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Macrophages play critical roles in both innate and adaptive immunity and are known for their high plasticity in response to various external signals. Macrophages are involved in regulating systematic iron homeostasis and they sequester iron by phagocytotic activity, which triggers M1 macrophage polarization and typically exerts antitumor effects. We previously developed a novel cryo-thermal therapy that can induce the mass release of tumor antigens and damage-associated molecular patterns (DAMPs), promoting M1 macrophage polarization. However, that study did not examine whether iron released after cryo-thermal therapy induced M1 macrophage polarization, this question still needed to be addressed. We hypothesized that cryo-thermal therapy would cause the release of a large quantity of iron to augment M1 macrophage polarization due to the disruption of tumor cells and blood vessels, which would further enhance antitumor immunity. In this study, we investigated iron released in primary tumors, the level of iron in splenic macrophages after cryo-thermal therapy and the effect of iron on macrophage polarization and CD4+ T cell differentiation in metastatic 4T1 murine mammary carcinoma. We found that a large amount of iron was released after cryo-thermal therapy and could be taken up by splenic macrophages, which further promoted M1 macrophage polarization by inhibiting ERK phosphorylation. Moreover, iron promoted DC maturation, which was possibly mediated by iron-induced M1 macrophages. In addition, iron-induced M1 macrophages and mature DCs promoted the differentiation of CD4+ T cells into the CD4 cytolytic T lymphocytes (CTL) subset and inhibited differentiation into Th2 and Th17 cells. This study explains the role of iron in cryo-thermal therapy-induced antitumor immunity from a new perspective.

Multi-string pattern matching is a crucial building block for many network security applications, and thus of great importance. Since every byte of a packet has to be inspected by a large set of patterns, it often becomes a bottleneck of these applications and dominates the performance of an entire system. Many existing works have been devoted to alleviate this performance bottleneck either by algorithm optimization or hardware acceleration. However, neither one provides the desired scalability and costs that keep pace with the dramatic increase of the network bandwidth and network traffic today. In this paper, we present BOLT, a scalable and cost-efficient multi-string pattern matching system leveraging the capability of emerging programmable switches. BOLT combines the following two techniques, a smart state encoding scheme to fit a large number of strings into the limited memory on the programmable switch, and a variable k-stride transition mechanism to increase the throughput significantly with the same level of memory costs. We implement a prototype of BOLT and make its source code publicly available. Extensive evaluations demonstrate that BOLT could provide orders of magnitude improvement in throughput which is scalable with pattern sets and workloads, and could also significantly decrease the number of entries and memory requirement.

The fouling behavior of a steam generator (SG) tube was investigated at different positions after 500 h of immersion in high-temperature water. A triple-layer structure of fouling appeared at both the crevice position and the free span position, namely, the large, dispersedly distributed deposition layer on the top, the small and faceted outer layer, and the relatively continuous inner layer. There was no obvious positional effect on the thickness of the inner layer. However, in the crevice position, the density of the deposited particle and the thickness of the outer layer was much higher than those of the free span position. The tube support plate (TSP) made of 410 stainless steel contributed significantly to the fouling behavior of the SG tube in the crevice between the SG tube and the TSP.

The aim of the present study was to compare the clinical and economic benefits of intra-articular injections of platelet-rich plasma (PRP) and hyaluronic acid (HA) in Chinese patients with knee osteoarthritis (OA). A total of 86 patients (42 treated with PRP and 44 with HA) were treated with three weekly intra-articular injections. The inclusion criteria included patients between 18 and 75 years of age, with chronic knee pain or swelling lasting >3 months and X-ray findings of degenerative joint alterations according to the Kellgren-Lawrence score grade I-III. Clinical examinations were performed before treatment, at 1- and 6-month post-injection intervals. International Knee Documentation Committee subjective, Western Ontario and McMaster Universities and visual analogue scale scores were determined at each examination. Adverse reactions, average cost, treatment time and patient satisfaction were also recorded. Compared with patients injected with HA, PRP was found to be associated with increased and more severe post-injection pain and swelling, where the duration of adverse reactions was greater in the PRP group (P=0.02). During the follow-up evaluations, both groups showed statistically significant improvements in all clinical scores from pre-injection to 1- and 6-month assessments (P

Limited data exist on patients with limb liposarcoma (LLS) with metastasis at presentation Moreover, the potential prognostic factors of this patient population are poorly documented because of its rarity. Therefore, we conducted this study to evaluate the clinicopathologic characteristics and prognostic factors for patients with metastatic LLS. All patients with LLS with metastasis at presentation from 1975 to 2016 were identified by using the Surveillance, Epidemiology, and End Results (SEER) database. The following clinical data were derived from this clinical database: age, sex, histologic grade, subtype, size of tumor, surgery, radiotherapy, chemotherapy, vital status, cause of death, and survival duration. The Kaplan-Meier method was performed to calculate median survival time and draw survivorship curves. Cox-proportional hazards regression model was used to reveal the statistical independence between various variables. The present study collected 184 cases from SEER database for survival analysis. Mean age was 57.8 years with 63.6% (n = 117) men. The 3-year overall survival (OS) and cancer-specific survival (CSS) rates of this population were 27.8% and 30.1%, respectively. Univariate analysis revealed that age, tumor grade, and surgery were significantly correlated with survival. Sex and tumor size did not reach significant predictor status of survival. Multivariate analysis revealed that age at diagnosis

Accurate forecasting of power load is of great significance to economic dispatch and safe operation of power grid. A short-term load forecasting model based on EEMD- LN-GRU is proposed according to the characteristics of uncertainty and nonlinearity of power load. In order to solve the problem of power load fluctuation and mode aliasing caused by empirical mode decomposition (EMD), the original load time series signal is decomposed into multiple intrinsic mode functions (IMF) and residual error component by ensemble empirical mode decomposition (EEMD). Each component signal is predicted by the gating recurrent unit (GRU) after layer normalization (LN). Finally, the components are predicted. The results are recombined, and then the peak valley value of the prediction sequence obtained by peak valley value correction strategy is modified to obtain the final load series. Taking the real load data of power plant of Slovak power company as an example, this method is compared with LSTM, GRU and other methods, and the results show that the proposed method has higher prediction accuracy for load forecasting.

Minimal residual disease that persists after chemotherapy is the most valuable prognostic marker for haematological malignancies and solid cancers. Unfortunately, our understanding of the resistance elicited in minimal residual disease is limited due to the rarity and heterogeneity of the residual cells. Here we generated 161,986 single-cell transcriptomes to analyse the dynamic changes of B-cell acute lymphoblastic leukaemia (B-ALL) at diagnosis, residual and relapse by combining single-cell RNA sequencing and B-cell-receptor sequencing. In contrast to those at diagnosis, the leukaemic cells at relapse tended to shift to poorly differentiated states, whereas the changes in the residual cells were more complicated. Differential analyses highlighted the activation of the hypoxia pathway in residual cells, resistant clones and B-ALL with MLL rearrangement. Both in vitro and in vivo models demonstrated that inhibition of the hypoxia pathway sensitized leukaemic cells to chemotherapy. This single-cell analysis of minimal residual disease opens up an avenue for the identification of potent treatment opportunities for B-ALL.

Higher heating value (HHV) is one of the properties of biomass fuels which is essential in investigating their special characteristics and potentialities. In this paper, various techniques based on Gaussian process regression (GPR) were utilized to assess this value for biomass fuels, including several kernel functions, i.e., exponential, Matern, rational quadratic, and squared exponential. An extensive databank was collected from literature. The findings were compared, and the results indicated that Exponential-based model was more accurate, with the coefficient of regression ( R 2 ) of 0.961 and the mean relative error (% MRE) of 3.11 for total data. Compared to former models presented by previous researchers, the model proposed in this study showed a higher ability to predict output values. With various analyses, it can be concluded that the proposed method has a high rate of efficiency in assessing the HHV of various biomass.

As a variant of digital signature schemes, the blind signature enables that the signer signs a message without knowing its content. In identity-based cryptography, many blind signature schemes have been proposed. Among them, Verma et al. designed an identity-based blind signature scheme with message recovery (IDBS-MR). Unfortunately, after our cryptanalysis, their scheme cannot satisfy untraceability, which enables the signer to break the anonymity of users by tracking the previous signature transmission scripts. To solve the problem, we construct a new IDBS-MR scheme using the bilinear pairing and demonstrates that the proposed scheme has blindness, untraceability, and unforgeability in the random oracle model. Performance results show that compared with Verma et al.’s scheme, the proposed scheme has the same computation costs in views of signers, twice computation costs in views of users, but reduces 36% computation costs in views of verifiers.

Nowadays, the Internet of Things (IoT) has been rised. As an important branch, the Healthcare Wireless Medical Sensor Networks (HWMSNs) also have a huge developing prospect. The security, privacy and effiency in HWMSNs also have become the hot topics because of HWMSNs’ vulnerability in an open wireless channel. In such a scenario, various aggregate signature schemes for HWMSNs have been proposed. Nevertheless, the certificate-based aggregate signature schemes face with a common issue (i.e. complicated certificate management). While Identity-based (ID-based) aggregate signature schemes can mitigate this issue, they cannot resist varied attacks (e.g. the modification attack, the impersonation attack etc.). On the other hand, they usually use complicated computations (e.g. bilinear pairing), being intractable for lightweight devices of HWMSNs. After analyzing proposed aggregate signature schemes, we improve Gayathri et al.’s scheme [1] which is the most efficient in current schemes and propose a certificateless aggregate signature scheme with enhanced security and efficiency (CLAS) scheme. At the same time, the security analysis and performance analysis provided by this paper indicate our scheme can provide privacy preserving, resist current known attacks and has the utility for HWMSNs.

Frameshift mutation caused by small insertions/deletions (indels) often generate truncated and non-functional proteins, which underlies 22% inherited Mendelian disorders in humans. However, there is no efficient in vivo gene therapy strategies available to date, especially in postmitotic systems. Here, we leveraged the non-homologous end joining (NHEJ) mediated non-random editing profiles to compensate the frameshift mutation in a USH1F mouse model – av3j. After treatment by the selected gRNA, about 50% editing products showed reading-frame restoration, and more than 70% targeted hair cells recovered mechanotransduction. In vivo treatment ameliorated the hearing and balance symptoms in homozygous mutant mice. Furthermore, a scale-up analysis of 114 gRNAs targeting 40 frameshift deafness mutations reveals that 65% loci have at least one gRNA with predicted therapeutic potential. Together, our study demonstrates that the NHEJ-mediated frame restoration is a simple and highly efficient therapeutic strategy for small-indel induced frameshift mutations.

The success of artificial vascular graft in the host to obtain functional tissue regeneration and remodeling is a great challenge in the field of small diameter tissue engineering blood vessels. In our previous work, poly(ε-caprolactone) (PCL)/fibrin vascular grafts were fabricated by electrospinning. It was proved that the PCL/fibrin vascular graft was a suitable small diameter tissue engineering vascular scaffold with good biomechanical properties and cell compatibility. Here we mainly examined the performance of PCL/fibrin vascular graft in vivo. The graft showed randomly arranged nanofiber structure, excellent mechanical strength, higher compliance and degradation properties. At 9 months after implantation in the rat abdominal aorta, the graft induced the regeneration of neoarteries, and promoted ECM deposition and rapid endothelialization. More importantly, the PCL/fibrin vascular graft showed more microvessels density and fewer calcification areas at 3 months, which was beneficial to improve cell infiltration and proliferation. Moreover, the ratio of M2/M1macrophage in PCL/fibrin graft had a higher expression level and the secretion amount of pro-inflammatory cytokines started to increase, and then decreased to similar to the native artery. Thus, the electrospun PCL/fibrin tubular vascular graft had great potential to become a new type of artificial blood vessel scaffold that can be implanted in vivo for long term., Highlights • In this manuscript, we successfully prepared the PCL/fibrin vascular scaffold through electrospinning technology. • We further explore its role as a substitute for artificial blood vessels in vivo. • Mechanical properties, cell formation, extracellular matrix, immune response and calcification of grafts were assessed. • PCL/fibrin tubular vascular graft had great potential to become a new type of artificial blood vessel scaffold. • This research will bring significance to treatment of cardiovascular diseases, and promote development of vascular grafts.

Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenvironments at single-cell transcriptomic level. Here, we develop an R package named scCancer, which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness), gene signatures and cell–cell interactions. Besides, it provided multi-sample data integration analysis with different batch-effect correction strategies. Finally, user-friendly graphic reports were generated for all the analyses. By testing on 56 samples with 433 405 cells in total, we demonstrated its good performance. The package is available at: http://lifeome.net/software/sccancer/.

It has always been a research hotspot to use geographic information to assist the navigation of unmanned aerial vehicles. In this paper, a road-network-based localization method is proposed. We match roads in the measurement images to the reference road vector map, and realize successful localization on areas as large as a whole city. The road network matching problem is treated as a point cloud registration problem under two-dimensional projective transformation, and solved under a hypothesise-and-test framework. To deal with the projective point cloud registration problem, a global projective invariant feature is proposed, which consists of two road intersections augmented with the information of their tangents. We call it two road intersections tuple. We deduce the closed-form solution for determining the alignment transformation from a pair of matching two road intersections tuples. In addition, we propose the necessary conditions for the tuples to match. This can reduce the candidate matching tuples, thus accelerating the search to a great extent. We test all the candidate matching tuples under a hypothesise-and-test framework to search for the best match. The experiments show that our method can localize the target area over an area of 400 within 1 second on a single cpu., 19pages, 10 figures, 3 tables. in IEEE Transactions on Geoscience and Remote Sensing

This paper deals with the input–output finite-time stability of discrete time-varying linear systems in the presence of finite-time boundedness. The state boundedness and output stability of this s...

Purpose This study aims to find a novel solution to the calibration of three-axis magnetometers to suppress errors of sensors. The nature of the calibration process is parameter estimation and hence the purpose of the paper is to calculate the error parameters and eliminate sensor errors and obtain the true value of the pure magnetic field. Design/methodology/approach The paper puts forward a calibration method using an alternative iteration looping optimization (AILO) to estimate the parameters. The proposed method divided the parameters to be estimated into two parts: a portion less than one and the other greater than one. Parameters with different orders of magnitude are calculated respectively, which let one part to be a known quantity and the other part is derived by the known quantity; the derived quantity is used to calculate the known quantity again, and looping iteration multiple times until the iteration termination condition is satisfied. Findings The simulation and experimental results indicate that the calibration accuracy is improved at least by two orders by the proposed method compared to the two-step method and the linear decreasing weight particle swarm optimization (LDW-PSO) algorithm which proves the validity of the proposed method. Practical implications The proposed method can improve the calibration accuracy of total magnetic field, which provides a reference to the calibration of three-axis magnetometers. Originality/value A calibration method based on the AILO is proposed in this paper, which is used to improve the calibration accuracy of the three-axis magnetometer.

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb. Keywords: Hepatocellular carcinoma, Database, Transcriptome, Integrative analysis, Meta-analysis

The array antenna SAR or integrated multi-task imaging sensors are the most attractive development directions of aerial survey and remote sensing system, and urgently demand an airborne distributed position and orientation system (ADPOS), which depends on transfer alignment to accurately measure multi-node motion information. In this paper, an adaptive unscented two-filter smoother (AUTFS) is proposed for the offline transfer alignment of ADPOS, which deals with the problem of time-varying measurement noise covariance. The proposed smoother adopts a forward–backward approach, which includes an adaptive unscented Kalman filter tuned by fading factors in the forward direction and a backward filter using the weighted statistical linear regression formulation. A semi-physical simulation based on a flight experiment with ADPOS shows that the proposed AUTFS can achieve higher accuracy than the standard unscented two-filter smoother.

In this paper, we study the containment control problem for nonlinear second-order systems with unknown parameters and multiple stationary U+002F dynamic leaders. The topologies that characterize the interaction among the leaders and the followers are directed graphs. Necessary and sufficient criteria which guarantee the control objectives are established for both stationary leaders U+0028 regulation case U+0029 and dynamic leaders U+0028 dynamic tracking case U+0029 based protocols. The final states of all the followers are exclusively determined by the initial values of the leaders and the topology structures. In the regulation case, all the followers converge into the convex hull spanned by the leaders, while in the dynamic tracking case, not only the positions of the followers converge into the convex hull but also the velocities of the followers converge into the velocity convex hull of the leaders. Finally, all the theoretical results are illustrated by numerical simulations.

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, of which B cell ALL (B-ALL) accounts for up to 85% of all cases. Although risk-stratified chemotherapy significantly improves the clinical outcome of affected pediatric patients with B-ALL, relapse still occurs in approximately 10% of children, representing the main cause of pediatric cancer deaths. Minimal residual disease (MRD) that persists after chemotherapy was the most valuable prognostic marker for hematological malignancies and solid cancers. Unfortunately, our understanding of the resistance mechanisms elicited in MRD is limited due to the rarity and heterogeneity of these residual cells. In our study, we employed paired scRNA-seq and single-cell BCR sequencing (scBCR-seq) to study the distinct features of leukemic cells from longitudinal samples obtained at the diagnosis, residual and relapsed stages at the single-cell level. By performing unsupervised clustering of the scRNA-seq data from 16,543 bone marrow CD19 -CD34 +cells and 20,392 CD19 +cells of healthy donors, we successfully defined the cell clusters of different B cell development stages sequentially, from hematopoietic stem cell / lymphoid-primed multipotential progenitors (HSC/LMPP) to common lymphoid progenitor (CLP), proB, preBI, preBII, immature/mature B cells and finally, activated B cells. By referring to the landmarks of normal cells, we then employed scRNA-seq and scBCR-seq to further dissect the phenotypic complexities within and across 4 pediatric B-ALL diagnostic-relapsed pairs at the single cell level. Our study found that BCR states can be used to distinguish leukemic cells and normal cells. From the four relapsed pediatric B-ALL patients, we obtained a total of 104,055 CD19 +cells with paired scRNA-seq and scBCR-seq data encompassing the three stages of B cell differentiation that passed the quality control. By examining the scBCR-seq data at the diagnosis stage to distinguish leukemic and normal (or non-leukemic) B cells based on genome-wide expression patterns rather than a few marker genes, we employed a machine learning approach. To train the classifier, CD19 +cells with non-clonal BCRs in D19 samples were selected as "non-leukemic", and CD19 +cells with clonal BCRs (B265) and without detected BCRs (B590, B069 and B887) in D19 samples were selected as "leukemic". Using this strategy, we compared the gene expression profiles of the leukemic cells at the diagnosis and relapse for each patient, with the aim to identify specific features of relapse stage leukemia cells at the single-cell level. We found that the cell composition profile tended to shift to early differentiation stages in the relapsed samples in all four patients. By analyzing the differentiation stage, cell cycle and gene expression characteristics of relapsed cell samples at the single-cell level, we obtained some unique findings, such as significantly increased expression of CDKN1A in relapsed cells. To understand the basis of such specific differentiation stage and cell cycle transition during chemotherapy, we performed differential expression analysis to identify genes specifically altered at D19 compared to diagnosis and relapse. Then, pathway enrichment analysis applied to the differentially expressed genes revealed that the hypoxia pathway was one of the top hits, being significantly upregulated during intensified chemotherapy. We obtained experimental support by validating the efficacy of the HIF-1a inhibitor PX478 combined with chemotherapy drugs in two B-ALL cell lines and two primary B-ALL cells. In summary, our study leveraged single-cell transcriptomic analysis with paired BCR repertoire profiling to decode the molecular aberrations across the phenotypically heterogeneous disease, B-ALL. We also applied a powerful B cell development classifier and an innovative machine learning model for B-ALL cell identification at single-cell resolution to determine the clonal signatures, and to track residual cell evolution in a longitudinal manner from diagnosis, to post-treatment, and finally relapse. We propose that hypoxia signaling pathway activation might serve as valuable MRD therapeutic target. While this study provided great insights into the transcriptomic characteristics of MRD cells, practically, our analytical approach could readily be applied to other hematological malignancies and solid cancers. Disclosures No relevant conflicts of interest to declare.

Effective cancer therapies should reshape immunosuppression and trigger antitumor immunity. Previously, we developed a novel cryo-thermal therapy through applying local rapid cooling followed by rapid heating of tumor tissue. It could not only ablate local tumors, but also, subsequently, induce systemic long-term antitumor immunity. Hyperthermia can induce the release of extracellular vesicles (EVs) to stimulate antitumor immunity. We examine whether EVs are released after cryo-thermal therapy and whether they could improve the efficacy of cryo-thermal therapy in the 4T1 model. In this study, serum extracellular vesicles (sEVs) are isolated and characterized 3 h after cryo-thermal therapy of subcutaneous tumors. sEV phagocytosis is observed in vitro and in vivo by using laser confocal microscopy and flow cytometry. After cryo-thermal therapy, sEVs are administered to mice via the tail vein, and changes in immune cells are investigated by using flow cytometry. After cryo-thermal therapy, a large number of sEVs are released to the periphery carrying danger signals and tumor antigens, and these sEVs could be phagocytosed by peripheral blood monocytes and differentiated macrophages. After cryo-thermal therapy, supplementation with sEVs released after treatment promotes the differentiation of myeloid-derived suppressor cells (MDSCs), monocytes into macrophages and CD4+ T cells into the Th1 subtype, as well as prolonging the long-term survival of the 4T1 subcutaneous tumor-bearing mice. sEVs released after cryo-thermal tumor treatment could clinically serve as an adjuvant in subsequent cryo-thermal therapy to improve the therapeutic effects on malignant tumors.

Immunotherapy has emerged as a therapeutic pillar in tumor treatment, but only a minority of patients get benefit. Overcoming the limitations of immunosuppressive environment is effective for immunotherapy. Moreover, host T cell activation and longevity within tumor are required for the long-term efficacy. In our previous study, a novel cryo-thermal therapy was developed to improve long-term survival in B16F10 melanoma and s.q. 4T1 breast cancer mouse models. We determined that cryo-thermal therapy induced Th1-dominant CD4+ T cell differentiation and the downregulation of Tregs in B16F10 model, contributing to tumor-specific and long-lasting immune protection. However, whether cryo-thermal therapy can affect the differentiation and function of T cells in a s.q. 4T1 model remains unknown. In this study, we also found that cryo-thermal therapy induced Th1-dominant differentiation of CD4+ T cells and the downregulation of effector Tregs. In particular, cryo-thermal therapy drove the fragility of Tregs and impaired their function. Furthermore, we discovered the downregulated level of serum tumor necrosis factor-α at the late stage after cryo-thermal therapy which played an important role in driving Treg fragility. Our findings revealed that cryo-thermal therapy could reprogram the suppressive environment and induce strong and durable antitumor immunity, which facilitate the development of combination strategies in immunotherapy.

Today, the use of alternative energy sources such as solar energy to overcome the obstacles caused by the consumption of fossil fuels is inevitable. However, solar energy faces natural issues such as intermittency, instability and uncertainty. Meanwhile, integration of clean energy sources can be a key solution. On the other hand, fuel cells are conversion devices that have advantages, e.g., high reliability, low emissions, and high efficiency. The aim of this study is to present and evaluate the operation of a new energy process based on alkaline fuel cell (AFC) and solar photovoltaic (PV) field. AFC produces electrical and thermal power. In downstream cycles, additional electricity and cooling are generated by the Stirling engine and the absorption chiller, respectively. The solar field provides the power of an electrolyzer to supply fuel and oxidant to the fuel cell. Results showed that the cycle can produce up to 3.4 kW of electricity. The share of AFC, Stirling engine and solar PV field in electricity generation is 29.3, 21.4 and 49.3 %, respectively. It was also found that the electrical and overall efficiencies of the cycle are 64.36 and 77.57 %, respectively. In addition, 77.44 kW of exergy is destroyed.

Distributed array antenna synthetic aperture radar (SAR), flexible baseline interferometric SAR (InSAR) or integrated multi-task imaging sensors are the most attractive development directions of aerial survey and remote sensing system, and urgently demand a distributed Position and Orientation System (DPOS) to accurately measure multi-nodes time-spatial reference information. However, the traditional transfer alignment (TA) method can't meet the requirements of some high precision interferometric imaging task. To solve the problem, a dual-filter TA method based on position-velocity-attitude matching (PVAM) was proposed. Firstly, the TA method based on attitude matching (AM) is conducted in filter-1 to estimate the flexible angles and the derivatives. Then the TA method based on position-velocity matching (PVM) is conducted in filter-2, and the position and velocity measurements are compensated by the flexible angles and the derivatives estimated by filter-1. Finally, the strapdown solutions of slave IMU are corrected by the corrections from both filter-1 and filter-2. A semi-physical simulation based on airborne DPOS flight experiment has been conducted, verifying that the baseline error has been reduced from 0.0240 m to 0.0083 m and the computation time has been decrease by 3.41%.

Suppose an orientation-preserving action of a finite group G on the closed surface \(\Sigma _g\) of genus \(g>1\) extends over the 3-torus \(T^3\) for some embedding \(\Sigma _g\subset T^3\). Then \(|G|\le 12(g-1)\), and this upper bound \(12(g-1)\) can be achieved for \(g=n^2+1, 3n^2+1, 2n^3+1, 4n^3+1, 8n^3+1, n\in {\mathbb {Z}}_+\). The surfaces in \(T^3\) realizing a maximal symmetry can be either unknotted or knotted. Similar problems in the non-orientable category are also discussed. The connection with minimal surfaces in \(T^3\) is addressed and the situation when the maximally symmetric surfaces above can be realized by minimal surfaces is identified.

SummaryMolecular heterogeneities bring great challenges for cancer diagnosis and treatment. Recent advance in single cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer transcriptomic heterogeneities at single cell level. Here, we develop an R package named scCancer which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness) and gene signatures. Finally, a user-friendly graphic report was generated for all the analyses.Availabilityhttp://lifeome.net/software/sccancer/.Contactjgu@tsinghua.edu.cn

In our previous study, Deferoxamine (DFO) increased the iron concentration by upregulating the expression levels of TfR1 and DMT1 and exacerbated the migration of triple-negative breast cancer cells. However, the mechanisms of iron distribution and utilization in triple-negative breast cancer cells with a DFO-induced iron deficiency are still unclear. In this study, triple-negative MDA-MB-231 and estrogen receptor (ER)-positive MCF-7 breast cancer cells were used to investigate the mechanisms of iron distribution and utilization with a DFO-induced iron deficiency. We found that the mitochondrial iron concentration was elevated in MDA-MB-231 cells, while it was decreased in MCF-7 cells after DFO treatment. The cellular and mitochondrial reactive oxygen species (ROS) levels increased in both breast cancer cell types under DFO-induced iron-deficient conditions. However, the increased ROS levels had different effects on the different breast cancer cell types: Cell viability was inhibited and apoptosis was enhanced in MCF-7 cells, but cell viability was maintained and cell migration was promoted in MDA-MB-231 cells through the ROS/NF-&kappa, B and ROS/TGF-&beta, signaling pathways. Collectively, this study suggests that under DFO-induced iron-deficient conditions, the increased mitochondrial iron levels in triple-negative MDA-MB-231 breast cancer cells would generate large amounts of ROS to activate the NF-&kappa, B and TGF-&beta, signaling pathways to promote cell migration.

Rotating packed bed (RPB) has been demonstrated as a significant and emerging technology to be applied in natural gas desulfurization. However, droplet characteristics and principle in H2S selective absorption with N-methyldiethanolamine (MDEA) solution have seldom been fully investigated by experimental method. Therefore, a 3D Eulerian&ndash, Lagrangian approach has been established to investigate the droplet characteristics. The discrete phase model (DPM) is implemented to track the behavior of droplets, meanwhile the collision model and breakup model are employed to describe the coalescence and breakup of droplets. The simulation results indicate that rotating speed and radial position have a dominant impact on droplet velocity, average residence time and average diameter rather than initial droplet velocity. A short residence time of 0.039&ndash, 0.085 s is credited in this study for faster mass transfer and reaction rate in RPB. The average droplet diameter decreases when the initial droplet velocity and rotating speed enhances. Restriction of minimum droplet diameter for it to be broken and an appropriate rotating speed have also been elaborated. Additional correlations on droplet velocity and diameter have been obtained mainly considering the rotating speed and radial position in RPB. This proposed formula leads to a much better understanding of droplet characteristics in RPB.

Given a connected real Lie group and a contractible homogeneous proper $G$--space $X$ furnished with a $G$--invariant volume form, a real valued volume can be assigned to any representation $\rho\colon \pi_1(M)\to G$ for any oriented closed smooth manifold $M$ of the same dimension as $X$. Suppose that $G$ contains a closed and cocompact semisimple subgroup, it is shown in this paper that the set of volumes is finite for any given $M$. From a perspective of model geometries, examples are investigated and applications with mapping degrees are discussed., Comment: 34 pages

Supplementary_information for Preparation of graphene/polyaniline nanocomposite by in situ intercalation polymerization and their application in anti-corrosion coatings by Yiyi Li, Yiting Xu, Shicheng Wang, Hongchao Wang, Meng Li and Lizong Dai in High Performance Polymers

In this paper, a two-dimensional steady model is established to investigate the gas-solid heat transfer in a sinter vertical tank based on the porous media theory and the local thermal non-equilibrium model. The influences of the air flow rate, sinter flow rate, and sinter particle diameter on the gas-solid heat transfer process are investigated numerically. In addition, exergy destruction minimization is used as a new principle for heat transfer enhancement. Furthermore, a multi-objective genetic algorithm based on a Back Propagation (BP) neural network is applied to obtain a combination of each parameter for a more comprehensive performance, with the exergy destruction caused by heat transfer and the one caused by fluid flow as the two objectives. The results show that the heat dissipation and power consumption both gradually increase with an increase of the air mass flow rate. Additionally, the increase of the sinter flow rate results in a decrease of the heat dissipation and an increase of the power consumption. In addition, both heat dissipation and power consumption gradually decrease with an increase of the sinter particle diameter. For the given structure of the vertical tank, the optimal operating parameters are 2.99 kg/s, 0.61 kg/s, and 32.8 mm for the air flow rate, sinter flow rate, and sinter diameter, respectively.

We present a 3-manifold automorphism f : M → M with rank Fix ( f ⁎ ) = 2 rank π 1 ( M ) . Related facts are discussed.

We address the problem of aerial image geolocalization over an area as large as a whole city through road network matching, which is modeled as a 2D point set registration problem under the 2D projective transformation and solved in a two-stage manner. In the first stage, all the potential transformations aligning the query road point set to the reference road point set are found by local point feature matching. A local geometric feature, called the Projective-Invariant Contour Feature (PICF), which consists of a road intersection and the closest points to it in each direction, is specifically designed. We prove that the proposed PICF is equivariant under the 2D projective transformation group. We then encode the PICF with a projective-invariant descriptor to enable the fast search of potential correspondences. The bad correspondences are then removed by a geometric consistency check with the graph-cut algorithm effectively. In the second stage, a flexible strategy is developed to recover the homography transformation with all the PICF correspondences with the Random Sample Consensus (RANSAC) method or to recover the transformation with only one correspondence and then refine it with the local-to-global Iterative Closest Point (ICP) algorithm when only a few correspondences exist. The strategy makes our method efficient to deal with both scenes where roads are sparse and scenes where roads are dense. The refined transformations are then verified with alignment accuracy to determine whether they are accepted as correct. Experimental results show that our method runs faster and greatly improves the recall compared with the state-of-the-art methods.

Nuclear power has gradually become one of the key parts in power supply structure due to its environmental benefits, effective productivity and steady operation. However, complicated system, high investment and derivative security issues make it difficult to develop in a large scale. Nowadays, faced with serious challenges from environment protection, fossil fuel lacking and upgrading of industrial structure, China are taking measures to promote nuclear power industry to realize sustainable development. China׳s nuclear power industry has achieved large achievements in industrial policy, technical and economic condition during the last three decades. However, there still exist problems impeding its future development. Therefore, this paper first analyzes the external environment and historical stages of nuclear power industry in China. Then, it summarizes its current situation and points out the existing problems. In the end, to deal with the above problems, this paper proposes relative solutions from the aspects of industrial distribution optimization, regional resources integration, technical standard system, industrial organization mode and so on.

Automatic target recognition in infrared imagery is a challenging problem. In this paper, a kernel sparse coding method for infrared target recognition using covariance descriptor is proposed. First, covariance descriptor combining gray intensity and gradient information of the infrared target is extracted as a feature representation. Then, due to the reason that covariance descriptor lies in non-Euclidean manifold, kernel sparse coding theory is used to solve this problem. We verify the efficacy of the proposed algorithm in terms of the confusion matrices on the real images consisting of seven categories of infrared vehicle targets.

Remote sensing image classification is a very challenging problem and covariance descriptor can be introduced in the feature extraction and representation process for remote sensing image. However, due to the reason that covariance descriptor lies in non-Euclidean manifold, conventional extreme learning machine (ELM) cannot effectively deal with this problem. In this paper, we propose an improved ELM framework which incorporates the collaborative coding to tackle the covariance descriptor classification problem. First, a new ELM-guided dictionary learning and coding model is proposed. Then the iterative optimization algorithm is developed to solve the model. By evaluating the proposed approach on the UCMERCED high-resolution aerial image dataset, we show the effectiveness of the proposed strategy.

As one of the most economically developed and seismically active regions of China, Fujian faces a threat from severe earthquakes, particularly those that occur in Taiwan. Following the worldwide construction of an earthquake early warning (EEW) system, we developed an EEW system in Fujian in 2009 and began online testing in November 2012. During this testing, our EEW system successfully processed several earthquakes in both the Fujian region and Taiwan. The results showed that, for inland events (Fujian region), the first alarm was generated 6.4±0.97 s after the first station was triggered, with a location error of 4.6±4.0 km and magnitude estimation error of 0.6±0.5. For offshore events (Taiwan), the first alarm was generated 13.7±2.9 s after the first station was triggered, with a location error of 30.6±31.4 km and magnitude estimation error of −0.2±0.4. Online testing allows us to continuously improve and perfect our system. In 2017, our system will officially begin providing EEW information to the public in the Fujian region. In addition to the preceding, the architecture, key algorithms, software design, and online testing results are included in this article to provide readers with a comprehensive understanding of our EEW system.

Porphyra sensu lato belongs to Bangiales, the most genetically diverse order of red algae. Porphyra or Pyropia is widely cultivated in East Asian countries, such as China, Japan, and Korea. Dried Porphyra contains numerous nutritional and biofunctional compounds, including proteins, minerals, dietary fiber, polyunsaturated fatty acids, carotenoids, saccharides, and mycosporine-like amino acids. In addition, the compound is most abundant in Porphyra, such as polysaccharides and phycobiliproteins, and demonstrates various immunomodulating, anticancer, antihyperlipidemic, and antioxidative activities. This review summarizes our current knowledge concerning the pharmacologically active substances found in Porphyra species. The biological activities and potential applications of certain carbohydrates, proteins, peptides, and other small molecules purified from Porphyra are also described, and possible areas for future studies are discussed.

In this paper, numerical simulation has been carried out to study effect of heater power allocation on the thermal stress evolution during Kyropoulos sapphire cooling process. Characteristics of the temperature and stress distributions during the whole cooling process are firstly analyzed. A design of divided side heater is then proposed for a flexible power adjustment. The transient profiles of thermal stresses are obtained from analysis of the typical power allocation ratios of the top part to the lower part of the side heater. The results show that during the cooling process large stresses usually present in the regions near the ‘throat’ and ‘bottleneck’ of the crystal. The highest stress turns up at the bottleneck during the naturally cooling process occurred after the power is off. The results further indicate that the von Mises stress significantly decreases as the power radio increases. Additionally, the maximum stresses for a higher power ratio under the range of the current study are always smaller than that of a lower one before reaching the peak values, which is beneficial to avoid thermal stress-related defects. Based on the analysis, optimized power allocation of the side heater is recommended.