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Background The left-sided and right-sided colon cancer (LCCs and RCCs, respectively) have unique molecular features and clinical heterogeneity. This study aimed to identify the characteristics of immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. Methods The independent gene datasets, corresponding somatic mutation and clinical information were collected from The Cancer Genome Atlas and Gene Expression Omnibus. The ICI contents were evaluated by “ESTIMATE” and “CIBERSORT.” We performed two computational algorithms to identify the ICI landscape related to prognosis and found the unique infiltration characteristics. Next, principal component analysis was conducted to construct ICI score based on three ICI patterns. We analyzed the correlation between ICI score and tumor mutation burden (TMB), and stratified patients into prognostic-related high- and low- ICI score groups (HSG and LSG, respectively). The role of ICI scores in the prediction of therapeutic benefits was investigated by "pRRophetic" and verified by Immunophenoscores (IPS) (TCIA database) and an independent immunotherapy cohort (IMvigor210). The key genes were preliminary screened by weighted gene co-expression network analysis based on ICI scores. And they were further identified at various levels, including single cell, protein and immunotherapy response. The predictive ability of ICI score for prognosis was also verified in IMvigor210 cohort. Results The ICI features with a better prognosis were marked by high plasma cells, dendritic cells and mast cells, low memory CD4+ T cells, M0 macrophages, M1 macrophages, as well as M2 macrophages. A high ICI score was characterized by an increased TMB and genomic instability related signaling pathways. The prognosis, sensitivities of targeted inhibitors and immunotherapy, IPS and expression of immune checkpoints were significantly different in HSG and LSG. The genes identified by ICI scores and various levels included CA2 and TSPAN1. Conclusion The identification of ICI subtypes and ICI scores will help gain insights into the heterogeneity in LCC and RCC, and identify patients probably benefiting from treatments. ICI scores and the key genes could serve as an effective biomarker to predict prognosis and the sensitivity of immunotherapy.

Summary In this paper, we study the simulation and fault diagnosis of a conventional pumping unit under balanced conditions. As the energy input of sucker-rod pumping (SRP), the motor power contains abundant information about the whole pumping cycle under SRP. It is an important step in oilfield information construction to establish a computer-aided system that is based on motor power diagnosis. Hence, we propose an SRP simulation model for generating motor power. By analyzing the working conditions of six oil wells that contain normal or insufficient liquid supply, gas lock, traveling valve leakage, standing valve leakage, and parting rod, we simulate the motor power of the six wells. In addition, we verify the simulation model using a test well with favorable performance and establish the motor power template set (MPTS) using this simulation model. To allow for computer-aided diagnosis, we propose the use of the area proportion method to extract motor power features. We establish a diagnosis model of oilwell conditions that is based on oblique decision tree and train the diagnosis model using the MPTS. Through the verification of six oil wells in the actual production of the oil field, the diagnosis model shows a favorable response. The test results show that the methods of establishing MPTS and oilwell working-condition diagnosis are feasible.

Background Studies have shown that long noncoding RNAs and N6-methyladenosine play an important role in gastric cancer. The purpose of this study was to determine the correlation and prognostic value of m6A-related lncRNAs and immune infiltration in gastric cancer. Methods We downloaded the clinically related information and RNA-Seq transcriptome data of gastric cancer patients from the TCGA database. Univariate Cox regression analysis and Pearson analysis were used to screen out m6A-related lncRNAs. Consensus cluster analysis was used to divide the sample into two clusters, and LASSO analysis and minimum absolute shrinkage were used to construct a risk scoring model. Results A total of 25 lncRNA expression profiles were screened, and gastric cancer patients were divided into different subtypes. Cluster 2 had a better prognosis, but its matrix score, estimate score and immune score were low. Cluster 1 was rich in resting memory CD4 T cells, regulatory T cells, monocytes, and resting mast cells, and Cluster 2 was rich in activated memory CD4 T cells and follicular helper T cells. Thirteen lncRNAs were selected to construct a risk model, and the prognosis of gastric cancer patients in the high-risk group was poor. The expression of PD-L1 in tumors is significantly higher than that in normal tissues. Univariate and multivariate Cox regression analysis results showed that the overall survival rate was significantly related to stage and risk score, which can be used as an independent prognostic factor. The results of the heat map and scatter plot showed that clusters (P=0.0045) and grade (G1-2, G3, P=0.0037) were significantly related to prognosis. The results of the relationship between the risk score and immune cell infiltration showed that memory B cells, resting dendritic cells, M0 macrophages, and M2 macrophages were positively correlated with risk scores, while resting mast cells, monocytes, activated NK cells, and follicular helper T cells were negatively correlated with risk scores. Conclusion The results of this study indicate that m6A-related lncRNAs may play an important role in the prognosis of gastric cancer patients and the tumor immune microenvironment and provide help for the treatment of gastric cancer patients.

Convolutional neural networks (CNNs) have achieved success in optical flow estimation using labeled datasets, but they fail to build an internal representation to fast adapt to the specific task. On the other hand, limited by the lack of ground truth, existing CNNs-based methods suffer from high noise sensitivity and inferior generalization performance. We integrate the meta-learning technique with optical flow estimation, which can learn internal features to search optimal initial state parameters of the network. Meanwhile, we devise an enhanced network termed MetaFlow to further improve performance. MetaFlow extracts per-pixel features, builds correlation volumes for all pairs of pixels, and iteratively updates optical flow through optical flow predictor using meta-learning. In addition, we propose a meta-transfer pretraining approach to obtain initial network weights, which can efficiently avoid network overfitting. Empirical experiments on MPI Sintel and KITTI benchmarks have shown that the proposed MetaFlow achieves the state-of-the-art results and performs outstanding in challenging scenarios such as textureless regions and abrupt motions.

Most Chinese poetry generation methods only accept texts or user-specified words as input, which contradicts with the fact that ancient Chinese wrote poems inspired by visions, hearings and feelings. This paper proposes a method to generate sentimental Chinese classical poetry automatically from images based on convolutional neural networks and the language model. First, our method extracts visual information from the image and maps it to initial keywords by two parallel image classification models, then filters and extends these keywords to form a keywords set which is finally input into the poetry generation model to generate poems of different genres. A bi-directional generation algorithm and two fluency checkers are proposed to ensure the diversity and quality of generated poems, respectively. Besides, we constrain the range of optional keywords and define three sentiment-related keywords dictionary to avoid modern words that lead to incoherent content as well as ensure the emotional consistency with given images. Both human and automatic evaluation results demonstrate that our method can reach a better performance on quality and diversity of generated poems.

Background: While evolution has led certain breeds of sheep to exhibit large tails composed of fatty tissue, the genetic basis for this fatty large-tailed phenotypic trait remains to be defined in breeds of Han sheep. Here, we employed a high-throughput sequencing approach to identify mRNAs and microRNAs (miRNAs) that were differentially expressed in tail fat tissue samples from large-tailed Han (LTH) and small-tailed Han (STH) sheep in order to identify key genetic determinants of the large-tailed phenotype.Results: In total, we identified 521 mRNAs (237 upregulated, 284 downregulated) and 14 miRNAs (6 upregulated, 8 downregulated) that were differentially expressed between these two sheep breeds. Predictive analytical database tools were subsequently utilized to identify 2,409 putative targets of these differentially expressed miRNAs (DEMs), including 65 which were among the list of differentially expressed genes (DEGs) identified in the present study. By specifically focusing on predicted DEM/DEG pairs with appropriate regulatory directionality, we identified DIRF, HSD17B12, LPL, APOBR, INSIGI, THRSP, ACSL5, FAAH, ACSS2, APOA1, ACLY, and ACSM3 through mRNA analyses and ACSL4, FTO, FGF8, IGF2, GNPDA2, LIPG, PRKAA2, ELOVL7, SOAT2, and SIRT1 through miRNA analyses as candidate genes which may regulate fat deposition and fatty acid metabolism in the adipose tissue from the tails of Han sheep. Conclusion: Together, our data provide insight into the potential genetic basis for the large-tailed phenotype of LTH sheep, suggesting that it may be attributable to specific DEMs and DEGs that regulate one another and thereby control lipid metabolism. These data provide a basis for future research regarding the role of these genes in ovine tail fat deposition, and offer preliminary perspectives on the molecular mechanisms governing the fatty large-tailed phenotype in LTH sheep.

Cigarette smoking increases health risks, such as respiratory diseases and heart diseases. Despite the decline in smoking rates in some countries, millions of adults still choose to smoke cigarettes. The use of next-generation nicotine delivery devices, such as tobacco heating products (THPs), may become a potentially safer alternative to smoking. Here, we report on the development of an electrically heated THP, coded as THP COO, with three different flavored tobacco sticks. The purpose of the study was to measure the levels of a list of harmful and potentially harmful constituents (HPHCs) in the total particulate matter (TPM) generated and to conduct a set of toxicological assessments of THP COO as compared with 3R4F reference cigarette. For all 55 HPHCs identified, the levels generated by the THP tobacco sticks were significantly lower in comparison to those in 3R4F TPM. The rate of reduction of HPHCs was between 68.6% and 99.9% under Health Canada Intense (HCI) smoking regimen. Human lung cancer cells (NCI-H292) exposed to 3R4F TPM showed dose-dependent responses for most of the 15 in vitro toxicity endpoints, whereas those exposed to comparable doses of THP COO TPMs did not. Therefore, exclusive use of the THP COO products may reduce the exposure of those tested HPHCs and thus potentially reduce health risk of smoking.

Ocean energy is one of the renewable energy sources. Ocean thermal energy is the most abundant in marine energy, so it has a good development prospect. At present, the main way to use ocean energy is power generation. However, it has disadvantages: low efficiency and high energy consumption. In view of the above shortcomings, this study puts forward a new type of ocean energy comprehensive utilisation system of water–electricity cogeneration. The system is based on the ocean thermal energy conversion: wave energy power generation and solar pond are integrated in the system. The basic principle and working process were analysed, and the energy consumption and the product of the system were calculated. As shown in the calculation results, it is effective to reduce energy consumption and improve the system efficiency. The research of this study has valuable reference for the development of ocean energy in the future.

In large-scale photovoltaic (PV) power plant, the output power of each grid-connected inverter is collected by electricity energy collection system and then is put into the grid. Previous studies have demonstrated that the harmonic problem may occur when PV inverters run in parallel even if all the PV inverters output power do individually satisfy the standards. Considering the electricity energy collection system, this study builds the model of harmonic transfer passive network for the typical topological structure of large-scale grid-connected PV power plant, and study the generating mechanism of harmonic and overvoltage. The harmonic power flow of a given calculation example is calculated by using node matrix method and the harmonic voltage magnification of each node is got. The point of common coupling is chosen as the study object. In this study, the impacts of cable parameters, the equivalent impedance of power grid and operation mode of PV power plant on the voltage magnification properties of the transfer network are analysed.

Serial Elastic Actuator (SEA) system attracts much attention recent years in robotics research. The control methods for SEA is studied especially considering the unknown and time-varying dynamic load. Most methods are based on the predetermined nominal dynamics of the SEA system. However, imperfect dynamics and time varying reference torque make the torque tracking problem difficult. In this paper, the Active Disturbance Rejection Control (ADRC) method is proposed to solve the above problems. The dynamics of SEA is simplified by considering the dynamics of load as the unknown disturbance. An Extended State Observer (ESO) is designed to identify the model uncertainties. The control framework could observe and reject the disturbance effectively. Finally, the effectiveness of the ADRC based torque controller is verified and compared with traditional cascade PID controller by using MATLAB/ADAMS Co-simulation, especially considering the case that SEA is implemented in a vertical plane which makes the dynamics much more complicated.

Multi-axis plunge milling has an increasing application in the manufacturing industry to rough machine complex parts, such as blisks and impellers. In order to prevent excessive cutting forces and unexpected tool breakage, cutting parameters of multi-axis plunge milling are usually assigned to be conservative according to the maximum cutting load in one feeding phase. This is an obstacle to improve the productivity of rough machining. To address this challenge, an original approach is proposed to schedule the feedrate of multi-axis plunge milling based on the mechanistic model. The cross section of the removed material is used to calculate the complicated engagement of multi-axis plunge milling. First, an accurate mathematic model of the cross section is established by its defining parameters. Second, a specific mechanistic model for multi-axis plunge milling is deduced based on the identified cross section. Then, a mechanics-based feedrate scheduling strategy is proposed to regulate the cutting forces and torque in multi-axis plunge milling. Finally, three feedrate scheduling methods with different references are conducted and compared in experimental tests to verify this new approach. The method proposed in this paper can reduce the cutting time and smooth the variances of cutting forces and torque.

Combination of theoretical and numerical analysis, an assessment approach of shallow geothermal energy project is proposed. A case study on Chongqing is carried out to verify the methods. According to the theoretical calculation, the heat transfer power per meter of typical boreholes in Chongqing is 40 W/m for cooling and 50 W/m for heating. The numerical model of 100m borehole heat exchanger (BHE) of ground sourced heat pump (GSHP) system is built, two sets of heating and cooling loads are input to calculate the ground thermal response, the results show that the thermal unbalance ratio equals to 1.5 would ensure the safe and reliable long time operation of GSHP system. By comparing the single and group borehole model, the heat transfer efficiency of BHE is not influenced by adjacent boreholes with 6m drilling spacing, the temperature distribution among boreholes almost uniform after a year running, however, the increase of cumulative temperature of the ground reaches 2.2°C after five years running.

In this letter, we consider a cooperation system with multiple untrusted relays (URs). To keep the transmitted information confidential, we obtain joint channel characteristics (JCCs) through combining the channels from the source to the destination. Then, in the null space of the JCCs, jammers construct artificial noise to confuse URs when the source node broadcasts its data. Through a distributed implementation algorithm, the weight of each node can be obtained from its own channel state information. Simulation results show that high-level security of the system can be achieved when internal and external eavesdroppers coexist.

Plunge milling has been widely adopted in the manufacturing industry to rough machine open blisks, and its objective is to remove stock material with high efficiency and machining stability. A current technique challenge is to calculate the tool orientation and locations (called plunger paths) in four-axis rough plunging of open blisks, so that the residual raw material left on the blades after roughing is close to the specified value. To address this challenge, a novel approach is proposed to optimize tool orientation and determine tool locations for four-axis plunge milling of open blisks. First, tool locations are determined with two principles without interfering the blades and hub. Second, tool orientation is optimized according to a new evaluation criterion. Then, considering the impact of previous tool paths, an in-process model of a blisk is used to calculate residual material. Finally, an experiment is conducted to verify this new approach. This approach can promote four-axis plunge milling in the open blisk manufacturing.

With the development of Internet of Things, technology of Power over Ethernet can take enough electricity to LED lighting system. Depending on the sensed information of the current brightness and the number of persons in a room, the system can automatically identify and apply a predefined brightness. Therefore, it overcomes the disadvantages of traditional light control systems, for example, inefficient management, uncomfortable, waste of energy and security. At the same time system can transfer DC power and data through Ethernet, reduce the power adapter failure which caused by data network failure and promote the application of the low power network equipment. In addition, it has a wireless control function and makes the system more humanized.

Energy is a significant bottleneck of smartphone operation. Today's smartphone batteries can normally support less than two day's continuous daily use. It is therefore important to find out where the energy goes inside a smartphone. In this paper, we present a hardware based method for Android smartphones. We conduct a comprehensive power evaluation under a predefined set of test cases, and identify a number of primary power-hungry modules, such as the screen display, GPS and WiFi modules. Finally, an energy model for these modules is established.

With large spatial deployable antennas used more widely, the stability of deployable antennas is attracting more attention. The form of the support structure is an important factor of the antenna’s natural frequency, which is essential to study to prevent the resonance. The deployable truss structures based on shape memory polymer composites (SMPCs) have made themselves feasible for their unique properties such as highly reliable, low-cost, light weight, and self-deployment without complex mechanical devices compared with conventional deployable masts. This study offers deliverables as follows: an establishment of three-longeron beam and three-longeron truss finite element models by using ABAQUS; calculation of natural frequencies and vibration modes; parameter studies for influence on their dynamic properties; manufacture of a three-longeron truss based on SMPC, and modal test of the three-longeron truss. The results show that modal test and finite element simulation fit well.

This paper presents a special element named HMF (Hold-Match-Fetch) unit by us. The HMF unit implements token storing, token matching and token fetching mechanism that is necessary in dynamic dataflow ASIC. The HMF unit presented in this paper is implemented in asynchronous way and has been used in an AES ASIC chip, which is based on a dynamic dataflow structure and can resist different power analysis (DPA) attack by randomly changing the operations' sequence. Due to the application requirement, a random fetching mechanism is implemented by the HMF unit in this example.

A full compensated depletion-mode MOS capacitor is presented in this article. The capacitor is composed of MOS depletion capacitors which are biased appropriately to extend available usable voltage range. The capacitor is suitable for state-of-art technology and low-voltage switched capacitor applications. Completely digital technology cuts the cost down heavily. The voltage-dependence and temperature-dependence of the capacitor are much smaller compared with series and parallel compensated depletion-mode MOS capacitors. Theoretical analysis and HSPICE simulations show that the capacitor achieves a density of 0.52 fF/mum2 and a temperature-dependence coefficient of 0.096 ppm/C. A much smaller voltage-dependence square coefficient of 57.2 ppm/V makes it superior in full differential switched-capacitor applications.

THDFAES04 is a data flow random execution Rijndael encryption ASIC, which can resist against side-channel attacks and is low power. It is based on dynamic data-flow architecture. It performs token matching and random service jointly by the token Hold-Match-Fetch components. In experiments, it could resist 15000 less samples correlation power analysis attack. The fabricated chip's average energy of one 128bits key AES encryption is 0.053?J. Its die size is 2.21mm2. Its throughput distributes between 59 Mbps and 63 Mbps. Sponsored by the National Natural Science Foundation of China under grant No.60236020 and the Specialized Research Fund for the Doctoral Program of Higher Education No.20050003083.

The differential power analysis technique is a kind of attack to cryptographic device. It can extract keys by analyzing information leaked in the form of power usage. A power-balanced implementation was able to provide a cryptographic device resistant to power analysis. This paper presents an implementation of delay-insensitive carry-lookahead adder (DICLA) made of power-balanced modules whose power dissipated are independent of the input data. The feature of this design is to balance the power consumption on the transistor level. The power differenced of the power-balanced modules and the common modules are given out. The circuit level modified circuits were demonstrated to be more invulnerable by power analysis.

A low power low voltage ΣΔ ADM is given is this paper, which can be realized in standard digital CMOS technology. The circuit is realized in SMIC 0.18 μm 1P6M digital CMOS technology. The measured result based on an Advantest T6575 shows that the modulator can achieve 84 dB dynamic range with 1.2 V supply voltage. The total power dissipation is 2460 μW and the FOM is 154. The modulator is useful as a digital IP to be integrated into an SOC system.

This paper presents an AES (advanced encryption standard) chip that combats differential power analysis (DPA) side-channel attack through hardware-based random order execution. Both decryption and encryption procedures of an AES are implemented on the chip. A fine-grained dataflow architecture is proposed, which dynamically exploits intrinsic byte-level independence in the algorithm. A novel circuit called an HMF (Hold-Match-Fetch) unit is proposed for random control, which randomly sets execution orders for concurrent operations. The AES chip was manufactured in SMIC 0.18 μm technology. The average energy for encrypting one group of plain texts (128 bits secrete keys) is 19 nJ. The core area is 0.43 mm2. A sophisticated experimental setup was built to test the DPA resistance. Measurement-based experimental results show that one byte of a secret key cannot be disclosed from our chip under random mode after 64000 power traces were used in the DPA attack. Compared with the corresponding fixed order execution, the hardware based random order execution is improved by at least 21 times the DPA resistance.