer in data center should be robust to these diversities. Although prior fine-grained schemes such as RPS and Presto make the best use of available paths, However, they are prone to experiencing packet reordering problem under the asymmetric topology. The coarse-grained solutions such as ECMP and LetFlow effectively avoid packet reordering, but easily lead to under-utilization of multiple paths. To cope with these inefficiencies, we propose a load balancing mechanism called PDLB, which adaptively adjusts flowcell granularity according to path diversity. PDLB increases flowcell granularity to alleviate packet reordering under large degrees of topology asymmetry, while reducing flowcell granularity to obtain high link utilization under small degrees of topology asymmetry. PDLB is only deployed on the sender without any modification on switch. We evaluate PDLB through large-scale NS2 simulations. The experimental results show that PDLB reduces the average flow completion time by up to $$\sim$$ ∼ 8-53% over the state-of-the-art load balancing schemes.

Summary: Understanding the cellular composition of a disease-related tissue is important in disease diagnosis, prognosis, and downstream treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technique have allowed the measurement of gene expression profiles for individual cells. However, scRNA-seq is still too expensive to be used for large-scale population studies, and bulk RNA-seq is still widely used in such situations. An essential challenge is to deconvolve cellular composition for bulk RNA-seq data based on scRNA-seq data. Here, we present DeepDecon, a deep neural network model that leverages single-cell gene expression information to accurately predict the fraction of cancer cells in bulk tissues. It provides a refining strategy in which the cancer cell fraction is iteratively estimated by a set of trained models. When applied to simulated and real cancer data, DeepDecon exhibits superior performance compared to existing decomposition methods in terms of accuracy. The bigger picture: Estimating the malignant cell fraction accurately and cheaply is essential for cancer diagnosis and prognosis. Although single-cell RNA sequencing (scRNA-seq) can provide accurate information on malignant cell fraction, it is too labor intensive and expensive for clinical application. Bulk RNA-seq, on the other hand, is cost effective and widely used in clinical settings but traditionally only provides the average gene expression profiles of a cancer cell population. Using reference malignant and normal scRNA-seq data, DeepDecon provides an iterative deep-learning-based computational method for accurate estimation of the fraction of malignant cells based on the bulk-averaged gene expression profiles. This study used DeepDecon to accurately estimate acute myeloid leukemia (AML), neuroblastoma, and head-and-neck squamous cell carcinoma (HNSCC) cell fractions from bulk RNA-seq data.

Minimally invasive esophagectomy for cancer surgery remains associated with significant morbidity and surgical complications across the globe. Non-intubation video-assisted thoracic surgery (NIVATS) has been successfully employed in lung resection in recent years, but there are few reported cases with regard to the safety and feasibility of this approach in radical esophagectomy for patients with esophageal cancers. We present 4 consecutive cases with esophageal squamous cell carcinoma (ESCC) who received minimally invasive McKeown’s esophagectomy under non-intubation general anesthesia from November 2022 to April 2023. All these patients were aged from 55 to 75 years old and were pathologically diagnosed with ESCC. All procedures of McKeown’s esophagectomy in these patients were completed with non-invasive ventilation by laryngeal mask-assisted anesthesia. Operation duration ranged from 185 to 395 minutes and the estimated blood loss ranged from 25 to 60 ml in these 4 cases. No severe hypoxia was observed and transient hypercapnia was resolved intraoperatively. None of them was converted to endotracheal intubation with mechanical ventilation or to thoracotomy. The number of retrieved lymph nodes in mediastinum were 21-27 and all patients received R0 surgery with pathological stage as T1bN0M0 to T3N2M0. There was no serious complication (Clavien-Dindo grade III-IV) observed perioperatively and they were all discharged 11-14 days after the surgery with resumption of oral feeding. They are all alive without tumor recurrence at the date of data collection. The safety and efficacy of minimally invasive esophagectomy with non-invasive ventilation by laryngeal mask-assisted anesthesia for patients with ESCC are warranted for explored in a larger cohort study.

Objective To assess the impact of HRQoL in patients hospitalised with COVID-19-related SARI at 1 year post discharge, focusing on the potential impact of age, frailty, and disease severity.Method Routinely collected outcome data on 1207 patients admitted with confirmed COVID-19 related SARI across all three secondary care sites in our NHS trust over 3 months were assessed in this retrospective cohort study. Of those surviving 1 year, we prospectively collected 36-item short form (SF-36) HRQoL questionnaires, comparing three age groups (

Tamusu mudstone is a potential geological medium for high-level radioactive waste disposal in China. In this study, the mechanical behavior of Tamusu mudstone was examined through a series of triaxial compression experiments conducted under varying confining pressures (5, 10, 15, and 20 MPa) at two temperatures: 22 °C and 80 °C. The experimental findings revealed that heating strengthened the mechanical properties of Tamusu mudstone when compared under the same hydro-mechanical conditions. The strength, elastic modulus, cohesion, and friction angle of Tamusu mudstone increased after being subjected to elevated temperatures. However, the brittleness of Tamusu mudstone was also enhanced compared to its behavior at room temperature. The investigation into the post-peak deformation properties of Tamusu mudstone indicated a gradual failure process, which possibly involved multiple stress drops. As the number of stress drops increased, the rate of deviatoric stress reduction gradually decreased, while the corresponding plastic deformation progressively increased. This behavior was attributed to the weakened cohesion and strengthened friction of the Tamusu mudstone. This study contributes to the understanding of thermomechanical phenomena in argillaceous rocks and provides important input parameters for theoretical and numerical modeling in the safety assessment of HLW repositories.

Abstract Datacenter applications generate diverse flows, including deadline flows and non‐deadline flows. The deadline flows require to complete within strict deadline, while non‐deadline flows seek a shorter flow completion time. The state‐of‐the‐art deadline‐aware methods either transmit deadline flows with best‐effort at high priority, resulting in the starvation of non‐deadline flows, or blindly restrict the sending rates of deadline flows, leading to a high deadline missing ratio. To meet the different requirements of mix‐flows, a novel traffic‐aware rate control (TRC) method is proposed. TRC dynamically adjusts the sending rates of deadline flows according to their deadlines and the predicted future traffic patterns. If the intense competition is predicted among deadline flows, TRC will adopt a more aggressive manner to transmit the current deadline flows to avoid bandwidth contention in the future, reducing the deadline missing ratio. Otherwise, TRC will conservatively transmit deadline flows and complete these flows near their respective deadlines, relinquishing the excess bandwidth to non‐deadline flows. Meanwhile, TRC schedules non‐deadline flows in accordance with their sizes, minimizing the average FCT. The performance of TRC in large‐scale scenarios is evaluated through NS2 simulations. The test results show that TRC reduces the deadline missing ratio of deadline flows and the FCT of non‐deadline flows by up to 69.5% and 78.7% compared to the state‐of‐the‐art deadline‐aware schemes, respectively.

With the growing significance of green chemistry in organic synthesis, electrochemical oxidation has seen rapid development. Compounds undergo oxidation–reduction reactions through electron transfer at the electrode surface. This article proposes the use of electrochemical methods to achieve cleavage of the benzyl C–N bond. This method selectively oxidatively cleaves the C–N bond without the need for metal catalysts or external oxidants. Additionally, primary, secondary, and tertiary amines exhibit good adaptability under these conditions, utilizing water as the sole source of oxygen.

Abstract A triple‐objective optimal design method for AC filters in high voltage direct current (HVDC) system based on an improved multi‐objective evolutionary algorithm based on decomposition (MOEA/D) is proposed. A triple‐objective optimisation mathematical model including total harmonic distortion (THD) on AC side voltage, investment cost of AC filters and telephone harmonic form factor (THFF) is established. An improved MOEA/D is proposed to realise the triple‐objective optimal design for AC filters more efficiently. The improved MOEA/D adds a particular mutation operator, which can not only to prevent MOEA/D from getting stuck at local optimum but also accelerate the convergence to the optimum solution while the algorithm approaches the neighbourhood of the optimum solution. A three‐dimensional fuzzy evaluation system is designed to select the optimum solution of the triple‐objective optimisation. A case of ±500 kV HVDC system is simulated. Taking the ±500 kV HVDC system as the prototype system, a dynamic simulation experimental platform of the rectification system of the direct current transmission system with AC filters is designed and established based on the similarity principle. Both the simulation and experimental results verify that the proposed method have excellent performance.

The predictive business process monitoring mainly focuses on the performance prediction of business process execution, i.e., predicting the next activity, the execution time of the next activity, and the remaining time, respectively, for an ongoing process instance based on the knowledge gained from historical event logs. Although there is a specific relationship between these three tasks, recent research has focused on training separate prediction models for each task, resulting in high costs and time complexity. Additionally, existing technologies are limited in their ability to capture long-distance dependent features in process instances, further impeding prediction performance. To address these issues, this paper proposes the MTLFormer approach, which leverages the self-attention mechanism of the Transformer network and conducts multi-task parallel training through shared feature representation obtained from different tasks. Our approach reduces the time complexity of model training while simultaneously improving prediction performance. We extensively evaluate our approach on four real-life event logs, demonstrating its capability to achieve multi-task online real-time prediction and effectively improve prediction performance.

Abstract Modern data centers have widely deployed lots of cluster computing applications such as MapReduce and Spark. Since the coflow/task abstraction can exactly express the requirements of cluster computing applications, various task-based solutions have been proposed to improve application-level performance. However, most of solutions require modification of the applications to obtain task information, making them impractical in many scenarios. In this paper, we propose a Bayesian decision-based Task Prediction mechanism named BTP to identify task and predict the task-size category. First, we design an automatic identification mechanism to identify tasks without manually modifying the applications. Then we leverage bayesian decision to predict the task-size category. Through a series of large-scale NS2 simulations, we demonstrate that BTP can accurately identify task and predict the task-size category. More specifically, BTP achieves 96% precision and 92% recall while obtaining accuracy by up to 98%.

Blazars are a subject of intense debate, specifically regarding their jet launch and emission mechanisms, and the origins of their γ -ray radiation. To explore these issues, we have built a comprehensive sample of flat-spectrum radio quasars (FSRQs), with well-characterized spectral energy distribution. This study aims to elucidate the dominant jet launch mechanism and the main processes behind the inverse Compton (IC) component. Additionally, we seek to pinpoint the location of the γ -ray dissipation region relative to the central black hole, denoted as R _γ . Our approach involves a detailed analysis of broad-line region (BLR) emission, from which we derive robust estimates of the black hole masses using two distinct virial techniques. This enables us to constrain the jet power across a wide array of FSRQs. Our findings lead to several significant conclusions: (i) The correlation of jet power with black hole mass allows us to test the Blandford–Znajek, Blandford–Payne, and hybrid mechanisms. We find that the hybrid mechanism is most effective in explaining the jet power observed in the majority of FSRQs; (ii) The IC component of the γ -rays in FSRQs is predominantly due to the external Compton process. (iii) Through simulations, we determine the minimum and maximum values of R _γ (the γ -ray dissipation region) and conclude it is located outside the BLR. This conclusion is derived from the variability timescale analysis.

Accurate delineation of individual teeth and alveolar bones from dental cone-beam CT images is an essential step in digital dentistry for precision dental healthcare. Here, the authors present a deep learning system for efficient, precise, and fully automatic segmentation of real-patient CBCT images presenting highly variable appearances.

Abstract Background Circular RNAs (circRNAs) play an important role in the progression of non-small cell lung cancer (NSCLC), especially under tumor hypoxia. However, the precise functions and underlying mechanisms of dysregulated circRNAs in NSCLC are largely unknown. Methods High-throughput RNA sequencing was performed to identify significantly expressed circRNAs in NSCLC tissues. The functions of circ-0001875 in NSCLC cells were investigated in vitro and in vivo. The regulatory relationships of circ-0001875, miR-31-5p and SP1 were examined by dual luciferase reporter assays and rescue experiments. The signal pathway of epithelial-to-mesenchymal transition and the formation of filopodia were analyzed by western blot and immunofluorescence staining. The binding of SP1 to Alu elements was evaluated by RNA immunoprecipitation, and the HIF1α and SP1 interaction was detected by co-immunoprecipitation. Results We identified the novel Has_circ_0001875 as a significantly upregulated circRNA in NSCLC tissues and cell lines. circ-0001875 promoted the proliferation and metastasis of NSCLC both in vitro and in vivo, and induced NSCLC cells to extend filopodia. Mechanistically, circ-0001875 sponged miR-31-5p to regulate SP1, influencing epithelial-to-mesenchymal transition via the TGFβ/Smad2 signal pathway. SP1 negatively regulated circ-0001875 formation through an AluSq-dependent feedback loop, which was disrupted by competitive binding of HIF1α to SP1 under hypoxia condition. The circ-0001875/miR-31-5p/SP1 axis was associated with the clinical features and prognosis of NSCLC patients. Conclusions Our results revealed that the circ-0001875/miR-31-5p/SP1 axis and the complex regulatory loops influence NSCLC progression. These findings provide new insights into the regulation of circRNA formation under tumor hypoxia.

The design and long-term safety of geological repositories for high-level radioactive waste (HLW) are dependent on the precise determination of the thermophysical parameters of mudstone. However, there is no relevant literature on the study of the thermophysical properties of Tamusu mudstone, a prospective rock for HLW disposal in China under the complex HLW disposal conditions. Therefore, in this paper, Tamusu mudstone is examined, and its thermophysical properties are tested at temperatures in the range of 25–80 °C with and without the influence of external forces. The thermophysical parameters exhibited significant anisotropic characteristics and were strongly correlated with temperature. The increase in temperature increases the specific heat capacity while lowering the thermal diffusivity. Due to the external force, the anisotropy of the thermophysical parameters decreases, enhancing the ability of the mudstone to transfer thermal energy. Furthermore, the aforementioned phenomena were interpreted from a microscopic perspective. This work can aid in the thermal-related physical phenomena of argillaceous rock and provide key input parameters for both analytical and numerical modeling in the safety assessment of HLW repositories, and other underground facilities at high temperatures.

Huang et al apply and benchmark multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. Their approach reveals potential genome functions and gene regulatory mechanisms from gene expression to neuronal electrophysiology.

Immiscible Cu-Fe alloys exhibit poor corrosion resistance due to different corrosion potentials between the constituent phases, which limits their application. In this paper, a composite gradient-structured Cu-10 wt.%Fe plate was prepared via the ultrasonic surface rolling process (USRP). The microstructure evolution, mechanical properties and corrosion behavior were studied. The results demonstrate that USRP effectively enhances both the strength and corrosion resistance of the Cu-10Fe alloy. The improved strength is related to the combined effects of Hall–Petch strengthening, dislocation strengthening, and additional strengthening resulting from homogeneous deformation between the surface layer and the matrix. The enhanced corrosion resistance is primarily attributed to the refined microstructure of the surface layer after USRP, which facilitates the formation of a protective passivation film.

Taking two types of silty clays from Nanjing and Wuxi as the research object，the static strength of these two kinds of soil in saturated and unsaturated states was measured using the TSZ-2 automatic triaxial instrument. The difference in shear strength between the original and disturbed samples of the soil in the saturated state，and the influence of the initial water content of the soil in the unsaturated state on the shear strength are studied. The comparison of test results shows that Wuxi soil has the characteristics of smaller water content，higher density，smaller void ratio，smaller compressibility，and higher static strength than Nanjing soil. However，the disturbance effect has a greater impact on Wuxi saturated soil compared to Nanjing soil. The shear strength of unsaturated cohesive soil is related to the particle gradation，resulting in a difference in the shear strength of the two types of soil.

Abstract Modern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

Abstract Understanding cell-type-specific gene regulatory mechanisms from genetic variants to diseases remains challenging. To address this, we developed a computational pipeline, scGRNom (single-cell Gene Regulatory Network prediction from multi-omics), to predict cell-type disease genes and regulatory networks including transcription factors and regulatory elements. With applications to schizophrenia and Alzheimer’s disease, we predicted disease genes and regulatory networks for excitatory and inhibitory neurons, microglia, and oligodendrocytes. Further enrichment analyses revealed cross-disease and disease-specific functions and pathways at the cell-type level. Our machine learning analysis also found that cell-type disease genes improved clinical phenotype predictions. scGRNom is a general-purpose tool available at https://github.com/daifengwanglab/scGRNom .

Abstract With the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

Due to the explosive growth of all kinds of Internet services, data centers have become an irreplaceable and vital infrastructure to support this soaring trend. Compared with traditional networks, data center networks (DCNs) have unique features, such as high bandwidth, low latency, many-to-one communication mode, shallow buffered switches, and multi-root topology. These new characteristics pose a lot of challenges to previous network technics (e.g., Ethernet, Equal Cost Multi-path (ECMP), TCP), making them hard to adapt to DCNs and leading to severe performance degradation. In order to solve these challenges, DCNs have attracted a lot of attention from the industry and academia in recent years, and many new mechanisms in different layers are proposed to improve the transmission performance of data center networks. In the meantime, many surveys have emerged currently to introduce the current research of data center networks. However, previous surveys of DCNs mainly focus on only one specific network layer, making them difficult for readers to know about advanced researches on a holistic level. To help readers comprehend the current research progress of data center networks quickly, we employ a multi-layered top down taxonomy to classify the literature and propose several probable dimensions for future research in this area.

Previous approach lacks the ability to produce large and continuously tunable strain states due to the limited number of available substrates. Here, the authors demonstrate strain-induced ferroelectricity in SrTiO3 membranes by laminating freestanding SrTiO3 films onto a stretchable polymer.

Abstract Background Sex hormone-binding globulin (SHBG) has been reported to be a risk factor associated with the development of arthritis by previous observational studies more so of three common forms of arthritis: osteoarthritis (OA), rheumatoid arthritis (RA), and ankylosing spondylitis (AS). This study aimed to determine whether the concentrations of circulating SHBG are causally associated with the risk of OA, RA, and AS. Methods The two-sample Mendelian randomization (MR) approach was used for this study. The inverse-variance-weighted (IVW) method was used for the main analysis. Single-nucleotide polymorphisms (SNPs) associated with SHBG were selected from a large genome-wide association study (GWAS) of 28,837 European individuals. The summary statistics for OA, RA, and AS were extracted from the UK Biobank Resource (n = 361,141) and a GWAS dataset (n = 455,221). Results Positive causal associations were found between circulating SHBG concentrations and OA (effect = 1.086; 95% CI, 1.009 to 1.168; P = 0.027) and RA (effect = 1.003; 95% CI, 1.000 to 1.007; P = 0.047) in overall analyses. However, there was no evidence of association between SHBG levels and AS. Based on the stratification of skeletal sites, SHBG levels were found to be significantly associated with hip OA (effect = 1.423; 95% CI, 1.219 to 1.660; P = 7.753 × 10−6). However, this was not the case with knee OA. Conclusions There were positive causal effects of circulating SHBG on the development of OA and RA. Moreover, there was a site-specific association between SHBG and hip OA. Evidently, measurement of SHBG in serum could be valuable in the clinical assessment of arthritis especially in early screening and prevention of OA and RA. However, the mechanisms by which SHBG plays causal roles in the development of arthritis require further investigations.

Abstract In the data center networks, multipath transmission control protocol(MPTCP) uses multiple subflows to balance traffic over parallel paths and achieve high throughput. Despite much recent progress in improving MPTCP performance in data center, how to adjust the number of subflows according to network status has remained elusive. In this paper, we reveal theoretically and empirically that controlling the number of concurrent subflows is very important in reducing flow completion time (FCT) under network dynamic. We further propose a novel design called MPTCP_OPN, which adaptively adjusts the number of concurrent subflows according to the real-time network state and flexibly shifts traffic from congested paths to mitigate the high tail latency. Experimental results show that MPTCP_OPN effectively reduces the timeout probability caused by full window loss and flow completion time by up to 50% compared with MPTCP protocol.

At present, designing museum art derivatives attracts more and more attention. Experts in the field often use hand painting or image editing software to process images. This is time-consuming work and requires professional knowledge for design. In order to address this problem, by exploiting the advanced computer simulation and image processing techniques, we develop a novel museum art derivative design system, named NK-CDS. This system consists of element operation and element application modules. Given a cultural relic image, the user extracts the interest region in the image, then processes the appearance of the element by denoising, sharpening, etc. Finally, with the application interface, the user can flexibly map the processed elements to any location of a lifestyle model. This system is intuitive and easy to operate, which can improve the design efficiency of museum derivatives and inspire ideas for creative culture product design.

Evaluating the pyrolysis of lignocellulose via theoretical and computational approaches is of great importance for the efficient utilization of biomass. In this work, the dynamic changes in physicochemical properties of eucalyptus and bamboo during plant-rich metallic element-catalyzed pyrolysis process were investigated, and their thermal decomposition behaviors were explored by kinetic analysis. Results showed that the metal absorption capacity and thermal stability of eucalyptus were better than those of bamboo. The temperatures corresponding to the initial devolatilization and the highest weight loss value of eucalyptus/bamboo decreased in the catalysis order of Mg > Fe > Ca > Cu > K > Na. Fourier-transform infrared (FT-IR) results showed that the thermal stability of ester bond of glucuronoarabinoxylan was higher than that of acetyl groups. The maximum weight loss rate could be observed for samples with the lowest metal-loaded concentration (5%). Moreover, Mg and Fe presented the better catalytic performance for facilitating the lignocellulose pyrolysis in comparison with other investigated metallic elements.

With the widespread availability of multi-homed devices, enabling multiple paths by utilizing multipath TCP (MPTCP) in current networks is a common practice to improve the performance and robustness. Although MPTCP improves both bandwidth efficiency and network reliability, the transmission performance for short flows can become worse than regular single path TCP when the concurrent subflows transferred through a shared bottleneck due to MPTCP’s aggressive slow start behavior, which is uncoupled, and each subflow behaves independently as regular TCP, affecting MPTCP and concurrent traffic at the bottleneck. In this paper, we first reveal that the MPTCP’s aggressive behavior in slow start causes timeouts and throughput collapse. We further present the design and implementation of GSAM, which employs the theoretical analysis to derive the appropriate threshold for smoothing the congestion window growth in GSAM according to the network conditions in slow start phase and leverages congestion detection and control at end-host to avoid buffer overflow under concurrent MPTCP connections with multiple subflows sharing the bottleneck. The experimental results based on the real implementations show that the GSAM reduces the completion time by up to 80% while retaining high Goodput for large flows as MPTCP.

In data center networks, MultiPath TCP (MPTCP) obtains both higher network utilization and fairer allocation of capacity by exploring multiple paths simultaneously. However, MPTCP experiences more queue oscillation in switch buffer with the increasing of the number of subflows. When using explicit congestion notification as the congestion indication to track the queue length in switch buffer, it is difficult for MPTCP to capture the accurate congestion state, resulting in wrong behavior in congestion control. Therefore, we propose an enhanced MPTCP protocol, namely, advanced MPTCP (AMP), which adjusts the time granularity of the congestion detection and control under a different number of subflows. The test results show that compared with Linked Increases Algorithm and eXplicit MultiPath, AMP achieves lower latency for small flows and higher throughput for large flows.

The optoelectronic properties of layered α-MoO3 are greatly limited due to its wide band gap and low carrier concentration. The insertion of hydrogen (H) can effectively tune the band structure and carrier concentration of MoO3. Herein, first-principles calculations were performed to unravel the physical mechanism of a H-doped α-MoO3 system. We found that the modulation of the electronic structure of H-doped MoO3 depends on the doping concentration and position of the H atoms. It was found that the band gap decreases at 8% doping concentration due to the strong coupling between Mo-4d and O-2p orbits when H atoms are inserted into the interlayer. More interestingly, the band gap decreases to an extreme due to the Mo-4d orbit when all the H atoms are inserted into the intralayer only, which has a remarkable effect on light absorption. Our research provides a comprehensive theoretical discussion on the mechanism of H-doped α-MoO3 from the doping positions and doping concentrations, and offers useful strategies on doping modulation of the photoelectric properties of layered transition metal oxides.

PM2.5 and formaldehyde (FA) are major outdoor and indoor air pollutants in China, respectively, and both are known to be harmful to human health and to be carcinogenic. Of all the known chronic health effects, leukaemia is one of the most serious health risks associated with these two pollutants. To explore the influence and underlying mechanisms of exposure to formaldehyde and PM2.5 on hematopoietic toxicity, we systematically studied the toxicity induced in hematopoietic organs: bone marrow (BM); spleen; and myeloid progenitor cells (MPCs). Male Balb/c mice were exposed to: PM2.5 (20, 160 μg/kg·d) at a dose of 40 μL per mouse or formaldehyde (0.5, 3.0 mg/m3) for 8 h per day for 2 weeks or co-exposed to formaldehyde and PM2.5 (20 μg/kg·d PM2.5 + 0.5 mg/m3 FA, 20 μg/kg·d PM2.5 + 3 mg/m3 FA, 160 μg/kg·d PM2.5 + 0.5 mg/m3 FA, 160 μg/kg·d PM2.5 + 3 mg/m3 FA) for 2 weeks. Similar toxic effects were found in the formaldehyde-only and PM2.5-only groups, including significant decrease of blood cells and MPCs, along with decreased expression of hematopoietic growth factors. In addition, individual exposure of formaldehyde or PM2.5 increased oxidative stress, DNA damage and immune system disorder by destroying the balance of Th1/Th2, and Treg/Th17. DNA repair was markedly inhibited by deregulating the mammalian target of rapamycin (mTOR) pathway. Combined exposure to PM2.5 and formaldehyde led to more severe effects. Administration of Vitamin E (VE) was shown to attenuate these effects. In conclusion, our findings suggested that PM2.5 and formaldehyde may induce hematopoietic toxicity by reducing the expression of hematopoietic growth factors, increasing oxidative stress and DNA damage, activating the ‘immune imbalance’ pathway and suppressing the DNA-repair related mTOR pathway. The hematopoietic toxicity induced by combined exposure of PM2.5 and formaldehyde might provide further insights into the increased incidence of hematological diseases, including human myeloid leukaemia.

Abstract Background As newly identified Wnt enhancer, R-spondin gene family members have been linked to various cancers; however, their role in isocitrate dehydrogenase-wildtype subtype of human glioblastoma (GBM) cells remains unknown. Methods Human U87 and U251 cell lines were used to perform the experiments. GBM stem-like cells were enriched in stem cell growth media and induced to differentiate using retinoid acid or growth factor deprivation. Wnthigh and Wntlow subpopulations were isolated and evaluated by MTS, sphere formation, transwell migration and xenograft formation assays. Results R-spondin 2 but not R-spondin 3 potentiates Wnt/β-catenin signaling in GBM cell lines. While R-spondin 2 does not affect cell growth, it induces the expression of pluripotent stem cell markers in combination with Wnt3A. GBM stem-like cells are endowed with intrinsic high activity of β-catenin signaling, which can be further intensified by R-spondin 2. In addition, R-spondin2 promotes stem cell self-renewal and suppresses retinoid acid- or growth factor deprivation-induced differentiation, indicating R-spondin 2 maintains stem cell traits in GBM. On the other hand, we identify subpopulations of GBM cells that show distinctive responsiveness to Wnt/β-catenin signaling. Interestingly, Wnthigh and Wntlow cells display distinctive biologic properties. Moreover, Wnthigh cell-inoculated xenografts exhibit enhanced tumorigenicity and increased expression levels of R-spondin 2 compared to Wntlow cell-inoculated xenografts. Conclusion Our study reveals a novel regulatory mechanisms underlying the over-activation of β-catenin-mediated signaling in the pathogenesis of GBM.

Background/Aims: TGF-β1 is beneficial during early liver disease but is tumor-progressive during late stages especially for hepatocellular carcinoma (HCC). Thus, exploring the underlying mechanisms may provide information about a potentially therapeutic role of TGF-β1 in HCC. Methods: Western blot and real-time quantitative PCR were used to quantify FGFR4 expression in HCC cell lines and a normal liver cell line. After constructing the best silencing FGFR4 expression vector, migration and invasiveness of TGF-β1 in HCC was studied in vitro and in vivo. Western blot was used to study the mechanism of TGF-β1 induction on FGFR4 expression with various inhibitors. Results: HepG2 cell lines had the most FGFR4 expression, and data show that silencing FGFR4 suppressed cell proliferation, invasion and migration in HCC induced by TGF-β1 in vitro and in vivo. Moreover, TGF-β1 induced FGFR4 expression through the ERK pathway. Conclusion: Promoting FGFR4 expression via the ERK pathway, TGF-β1 contributes to HCC invasion and metastasis.

In this study, the manganese-doped manganese–cobalt–iron spinel was prepared by the sol–gel self-combustion method, and its physical and chemical properties were analyzed by XRD (X-ray diffraction analysis), SEM (scanning electron microscope), and VSM (vibrating sample magnetometer). The mercury removal performance of simulated flue gas was tested on a fixed bed experimental device, and the effects of Mn doping amount, fuel addition amount, reaction temperature, and flue gas composition on its mercury removal capacity were studied. The results showed that the best synthesized product was when the doping amount of Mn was the molar ratio of 0.5, and the average mercury removal efficiency was 87.5% within 120 min. Among the fuel rich, stoichiometric ratio, and fuel lean systems, the stoichiometric ratio system is most conductive to product synthesis, and the mercury removal performance of the obtained product was the best. Moreover, the removal ability of Hg0 was enhanced with the increase in temperature in the test temperature range, and both physical and chemical adsorption play key roles in the spinel adsorption of Hg0 in the medium temperature range. The addition of O2 can promote the removal of Hg0 by adsorbent, but the continuous increase after the volume fraction reached 10% had little effect on the removal efficiency of Hg0. While SO2 inhibited the removal of mercury by adsorbent, the higher the volume fraction, the more obvious the inhibition. In addition, in an oxygen-free environment, the addition of a small amount of HCl can promote the removal of mercury by adsorbent, but the addition of more HCl does not have a better promotion effect. Compared with other reported adsorbents, the adsorbent has better mercury removal performance and magnetic properties, and has a strong recycling performance. The removal efficiency of mercury can always be maintained above 85% in five cycles.

Technological advancements have ushered in a new era of global educational development. Artificial Intelligence (AI) holds the potential to enhance teaching effectiveness and foster educational innovation. By utilizing student posture as a proxy, computer vision technology can accurately gauge levels of student engagement. While previous efforts have focused on refining posture classification models, this study uniquely addresses the comprehensive implementation of a real-time posture detection workflow, encompassing software, hardware, and network aspects. The proposed posture detection system leverages surveillance cameras equipped with cutting-edge computer vision technology, specifically employing the Open Visual Inference & Neural Network Optimization (Open VINO) model for precise student posture detection. Data transmission is facilitated using the Message Queuing Telemetry Transport (MQTT) protocol, effectively establishing a seamless posture detection workflow within the classroom setting. To validate the system, video recordings from a real teaching environment (a fifth-grade class in the Chinese compulsory education system) were analyzed, resulting in posture classifications with impressive accuracies of 0.933 for standing, 0.772 for sitting, and 0.959 for hand-raising. Achieving a frame processing time ranging from 109 to 758 milliseconds, the system efficiently delivers real-time posture data to educators. Consequently, the posture detection system developed in this study possesses the capability to intelligently monitor student postures in the classroom, with the potential to enhance teaching quality in smart classrooms.

The improvement of the saccharification of rice straw is one of the strategies to reduce the sophisticated pretreatment that results in high cost and is unfriendly to the environment. We explored the cell wall features in tetraploid rice and highlighted the enhanced saccharification of tetraploid with large biomass. Results showed that lignin content and S/G ratio reduced to 17.09% and 0.37, respectively, in tetraploid straw by the determination of the pyGC-MS method. After the pretreatment, the cellulose crystallinity index decreased from 63.22% to 57.65% in tetraploid straw, which is lower than that of pretreated diploid straw. Surface topological analysis of SEM images indicated that tetraploid straw was more susceptible to the pretreatment. Tetraploid straw showed a strong advantage in the process of enzymatic hydrolysis. The enzyme efficiency reached the highest value of 77.60%, and the rate of enzyme reaction was improved to make the reaction saturated earlier than conventional rice. We concluded that the high saccharification has resulted from the alteration of lignin and cellulose in tetraploid rice. Our research provides an improved green feedstock for bioenergy, and the tetraploid rice straw shows the potential utilization value in bioethanol production.

Bamboo is a gramineous plant widely distributed in China and has great prospects. Normally, local people cut bamboo culm at first year for paper milling or at six years for construction. Understanding lignin changes in bamboo with aging is necessary for better exploring the application of bamboo at different ages and can also promote the application of bamboo more effectively. Based on the previous study, the chemical structure and the lignin content of bamboo at different ages were further explored by FT-IR, GPC, NMR and other chemical methods in this paper. Results showed that the lignin structures of bamboo at different ages were similar with three monomers of S, G and H, but the molecular weight increased with age. Quantitative structure estimation further confirmed that S-type lignin content and S/G ratio of bamboo lignin constantly increased with age.

This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China.Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF.Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P

Cooperative communication is an effective method of improving the transmission performance for vehicular ad hoc networks. However, the rapid movement of vehicles leads to frequent changes in network topology and reduces the probability of successful data transmission on the medium access control (MAC) layer. In this paper, we propose an Optimal Cooperative Ad hoc MAC protocol (OCA-MAC) based on time division multiple access (TDMA). OCA-MAC utilizes multiple cooperative nodes to forward data, so as to improve the probability of successful data transmission. It chooses cooperative nodes according to direct successful transmission probability, communication range between potential helper node and destination node, and available time slot. Meanwhile, in order to avoid excessive transmission redundancy caused by multiple cooperative forwarding, the optimal number of cooperative forwarding nodes is obtained through analysis of a probabilistic model. Simulation results show that OCA-MAC improves the successful data transmission rate and reduces the number of transmission times and transmission delay compared to the multichannel TDMA MAC protocol (VeMAC) and the cooperative ad hoc MAC protocol (CAH-MAC).

Lignocellulose is a widely used renewable energy source on the Earth that is rich in carbon skeletons. The catalytic hydrolysis of lignocellulose over magnetic solid acid is an efficient pathway for the conversion of biomass into fuels and chemicals. In this study, a bamboo-derived carbonaceous magnetic solid acid catalyst was synthesized by FeCl3 impregnation, followed by carbonization and –SO3H group functionalization. The prepared catalyst was further subjected as the solid acid catalyst for the catalytic conversion of corncob polysaccharides into reducing sugars. The results showed that the as-prepared magnetic solid acid contained –SO3H, –COOH, and polycyclic aromatic, and presented good catalytic performance for the hydrolysis of corncob in the aqueous phase. The concentration of H+ was in the range of 0.6487 to 2.3204 mmol/g. Dilute acid and alkali pretreatments of raw material can greatly improve the catalytic activity of bamboo-derived carbonaceous magnetic solid acid. Using the catalyst prepared by 0.25% H2SO4-pretreated bamboo, 6417.5 mg/L of reducing sugars corresponding to 37.17% carbohydrates conversion could be obtained under the reaction conditions of 120 °C for 30 min.

Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstances as well as the reduction of failures. However, under dynamic traffic, current load-balancing schemes use the fixed parameter setting, resulting in suboptimal performances. Therefore, we propose a multi-level dynamic traffic load-balancing (MDTLB) protocol, which uses an adaptive approach of parameter setting. The simulation results show that the MDTLB outperforms the state-of-the-art schemes in terms of both the flow completion time and throughput in typical data center applications.

Modern data center networks typically adopt symmetric topologies, such as leaf-spine and fat-tree. When a large number of transmission control protocol (TCP) flows in data center networks send data to the same receiver, the congestion collapse, called TCP Incast, frequently happens because of the huge packet losses and Time-Out. To address the TCP Incast issue, we firstly demonstrate that adjusting the increasing speed of the congestion window during the slow start phase is crucially important. Then we propose the Gentle Slow Start (GSS) algorithm, which adjusts the congestion window according to real-time congestion state in a gentle manner and smoothly switches from slow start to congestion avoidance phase. Furthermore, we present the implementation and design of Gentle Slow Start and also integrate it into the state-of-the-art data center transport protocols. The test results show that GSS effectively decreases the Incast probability and increases the network goodput by average 8x.