Influence of air supply velocity on temperature field in the self heating process of coal

The air supply velocity is an important factor affecting the spontaneous combustion of coal. The appropriate air velocity can not only provide the oxygen required for the oxidation reaction, but maintains the good heat storage environment. Therefore, it is necessary to study the influence of the actual air velocity in the pore space on the self-heating process of coal particles. This paper focuses on studying the real space piled up by spherical particles. CFD simulation software is used to establish the numerical model from pore scale. Good fitness of the simulation results with the existing results verifies the feasibility of the calculation method. Later, the calculation conditions are changed to calculate and analyze the velocity field and the temperature field for self-heating of some particles (the surface of the particles is at a certain temperature) and expound the effect of different air supply velocities on gathering and dissipating the heat

Emerging Theranostic Nanomaterials in Diabetes and Its Complications

Diabetes mellitus (DM) refers to a group of metabolic disorders that are characterized by hyperglycemia. Oral subcutaneously administered antidiabetic drugs such as insulin, glipalamide, and metformin can temporarily balance blood sugar levels, however, long-term administration of these therapies is associated with undesirable side effects on the kidney and liver. In addition, due to overproduction of reactive oxygen species and hyperglycemia-induced macrovascular system damage, diabetics have an increased risk of complications. Fortunately, recent advances in nanomaterials have provided new opportunities for diabetes therapy and diagnosis. This review provides a panoramic overview of the current nanomaterials for the detection of diabetic biomarkers and diabetes treatment. Apart from diabetic sensing mechanisms and antidiabetic activities, the applications of these bioengineered nanoparticles for preventing several diabetic complications are elucidated. This review provides an overall perspective in this field, including current challenges and future trends, which may be helpful in informing the development of novel nanomaterials with new functions and properties for diabetes diagnosis and therapy.Peer reviewe

Three-phase optimal power flow for networked microgrids based on semidefinite programming convex relaxation

Many autonomous microgrids have extensive penetration of distributed generation (DG). Optimal power flow (OPF) is necessary for the optimal dispatch of networked microgrids (NMGs). Existing convex relaxation methods for three-phase OPF are limited to radial networks. In light of this, we develop a semidefinite programming (SDP) convex relaxation model which can cope with meshed networks and also includes a model of three-phase DG and under-load voltage regulators with different connection types. The SDP model solves the OPF problem of multi-phase meshed network effectively, with satisfactory accuracy, as validated by real 6-bus, 9-bus, and 30-bus NMGs, and the IEEE 123-bus test cases. In the SDP model, the convex symmetric component of the three-phase DG model is demonstrated to be more accurate than a three-phase DG modelled as three single-phase DG units in three-phase unbalanced OPF. The proposed method also has higher accuracy than the existing convex relaxation methods. The resultant optimal control variables obtained from the convex relaxation optimization can be used for both final optimal dispatch strategy and initial value of the non-convex OPF to obtain the globally optimal solution efficiently

Responses of soil microbial communities to a short-term application of seaweed fertilizer revealed by deep amplicon sequencing

Numerous studies have reported soil damage from chemical fertilizer application and an obvious promotional effect of seaweed fertilizer fermented with Sargassum horneri on the growth of tomato roots and seedlings due to its alginate oligosaccharide. However, few studies have assessed the effects of the fermented seaweed fertilizer on ecological environment and microorganisms in soil. Herein, our objective is to uncover microbial and soil environmental responses to Sargassum horneri-fermented seaweed fertilizer. After treated tomato-planting plots with Sargassum horneri fermented seaweed fertilizer, soil bacterial community compositions based on 16S rRNA gene amplicon sequencing, enzyme activities in soil and crop yield were analyzed. The bacterial a-diversity was strongly influenced by seaweed fertilizer amendment after 60 days. Non-metric multidimensional scaling (NMDS) analysis showed that a difference in bacterial community compositions between day 0 and day 60 was obvious for soil treated with seaweed fertilizer. The community variation could be caused by invertase activity and dehydrogenase activity in canonical correlation analysis (CCA). Protease activity, polyphenol oxidase activity and urease activity showed an obvious correlation with community variation in the Mantel test. The fertilization increased tomato yield by 1.48-1.83 times, Vc content by 1.24-4.55 times and lycopene content by 1.20-2.33 times. In the present study, a possible reason for bacterial community variation was discovered, which will provide an economical dilution rate of seaweed fertilizer for optimal crop yield and quality. Meanwhile, our study will be beneficial for developing a possible substitute for chemical fertilizer and an improved understanding of soil microbial functions and soil sustainability

Spatiotemporal genomic analysis reveals distinct molecular features in recurrent stage I non-small cell lung cancers

Stage I non-small cell lung cancer (NSCLC) presents diverse outcomes. To identify molecular features leading to tumor recurrence in early-stage NSCLC, we perform multiregional whole-exome sequencing (WES), RNA sequencing, and plasma-targeted circulating tumor DNA (ctDNA) detection analysis between recurrent and recurrent-free stage I NSCLC patients (CHN-P cohort) who had undergone R0 resection with a median 5-year follow-up time. Integrated analysis indicates that the multidimensional clinical and genomic model can stratify the prognosis of stage I NSCLC in both CHN-P and EUR-T cohorts and correlates with positive pre-surgical deep next generation sequencing (NGS) ctDNA detection. Increased genomic instability related to DNA interstrand crosslinks and double-strand break repair processes is significantly associated with early tumor relapse. This study reveals important molecular insights into stage I NSCLC and may inform clinical postoperative treatment and follow-up strategies

Automated vulnerability discovery and exploitation in the internet of things

Recently, automated software vulnerability detection and exploitation in Internet of Things (IoT) has attracted more and more attention, due to IoT’s fast adoption and high social impact. However, the task is challenging and the solutions are non-trivial: the existing methods have limited effectiveness at discovering vulnerabilities capable of compromising IoT systems. To address this, we propose an Automated Vulnerability Discovery and Exploitation framework with a Scheduling strategy, AutoDES that aims to improve the efficiency and effectiveness of vulnerability discovery and exploitation. In the vulnerability discovery stage, we use our Anti-Driller technique to mitigate the “path explosion” problem. This approach first generates a specific input proceeding from symbolic execution based on a Control Flow Graph (CFG). It then leverages a mutation-based fuzzer to find vulnerabilities while avoiding invalid mutations. In the vulnerability exploitation stage, we analyze the characteristics of vulnerabilities and then propose to generate exploits, via the use of several proposed attack techniques that can produce a shell based on the detected vulnerabilities. We also propose a genetic algorithm (GA)-based scheduling strategy (AutoS) that helps with assigning the computing resources dynamically and efficiently. The extensive experimental results on the RHG 2018 challenge dataset and the BCTF-RHG 2019 challenge dataset clearly demonstrate the effectiveness and efficiency of the proposed framework

Vaccination against Heterologous R5 Clade C SHIV: Prevention of Infection and Correlates of Protection

A safe, efficacious vaccine is required to stop the AIDS pandemic. Disappointing results from the STEP trial implied a need to include humoral anti-HIV-1 responses, a notion supported by RV144 trial data even though correlates of protection are unknown. We vaccinated rhesus macaques with recombinant simian immunodeficiency virus (SIV) Gag-Pol particles, HIV-1 Tat and trimeric clade C (HIV-C) gp160, which induced cross-neutralizing antibodies (nAbs) and robust cellular immune responses. After five low-dose mucosal challenges with a simian-human immunodeficiency virus (SHIV) that encoded a heterologous R5 HIV-C envelope (22.1% divergence from the gp160 immunogen), 94% of controls became viremic, whereas one third of vaccinees remained virus-free. Upon high-dose SHIV rechallenge, all controls became infected, whereas some vaccinees remained aviremic. Peak viremia was inversely correlated with both cellular immunity (p<0.001) and cross-nAb titers (p<0.001). These data simultaneously linked cellular as well as humoral immune responses with the degree of protection for the first time