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Protein function annotation has been one of the longstanding issues, which is key for discovering drug targets and understanding physiological or pathological process. A variety of computational methods have therefore been constructed to facilitate the research developments in this particular direction. However, the annotation of protein function based on computational methods has been suffering from the serious “long-tail problem”, and it remains extremely challenging for existing methods to improve the prediction accuracies for protein families intail label levels. In this study, an innovative strategy, entitled ‘AnnoPRO’, for protein function annotation was thus constructed.First, a novel method enabling image-like protein representations was proposed. This method is unique in capturing the intrinsic correlations among protein features, which can greatly favor the application of thestate-of-the-artdeep learning methods popular in image classification.Second, a multimodal framework integrating multichannel convolutional neural network and long short-term memory neural network was constructed to realize a deep learning-based protein functional annotation. Since this framework was inspired by a reputable method used in image classification for dealing with its ‘long-tail problem’, ourAnnoPROwas expected to significantly improve the annotation performance of the protein families intail label level. Multiple case studies based on benchmark were also conducted, which confirmed the superior performance ofAnnoPROamong the existing methods. All source codes and models ofAnnoPROwere freely available to all users athttps://github.com/idrblab/AnnoPRO, and would be essential complement to existing methods.

The ankle biomechanics is easily changed due to the acute injury of the tissue around the ankle joint and the damage of the ankle joint structure, such as ankle instability and joint surface imbalance. When the mechanical load of the ankle changes, it can cause ankle regeneration and remodeling processes such as cartilage loss, bone remodeling, and degenerative changes. The aim of this study was to investigate the effect and mechanism of ginsenoside Rg1 against interleukin-1β (IL-1β)-induced apoptosis in human articular chondrocytes (HACs). The apoptosis model of HAC cells was established by IL-1β induction, and then the HAC cells were cultured with different concentrations of Rg1. The protective effect of Rg1 on HAC cell apoptosis was investigated by detecting the changes of apoptosis and activity of PI3K/Akt/mitochondrial signaling pathway. The results showed that a specific concentration of Rg1 could promote the proliferation of IL-1β-induced HAC cells and inhibit apoptosis. At the same time, Rg1 treatment with specific concentration can reduce the content of reactive oxygen species (ROS) and malondialdehyde (MDA) in HACs and improve the related expression of mitochondrial membrane potential (MMP). Furthermore, qRT-PCR and western blot results showed that Rg1 could improve the low expression of Bcl-2 and inhibit the high expression of Bax, caspase-3, caspase-8, caspase-9, FasL, AIF, and Cyto c in IL-1β-induced cells. In summary, Rg1 can inhibit IL-1β-induced apoptosis of HAC cells by decreasing the activity of PI3K/Akt/mitochondrial signaling pathway, and Rg1 has a protective effect on apoptosis of HAC cells.

A typical output of a metabolomic experiment is a peak table corresponding to the intensity of measured signals. Peak table processing, an essential procedure in metabolomics, is characterized by its study dependency and combinatorial diversity. While various methods and tools have been developed to facilitate metabolomic data processing, it is challenging to determine which processing workflow will give good performance for a specific metabolomic study. NOREVA, an out-of-the-box protocol, was therefore developed to meet this challenge. First, the peak table is subjected to many processing workflows that consist of three to five defined calculations in combinatorially determined sequences. Second, the results of each workflow are judged against objective performance criteria. Third, various benchmarks are analyzed to highlight the uniqueness of this newly developed protocol in (1) evaluating the processing performance based on multiple criteria, (2) optimizing data processing by scanning thousands of workflows, and (3) allowing data processing for time-course and multiclass metabolomics. This protocol is implemented in an R package for convenient accessibility and to protect users' data privacy. Preliminary experience in R language would facilitate the usage of this protocol, and the execution time may vary from several minutes to a couple of hours depending on the size of the analyzed data.

The label-free quantification (LFQ) has emerged as an exceptional technique in proteomics owing to its broad proteome coverage, great dynamic ranges and enhanced analytical reproducibility. Due to the extreme difficulty lying in an in-depth quantification, the LFQ chains incorporating a variety of transformation, pretreatment and imputation methods are required and constructed. However, it remains challenging to determine the well-performing chain, owing to its strong dependence on the studied data and the diverse possibility of integrated chains. In this study, an R package EVALFQ was therefore constructed to enable a performance evaluation on >3000 LFQ chains. This package is unique in (a) automatically evaluating the performance using multiple criteria, (b) exploring the quantification accuracy based on spiking proteins and (c) discovering the well-performing chains by comprehensive assessment. All in all, because of its superiority in assessing from multiple perspectives and scanning among over 3000 chains, this package is expected to attract broad interests from the fields of proteomic quantification. The package is available at https://github.com/idrblab/EVALFQ.

In this study, the effects of multifunctional microbial inoculation on food waste composting based on the synergistic property between organic matter degradation and nitrogen fixation were investigated. The results showed that inoculation simultaneously strengthened organic matter degradation by 9.9% and improved the nitrogen content by 20.6% compared with that of the control group. Additionally, spectral analysis demonstrated that inoculation was conducive to the enhanced humification, which was supported by the improvement in polyphenol oxidase activity. Microbial analysis showed that most of the introduced microorganisms (Bacillus, Streptomyces, Saccharomonospora) successfully colonized, and stimulated the growth of other indigenous microorganisms (Enterobacter, Paenibacillus). Meanwhile, the change in microbial community structure was accompanied by the enhanced tricarboxylic acid cycle and amino acid metabolism. Furthermore, network analysis and structural equation model revealed that the enhanced cooperation of microorganisms, in which more carbon sources could be provided by cellulose decomposition for nitrogen fixation.

TNF α-induced protein 1 (TNFAIP1) was first identified in human umbilical vein endothelial cells and can be induced by tumor necrosis factor α (TNFα). Early studies have found that TNFAIP1 is involved in the development of many tumors and is closely associated with the neurological disorder Alzheimer’s disease. However, little is known about the expression pattern of TNFAIP1 under physiological conditions and its function during embryonic development. In this study, we used zebrafish as a model to illustrate the early developmental expression pattern of tnfaip1 and its role in early development. First, we examined the expression pattern of tnfaip1 during early zebrafish development using quantitative real-time PCR and whole mount in situ hybridization and found that tnfaip1 was highly expressed in early embryonic development and, subsequently, expression became localized to anterior embryonic structures. To investigate the function of tnfaip1 during early development, we constructed a model of a stably inherited tnfaip1 mutant using the CRISPR/Cas9 system. Tnfaip1 mutant embryos showed significant developmental delays as well as microcephaly and microphthalmia. At the same time, we found decreased expression of the neuronal marker genes tuba1b, neurod1, and ccnd1 in tnfaip1 mutants. Analysis of transcriptome sequencing data revealed altered expression of the embryonic development related genes dhx40, hspa13, tnfrsf19, nppa, lrp2b, hspb9, clul1, zbtb47a, cryba1a, and adgrg4a in the tnfaip1 mutants. These findings suggest an important role for tnfaip1 in the early development of zebrafish.

There was nearly 1.7 billion tons proved reserve in SINOPEC Shunbei oilfield, which is the deepest (>8000m) fault controlled marine carbonate oilfield in the world with high-temperature (>170 °C) and high -pressure (>140MPa). The formation geological conditions are complicated, high rock strength, easy leakage and collapse, multiple pressure systems co-exist in the slim borehole, which caused a series of directional drilling technical problems such as difficulty in controlling the tool surface, PDM build-up capacity prediction and so on. Therefore, the related research for ultra-deep direction drilling technology were carried out aiming at solving the directional drilling problem for Shunbei oilfield. Firstly, the optimized wellbore structure scheme design method was proposed, in which the geological characteristics, borehole size and the directional efficiency were considered. And then a double augmented well profile designed model was established based on optimizing the production casing size, through which the directional efficiency and the drilling rate of a trip were increased significantly, and the nonproductive time can be greatly reduced easily. Secondly, an ultra-deep directional well torque transmission prediction model was established based on the mechanical analysis of ultra-deep drilling string and based which a rapid tool face control method was formed. Furthermore, an innovative build-up rate prediction method was established based on both big Data analysis and balanced tendency build-up rate prediction method, and the accuracy is more than 90%. Moreover, the PDM rubber seal, stator and rotor dimensions are optimized to achieve high power output within a certain high temperature range to prolong the service life according to the wellbore temperature field. Finally, the optimization of high temperature MWD instrument and matching process technology was proposed, such as surface assisted cooling, borehole size enlarging and high displacement cooling technology effectively improve the reliability. The series of ultra-deep directional drilling technology has been applied in Shunbei oilfield. The field application results show that the average ROP of directional section is increased by more than 30%, directional efficiency is greatly improved, and the directional drilling cycle is shortened by more than 20%. Nearly 40 ultra-deep directional wells above 8000m have been constructed, setting more than 10 new Asia records of petroleum engineering onshore directional well. There are two innovations in this paper. The first is to put forward the design method of wellbore profile with the shortest drilling time as the goal, which can save 1-2 trips and improve the directional efficiency by more than 20%. The second is to introduce the prediction method of build-up rate based on borehole tendency angle, which improves the prediction accuracy of build-up rate by 28% in Shunbei ultra deep directional well.

Stroke causes significant morbidity and mortality worldwide, for which no satisfactory preventive option currently exists. Hypoxic preconditioning (HPC) is a protective strategy for cerebral ischemic stroke. To this end, we have identified, Conventional protein kinase C (cPKC)BetaII to play an important role in HPC. Pathway analysis and protein-protein interaction network building and functional proteomic exploration was used to identify 38 proteins in 6 Kyoto Encyclopedia of Genes and Genomes pathways that interact with cPKCBetaII in brains subjected to HPC. The role of the oxidative phosphorylation pathway was confirmed by experimental validation, and the demonstration that the activity of the complex I and complex V and expression and activity of Ndufv2 and ATP5d was increased. Ndufv2 was co-localized with PKCBetaII in neurons rather than glial cells. Together, these data show that Ndufv2 and the oxidative phosphorylation pathway play an important role in cPKCBetaII-related HPC mediated signalling, likely as an adaptive neuroprotective mechanism.

The effects of iron-carbon (Fe-C) particle amendment on organic matter degradation, product quality and functional microbial community in food waste composting were investigated. Fe-C particles (10%) were added to the material and composted for 32 days in a lab-scale composting system. The results suggested that Fe-C particle enhanced organic matter degradation by 12.3%, particularly lignocellulose, leading to a greater humification process (increased by 15.5%). In addition, NO

The equipment commonly used in managed pressure drilling (MPD) allows alternative responses to kicks that do not need to stop the pump or shut in the well. The pivotal issue of kick control for MPD is the early gas influx detection and the optimal initial response when the kick was detected during drilling. The careful research on gas influx detection and the corresponding control method is very important. Firstly, the valve opening, bottom hole and well head pressure variation characteristics were analyzed based on the real-time measured data, and then the valve opening and pressure signature of gas influx for different MPD modes (CBHP, CWHP, MFC) was obtained based on the theoretical and model analysis, in which the pressure variation caused by the tripping, ROP and flow rate variation were taken into account, through which the gas kick can accurately detected as soon as quickly. Secondly, the influence factors for initial response selection of kick control was analyzed, and then the comprehensive optimization schedule of response for kick control was established, in which several factors were took into account, such as formation characteristics, drilling conditions, influx intensity and so on, through which the best mode for kick control can be obtained easily. Moreover, integrated software that combined kick detection and gas kick control simulation was developed based on which the best pressure control procedure and kick initial response can be obtained easily. The gas influx detection and control technique has been applied in Fuling shale gas field of SINOPEC, which is the first large-scale commercial development shale gas field of China. The results show that we can make precisely gas detection based on the new early gas influx detection method and the kick can also be control very well based on the optimization method. Based on the proposed method for kick detection and control, the NPT have been reduced more than 60%. This study will presented a novel gas kick detection theoretical model for all common MPD modes, and the gas influx control optimal procedure. Through the field application in shale gas drilling, the results show that the NPT has been reduced obviously, and the optimal kick control was designed has successfully prevented the serious kick and reduced the drilling cost.

Tremendous amounts of oil and gas reservoir are located in ultra-deep formations, such as Shunnan block in Tarim basin of China, some reservoirs buried deeper than 8000m and which are major exploration areas of SINOPEC. The formation geological conditions are complicated, multiple pressure systems co-exist in the same borehole, narrow pressure-margin problems, all above may cause down-hole troublesome conditions while cementing, such as leaking, fracturing formations and so on. And the managed pressure cementing (MPC) was selected for solving the above problems. But the key for a successful MPC depend on accurate, real-time knowledge of dynamic parameters calculation. Therefore, a real time dynamic parameters calculation for MPC is very important. Firstly, a comprehensive real-time hydraulic calculation method for cementing replacement process was established, in which the difference of density, rheological properties, location and length of different fluids were taken into account. In order to improve the calculation precision, the flow channel both in pipe and annuli was divided into several sections, through which the different diameters of the channels were considered. Secondly, according to the density contrast of operating fluids, a vacuum (U-Tube effect) will appear at the inlet in the cementing replacement process, an integrated U-Tube effect analytical model was established based on the Euler equation, in which the influence of well deviation was taken into account too, and though which the height and volume of vacuum, the down-hole operating fluids acceleration, the out flow rate variation et al. all can be accurately calculated and simulated. Moreover, a series of system calculation software were developed to predict cementing fluids position, fluids acceleration, flow pressure drop, BHP, expected WHP and the related control parameters for MPC. The proposed model has been applied in HPHT ultra-deep well MPC operation of SINOPEC Northwest oil filed in Traim basin, there is an excellent match between the calculated and measured data. Furthermore, this simulation software has been used for designing the MPC parameters, and it runs smoothly with convenient operation. Therefore it can be seen this system can be applied to provide more convenient fast and precise dynamic parameters monitoring for MPC. This study proposed a novel model of Cementing dynamic parameters calculating and developed a comprehensive real-time monitoring system for MPC. Through the application of the monitoring, we can adjust the cementing parameters in real time while MPC, and this real-time monitoring has been applied in several wells very well. Therefore, this study is novel and can afford an effective approach to improve cement quality.

The longitudinal vibration of the drill pipe contains considerable energy which can be used to improve the rock-breaking efficiency during drilling. It is very important to the development of drilling speed-up tools to have a comprehensive understanding of the energy conversion efficiency of downhole drill string vibration. In this paper, the characteristics of downhole bit load and longitudinal vibration of drill string under different conditions were studied in the experiment, and the analysis method of energy conversion efficiency from drill string vibration to spring potential energy was proposed. The experimental analysis showed that the fluctuation of the downhole bit load was reduced by 10%–90% after the spring was installed in the bottom hole assembly. The rotation rate and the spring elastic stiffness had a significant and positive influence on the fluctuation amplitude of the downhole bit load. Meanwhile, the longitudinal vibration amplitude and acceleration of the drill string peaked at the elastic stiffness of 1 kN/mm. The closer the spring position to the drill bit was, the more severe the longitudinal vibration of the drill string above the spring component was. The bit load and the rotation rate had a positive influence on the severity of longitudinal vibration. The analysis of energy conversion efficiency showed that the available mechanical energy range of the longitudinal vibration of the drill pipe was about 200–420 kW. The work power of the drill string vibration to the spring component increased sharply and then decreased with the increasing of elastic stiffness. The energy conversion efficiency came to the optimal value when the elastic stiffness was between 1 kN/mm and 2 kN/mm. Increasing the rotation rate, keeping the bit load below 134.5 kN and installing the spring component near the drill bit are beneficial for improving the energy conversion efficiency of drill string vibration. This paper reveals the main factors affecting the energy conversion efficiency of drill string vibration and their influencing laws, and determines the range of WOB, rotation speed, spring position and stiffness to obtain the best energy conversion efficiency.

Introduction DJ-1 mutation is a causative reason for familial Parkinson's disease (PD). Leucine166Proline (L166P) and C106S are two important DJ-1 mutations. In this study, we established hydrogen peroxide (H2 O2 ) induced L166P and C106S DJ-1-transfected neuroblastoma (SH-SY5Y) cellular models of PD and investigated the effects of Cistanche extracts and key bioactive compounds, including acteoside, echinacoside, caffeic acid, and Cistanche total glycosides on these two models. Methods After expressing FLAG-tagged L166P and C106S DJ-1 plasmids in Escherichia coli, the expressed plasmids were collected, treated with restriction enzyme, and identified using DNA electrophoresis. After purification, the L166P DJ-1 and C106S DJ-1 plasmids were separately transfected into SH-SY5Y cells using liposomes. Transfected SH-SY5Y cells were detected by western blotting and immunocytochemistry. Cell viability was determined using MTT assay. Results Both western blotting and immunocytochemistry showed that L166P and C106S DJ-1 were highly expressed in the transfected SH-SY5Y cells. MTT assays showed that transfection with L166P or C106S DJ-1 reduced the viability of SH-SY5Y cells exposed to H2 O2 , as compared to untransfected SH-SY5Y cells. In addition, Cistanche extracts and key bioactive compounds, including acteoside, echinacoside, caffeic acid, and Cistanche total glycosides, significantly inhibited the decreases of cell viability caused by H2 O2 in L166P and C106S DJ-1-transfected SH-SY5Y cells. Conclusions These findings suggest that we successfully established sensitive and stable H2 O2 induced L166P DJ-1- and C106S DJ-1-transfected SH-SY5Y cell models of PD and Cistanche extracts may thus be useful for treating PD.

Background:Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.Objective:The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.Methods:Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.Results:In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.Conclusion:In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

The ultra-high pressure water jet assisted mechanical drilling technology is an effective approach to improve the rate of penetration (ROP), however, due to unreasonable design ideas and low reliability of the existing down-hole supercharger, this technology is not applied widely. To make breakthrough of this technology, a new idea of utilizing the drill string vibration energy to modulate ultra-high pressure jet is first proposed, and a novel down-hole supercharger, down-hole drill string absorption & hydraulic supercharging device (DSAHSD), is developed. The DSAHSD combines the advantages of reducing the axial drill string vibration and generating ultra-high pressure jet to effectively assist rock breaking. When the drilling fluid flows through this tool, part of the drilling fluid will be modulated to the ultra-high pressure jet by periodic compression of piston drove by drill string vibration. Because of hydraulic auxiliary rock breaking of the ultra-high pressure jet, the drillability of rock and the ROP will be enhanced. To analyse the feasibility and influence factors of the tool, mathematical model were established, the results show that the tool could produce more than 140 MPa pressure and the outer pressure increases with the increase of weight on bit and rotary speed. Moreover, there is an optimal diameter of ultra-high pressure nozzle to optimal performance of the tool. This tool has been applied to more than 60 wells in four oil fields throughout China. The results indicate that the maximum density of the test drilling fluid is 1.9 g/cm3, the single maximum footage is 1480 m, and the operation time of the tool is more than 200 h. Furthermore, the average ROP was increased by approximately 11–831%. In conclusion, the DSAHSD has the characteristics of a simple structure, has a long lifetime, is able to adapt well with existing drilling equipment, and can provide guarantee for wide application of the ultra-high pressure jet technology in oil fields.

Through the analysis of gas-cut features in deepwater drilling and shortages of existing gas-cut detection methods, the feasibility of early detection of gas cut at the bottom of riser was demonstrated, and a method was proposed for quantitative description of gas-cut degree in deepwater drilling based on ultrasonic monitoring at the bottom of riser. The problems of Doppler ultrasound gas-cut detection method was analyzed and the experimental device of gas-cut monitoring at the bottom of riser based on the ultrasonic transmission was built, which was used to analyze the sound attenuation characteristics under different conditions of void fraction. The solutions for using ultrasound to monitor gas-cut situation at the bottom of riser was proposed. Combined with the gas-liquid two-phase model of wellbore annulus in deepwater drilling and the formation pressure prediction method with credibility, the inverse calculation method of gas-cut degree in wellbore was established, which was based on the monitoring data of gas cut at the bottom section of riser. This method could detect the gas cut about four minutes in advance compared with conventional methods, and the gas cut occurring moment, the time left for gas to reach the wellhead, the total overflow rate at any moment, and the void fraction in different depth could be accurately determined based on the acoustic response data of the bottom of riser. Key words: deepwater drilling, gas-cut monitoring, ultrasonic transmission, gas-cut degree, inverse calculation method

DJ-1 is one of the important genes found in Parkinson's disease (PD). Studies have shown that the DJ-1 protein levels are elevated in the cerebrospinal fluid (CSF) and plasma of sporadic PD patients, and the DJ-1 protein levels in the CSF and plasma may serve as biomarkers of PD. However, Japanese scholars previously reported that there was no difference in the levels of the DJ-1 protein in serum between sporadic PD patients and controls. Therefore, whether the serum DJ-1 protein levels are different between PD patients and controls in Chinese patients as well as whether serum DJ-1 protein can serve as a biomarker of PD are unknown. The present study aimed to determine whether there was a difference in serum DJ-1 protein levels between Chinese PD patients and controls. The subjects included 18 primary PD patients and 7 controls. Blood was collected by venipuncture, and serum was collected by centrifugation after the blood was coagulated. The serum DJ-1 protein levels were detected by both Western blot and ELISA. There were differences in the serum DJ-1 protein levels among different individuals. The serum DJ-1 concentration in PD patients was 11.3±10.1ng/ml, and that in controls was 18.1±12.8ng/ml (P>0.05). In conclusion, similar to the study conducted by Japanese scholars, we found no significant difference in the serum DJ-1 protein levels between PD patients and controls in Chinese subjects. The levels of the DJ-1 protein in serum may not be a biomarker of PD. In addition, there may be differences in the serum DJ-1 protein levels between Chinese and Japanese patients.

To improve the down-hole drilling fluid energy and its utilization efficiency, a drilling string absorption and hydraulic pulsed jet generator was designed, its simulation model was established and simulation analysis was conducted, and its performance was tested in field application. Based on the idea of translating the energy of the drill string vibration into high pressure hydraulic pulsating jet energy, the structure of the device was designed and its working principle was analyzed, and then its simulation model was established. The simulation analysis results demonstrate that the device can produce the jet pressure 2 to 6 MPa higher than the nozzle pressure drop in conventional drilling. Field test results show that the device can improve the drilling speed significantly and extend the service life of the bit effectively; the device itself has steady performance and long service life, and can satisfy the drilling requirements. Key words: drilling, drilling string vibration, down-hole fluid pressure, pulsating jet, simulation analysis, penetration rate

The internal parts of currently used float valve have serious erosion and unstable performance situations. If the drilling float valve fails, it will take a long time to deal with accidents and increase the risk of drilling operations. To solve this problem, we use the computational fluid dynamics method (CFD) to analyze the flow field structure of common downhole float valve, including the velocity field, turbulence intensity field, and wall shear stress field. The study found that: the flow field is quite disordered near the sealing surface of valve core, as well as near the spring and the opening parts of lower seat. Meanwhile, strong vortexes have been generated. This is a good corresponding relationship between the CFD simulation and the erosion (location and extent) in real float valve. This indicates that the CFD method can be used for optimization of existing float valve. On this basis, we present the optimal design, and use CFD method to analyze the new design. The analysis results show that the optimized design has not high velocity region, simultaneously, disturbance and vortex phenomenon of the flow field are significantly reduced and even disappeared. Its flow field distribution is more reasonable, which can reduce the factors causing erosion and performance failure. Therefore, we can infer that the new float valve has better anti-erosion performance and working stability.

Predicting the rate of penetration (ROP) is critical for drilling optimization because maximization of ROP can greatly reduce expensive drilling costs. In this work, the typical extreme learning machine (ELM) and an efficient learning model, upper-layer-solution-aware (USA), have been used in ROP prediction. Because formation type, rock mechanical properties, hydraulics, bit type and properties (weight on the bit and rotary speed), and mud properties are the most important parameters that affect ROP, they have been considered to be the input parameters to predict ROP. The prediction model has been constructed using industrial reservoir data sets that are collected from an oil reservoir at the Bohai Bay, China. The prediction accuracy of the model has been evaluated and compared with the commonly used conventional artificial neural network (ANN). The results indicate that ANN, ELM, and USA models are all competent for ROP prediction, while both of the ELM and USA models have the advantage of faster learning speed and better generalization performance. The simulation results have shown a promising prospect for ELM and USA in the field of ROP prediction in new oil and gas exploration in general, as they outperform the ANN model. Meanwhile, this work provides drilling engineers with more choices for ROP prediction according to their computation and accuracy demand.

It is a hot topic for deep/ultradeep wells to improve rock-breaking efficiency and drilling speed by available downhole energy. Based on different downhole energies and working conditions, specialized plunger pump is proposed to convert longitudinal vibration of drilling string into rock-breaking energy. Technical design is developed to generate high-pressure water jet. And then a simulation model is built to verify feasibility of the technical design. Through simulation, the influence law of key factors is obtained. On this basis, this device is tested in several wells. The result indicates this device can increase drilling speed as much as 136%. Meanwhile the harmful vibration can be absorbed. The energy from drilling string vibration is of high frequency and increases as well depth and formation anisotropy increase. By reducing adverse vibration, this device is able to increase the drilling speed and the service life also meets the demand of field application. The longest working time lasts for more than 130 hours. The performance of this device demonstrates great application prospect in deep/ultradeep resources exploration. To provide more equipment support for deep/ultradeep wells, more effort should be put into fundamental study on downhole drill string vibration and related equipment.