A Guide to Cheek Augmentation: Single-Point Deep Injection of Hyaluronic Acid Filler at Midface in Close Proximity to Medial Suborbicularis Oculi Fat (SOOF) Area

Loss of volume in midface can result in an aged, wasted appearance. Osseous and fat atrophy with aging may further contribute to the loss of soft tissue support and midface ptosis. In the aging of periorbital area and midface, fat atrophy occurs mostly in the suborbicularis oculi fat (SOOF) area. The authors proposed that injection of hyaluronic acid (HA) filler to support the SOOF area could counteract the aging sign due to fat atrophy, restore volume loss and achieve a more youthful appearance. The authors described the treatment of 10 female patients who received CHAP®-particle hyaluronic acid (CHAP®-HA) injections for cheek augmentation, using single-point deep injection technique at midface in close proximity to SOOF area. Such approach provides satisfactory cheek augmentation results without significant complications. The authors discussed a rationale for their choice of dermal filler and provided an injection technique for restoring volume in the midface region with CHAP®-HA. Such technique is relatively quick to perform, have little down time, and result in a high rate of patient satisfaction.

Use of High-Resolution Ultrasound (HRU) in the Assessment of Deep Injections of CHAP-Hyaluronic Acid (CHAP-HA) Fillers for Midface Lift

High-resolution ultrasound (HRU) imaging is a useful tool to study hyaluronic acid (HA) filler injection in the face. It is noninvasive, quick, well-tolerated, and can provide in vivo and dynamic information. The formations of pools or pearls in HA fillers could be observed real time during injection. The plane of injection could be determined accurately, and there were no specimen manipulation artifacts. It was observed that HA gel fillers with differing production technologies showed distinct spread and distribution patterns in the periocular tissues on HRU examination. The authors used HRU to assess deep injections of CHAP-Hyaluronic Acid (CHAP-HA) fillers for midface lift. 10 patients who underwent bilateral midface deep injections using CHAP-HA filler were examined with HRU before and immediately after treatment, and in 2 weeks and one month later. The CHAP-HA appeared as hypoechoic densities within the preperiosteal plane in HRU. CHAP-HA adopted variable morphology within the tissue depending on individual tissue densities and the compliance of the tissues in the plane of injection. CHAP-HA was unidentifiable with surrounding tissue after one month in 13 of the 20 injection sites. HRU allows in vivo study of CHAP-HA injection behavior and could be a tool for further studies of HA-tissue reactions.

Coot Optimization with Deep Learning-Based False Data Injection Attack Recognition

The recent developments in smart cities pose major security issues for the Internet of Things(IoT)devices.These security issues directly result from inappropriate security management protocols and their implementation by IoT gadget developers.Cyber-attackers take advantage of such gadgets’vulnerabilities through various attacks such as injection and Distributed Denial of Service(DDoS)attacks.In this background,Intrusion Detection(ID)is the only way to identify the attacks and mitigate their damage.The recent advancements in Machine Learning(ML)and Deep Learning(DL)models are useful in effectively classifying cyber-attacks.The current research paper introduces a new Coot Optimization Algorithm with a Deep Learning-based False Data Injection Attack Recognition(COADL-FDIAR)model for the IoT environment.The presented COADL-FDIAR technique aims to identify false data injection attacks in the IoT environment.To accomplish this,the COADL-FDIAR model initially preprocesses the input data and selects the features with the help of the Chi-square test.To detect and classify false data injection attacks,the Stacked Long Short-Term Memory(SLSTM)model is exploited in this study.Finally,the COA algorithm effectively adjusts the SLTSM model’s hyperparameters effectively and accomplishes a superior recognition efficiency.The proposed COADL-FDIAR model was experimentally validated using a standard dataset,and the outcomes were scrutinized under distinct aspects.The comparative analysis results assured the superior performance of the proposed COADL-FDIAR model over other recent approaches with a maximum accuracy of 98.84%.

The accurate location of the injection- induced microearthquakes in German Continental Deep Drilling Program

From August 21, 2000 to October 20, 2000,a fluid injection-induced seismicity experiment has been carried out in the KTB (German Continental Deep Drilling Program). The KTB seismic network recorded more than 2 700 events. Among them 237 events were of high signal-to-noise ratio, and were processed and accurately located. When the events were located, non KTB events were weeded out by Wadatis method. The standard deviation, mean and median were obtained by Jackknife's technique, and finally the events were accurately located by Gei-gers method so that the mean error is about 0.1 km. No earthquakes with focal depth greater than 9.3 km, which is nearly at the bottom of the hole, were detected. One of the explanation is that at such depths the stress levels may not close to the rocks frictional strength so that failure could not be induced by the relatively small perturbation in pore pressure. Or at these depths there may be no permeable, well-oriented faults. This depth may be in close proximity to the bottom of the hole to the brittle-ductile transition, even in this relatively stable interior of the in-teraplate. This phenomenon is explained by the experimental results and geothermal data from the superdeep bore-hole.

Possible link between long-term and short-term water injections and earthquakes in salt mine and shale gas site in Changning,south Sichuan Basin, China

Late at night on 17 June 2019,a magnitude 6.0 earthquake struck Shuanghe Town and its surrounding area in Changning County,Sichuan,China,becoming the largest earthquake recorded within the southern Sichuan Basin.A series of earthquakes with magnitudes up to 5.6 occurred during a short period after the mainshock,and we thus refer to these earthquakes as the Changning M6 earthquake sequence(or swarm).The mainshock was located very close to a salt mine,into which for^3 decades fresh water had been extensively injected through several wells at a depth of 2.7–3 km.It was also near(within^15 km)the epicenter of the 18 December 2018 M5.7 Xingwen earthquake,which is thought to have been induced by shale gas hydraulic fracturing(HF),prompting questions about the possible involvement of industrial activities in the M6 sequence.Following previous studies,this paper focuses on the relationship between injection and seismicity in the Shuanghe salt field and its adjacent Shangluo shale gas block.Except for a period of serious water loss after the start of cross-well injection in 2005–2006,the frequency of earthquakes shows a slightly increasing tendency.Overall,there is a good correlation between the event rate in the Shuanghe area and the loss of injected water.More than 400 M≥3 earthquakes,including 40 M≥4 and 5 M≥5 events,had been observed by the end of August 2019.Meanwhile,in the Shangluo area,seismicity has increased during drilling and HF operations(mostly in vertical wells)since about 2009,and dramatically since the end of 2014,coincident with the start of systematic HF in the area.The event rate shows a progressively increasing background with some fluctuations,paralleling the increase in HF operations.More than 700 M≥3 earthquakes,including 10 M≥4 and 3 M≥5 in spatially and temporally clustered seismic events,are correlated closely with active fracturing platforms.Well-resolved centroid moment tensor results for M≥4 earthquakes were shown to occur at very shallow depths around shale formations with active HF,in agreement with some of the clusters,which occurred within the coverage area of temporary or new permanent monitoring stations and thus have been precisely located.After the Xingwen M5.7 earthquake,seismic activity in the salt well area increased significantly.The Xingwen earthquake may have created a unidirectional rupture to the NNW,with an end point close to the NW-trending fault of the Shuanghe earthquake.Thus,a fault in the Changning anticline might have terminated the fault rupture of the Xingwen earthquake,possibly giving the Xingwen earthquake a role in promoting the Changning M6 event.

Potential assessment of CO_(2)geological storage based on injection scenario simulation:A case study in eastern Junggar Basin

Carbon Capture and Storage(CCS)is one of the effective means to deal with global warming,and saline aquifer storage is considered to be the most promising storage method.Junggar Basin,located in the northern part of Xinjiang and with a large distribution area of saline aquifer,is an effective carbon storage site.Based on well logging data and 2D seismic data,a 3D heterogeneous geological model of the Cretaceous Donggou Formation reservoir near D7 well was constructed,and dynamic simulations under two scenarios of single-well injection and multi-well injection were carried out to explore the storage potential and CO2 storage mechanism of deep saline aquifer with real geological conditions in this study.The results show that within 100 km^(2)of the saline aquifer of Donggou Formation in the vicinity of D7 well,the theoretical static CO_(2)storage is 71.967×106 tons(P50)①,and the maximum dynamic CO_(2)storage is 145.295×106 tons(Case2).The heterogeneity of saline aquifer has a great influence on the spatial distribution of CO_(2)in the reservoir.The multi-well injection scenario is conducive to the efficient utilization of reservoir space and safer for storage.Based on the results from theoretical static calculation and the dynamic simulation,the effective coefficient of CO_(2)storage in deep saline aquifer in the eastern part of Xinjiang is recommended to be 4.9%.This study can be applied to the engineering practice of CO_(2)sequestration in the deep saline aquifer in Xinjiang.

Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model

E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely used.Various web developers may have varying levels of understanding when it comes to securing an online application.Structured Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these flaws.Many published articles focused on these attacks’binary classification.This article described a novel deep-learning approach for detecting SQL injection and XSS attacks.The datasets for SQL injection and XSS payloads are combined into a single dataset.The dataset is labeledmanually into three labels,each representing a kind of attack.This work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a vector.Our model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload dataset.The payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and normal.The outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious payloads.BiLSTM’s high performance was demonstrated by its accuracy of 99.26%.

Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids

False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal self-attention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness.

韧带深层透明质酸注射填充在面部年轻化治疗中的效果探讨

目的:探究韧带深层填充注射透明质酸对面部皮肤松垂患者面部年轻化的影响。方法:选择2022年1月-2023年1月笔者医院收治的120例面部皮肤松垂就医者,按随机数字表法分为观察组和对照组,各60例。对照组行传统浅层填充注射透明质酸治疗,观察组行韧带深层填充注射透明质酸治疗。统计比较两组面部年轻化改善程度[整体美学改善量表(Global aesthetic improvement scale,GAIS)]、面部皮肤相关指标[经皮水分丢失量(Trans epidermal water loss,TEWL)、表皮含水量、pH值及表皮油脂含量]、颧颊部横面弧(D-B-E)、冠状面弧(A-B-C)半径、就医者满意度及不良反应发生情况。结果:术后1周,观察组就医者面部皱纹、肤色及皮肤紧致度GAIS评分、表皮含水量、pH值及表皮油脂含量均高于对照组(P<0.05),TEWL低于对照组(P<0.05)。术后1周,两组颧颊部横面弧(D-B-E)、冠状面弧半径(A-B-C)均增长,且观察组长于对照组(P<0.05)。观察组就医者的满意度高于对照组(P<0.05),不良反应总发生率低于对照组(P<0.05)。结论:韧带深层填充注射透明质酸可明显提高面部皮肤松垂患者的面部年轻化改善程度,提升面部整体轮廓协调度,并减少不良反应发生率,就医者满意度高。

Optimal Hybrid Deep Learning Enabled Attack Detection and Classificationin IoT Environment

The Internet of Things (IoT) paradigm enables end users to accessnetworking services amongst diverse kinds of electronic devices. IoT securitymechanism is a technology that concentrates on safeguarding the devicesand networks connected in the IoT environment. In recent years, False DataInjection Attacks (FDIAs) have gained considerable interest in the IoT environment.Cybercriminals compromise the devices connected to the networkand inject the data. Such attacks on the IoT environment can result in a considerableloss and interrupt normal activities among the IoT network devices.The FDI attacks have been effectively overcome so far by conventional threatdetection techniques. The current research article develops a Hybrid DeepLearning to Combat Sophisticated False Data Injection Attacks detection(HDL-FDIAD) for the IoT environment. The presented HDL-FDIAD modelmajorly recognizes the presence of FDI attacks in the IoT environment.The HDL-FDIAD model exploits the Equilibrium Optimizer-based FeatureSelection (EO-FS) technique to select the optimal subset of the features.Moreover, the Long Short Term Memory with Recurrent Neural Network(LSTM-RNN) model is also utilized for the purpose of classification. At last,the Bayesian Optimization (BO) algorithm is employed as a hyperparameteroptimizer in this study. To validate the enhanced performance of the HDLFDIADmodel, a wide range of simulations was conducted, and the resultswere investigated in detail. A comparative study was conducted between theproposed model and the existing models. The outcomes revealed that theproposed HDL-FDIAD model is superior to other models.

Reducing risk in long deep tunnels by using TBM and drill-and-blast methods in the same project-the hybrid solution

There are many examples of TBM tunnels through mountains, or in mountainous terrain, which have suffered the ultimate fate of abandonment, due to insufficient pre-investigation. Depth-of-drilling limitations are inevitable when depths approach or even exceed l or 2 km. Uncertainties about the geology, hydro-geology, rock stresses and rock strengths go hand-in-hand with deep or ultra-deep tunnels. Unfortunately, unexpected conditions tend to have a much bigger impact on TBM projects than on drill-and-blast projects. There are two obvious reasons. Firstly the circular excavation maximizes the tangential stress, making the relation to rock strength a higher source of potential risk. Secondly, the TBM may have been progressing fast enough to make probe-drilling seem to be unnecessary. If the stress-to-strength ratio becomes too high, or if faulted rock with high water pressure is unexpectedly encountered, the ＂unexpected events＂ may have a remarkable delaying effect on TBM. A simple equation explains this phenomenon, via the adverse local Q-value that links directly to utilization. One may witness dramatic reductions in utilization, meaning ultra-steep deceleration-of-the-TBM gradients in a log-log plot of advance rate versus time. Some delays can be avoided or reduced with new TBM designs, where belief in the need for probe-drilling and sometimes also pre-injection, have been fully appreciated. Drill-and-blast tunneling, inevitably involving numerous ＂probe-holes＂ prior to each advance, should be used instead, if investigations have been too limited. TBM should be used where there is lower cover and where more is known about the rock and structural conditions. The advantages of the superior speed of TBM may then be fully realized. Choosing TBM because a tunnel is very long increases risk due to the law of deceleration with increased length, especially if there is limited pre-investigation because of tunnel depth.

Actions of negative bias temperature instability （NBTI） and hot carriers in ultra-deep submicron p-channel metal-oxide-semiconductor field-effect transistors （PMOSFETs）

Hot carrier injection （HCI） at high temperatures and different values of gate bias Vg has been performed in order to study the actions of negative bias temperature instability （NBTI） and hot carriers. Hot-carrier-stress-induced damage at Vg = Vd, where Vd is the voltage of the transistor drain, increases as temperature rises, contrary to conventional hot carrier behaviour, which is identified as being related to the NBTI. A comparison between the actions of NBTI and hot carriers at low and high gate voltages shows that the damage behaviours are quite different： the low gate voltage stress results in an increase in transconductance, while the NBTI-dominated high gate voltage and high temperature stress causes a decrease in transconductance. It is concluded that this can be a major source of hot carrier damage at elevated temperatures and high gate voltage stressing of p-channel metal-oxide-semiconductor field-effect transistors （PMOSFETs）. We demonstrate a novel mode of NBTI-enhanced hot carrier degradation in PMOSFETs. A novel method to decouple the actions of NBTI from that of hot carriers is also presented.

平衡式双解封注水封隔器的研制与应用

针对冀东油田大斜度深井多级分注管柱解封负荷大、密封有效期短的问题,在剖析封隔器结构的基础上,对关键结构进行三维仿真模拟优化设计,研制了平衡式双解封注水封隔器。该封隔器设计独立的双解封方式,减小解封负荷;利用弹簧及注水管柱内外压差,实现反洗阀自动关闭;综合采用橡胶挤压及金属线密封方式,提高反洗阀密封可靠性;胶筒优选高强度氟橡胶材质,提高耐温耐压性能;设计平衡活塞保护解封销钉,消除高压差提前解封风险。现场应用11井次,施工成功率为100%,密封有效期超过30个月;起管解封负荷降低17.2%。该封隔器密封周期长,解封负荷小,可满足大斜度深井高压分注长效密封需求,具有良好的经济效益和推广应用前景。

水泥分解炉SNCR脱硝系统的深度强化学习多目标优化控制研究

选择性非催化还原(selective non-catalytic reduction,SNCR)脱硝过程的工艺参数优化可以有效减少水泥分解炉NO_(x)排放和脱硝运行成本。以某水泥分解炉为研究对象,建立基于LightGBM的NO_(x)浓度预测模型,以脱硝成本和NO_(x)浓度最小化为优化目标,采用深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法对水泥分解炉掺烧污泥协同SNCR脱硝过程的相关工艺参数进行优化控制建模。结果表明,NO_(x)浓度预测模型均方根误差(root mean squared error,RMSE)为6.8,平均绝对百分比误差(mean absolute percentage error,MAPE)为3.48%;采用DDPG算法可以对相关工艺参数进行优化,喷氨量和污泥掺烧量分别为427.87 L/h和9.78 t/h时,NO_(x)排放浓度为225.99 mg/(Nm^(3)),脱硝运行成本为1 747.8元/h。该优化结果与其他优化算法结果和常规工况对比,NO_(x)排放浓度和脱硝运行成本均呈现不同程度下降;对模型进行仿真及效果验证可知,所建立模型能输出合理的喷氨量和污泥掺烧量组合,减少SNCR出口NO_(x)浓度波动,有效降低NO_(x)排放浓度和脱硝成本,可实现对SNCR脱硝系统的多目标优化控制。该结果可为基于智能算法的水泥分解炉SNCR脱硝的多目标优化控制设计提供一定参考。

超深层断控碳酸盐岩油藏地质力学建模及其在开发中的应用

为提高超深断控碳酸盐岩油藏的开发效益,通过开展大尺寸岩样力学实验,揭示高角度—近直立断裂面变形与连通机理;基于高压注水提采的力学与流动耦合原理,通过地质力学建模,明确了断控碳酸盐岩油藏现今地应力场和断裂活动性分布规律;发现不同方位的断裂活动性以及不同部位的缝洞体连通性有明显差异,进而分析了不同井眼轨迹的开发效果,提出了地质工程一体化工作方法,科学指导井眼轨迹设计和注水方案优化。结果表明:①走滑断裂变形中的大尺度破碎体和高角度裂缝系统是影响储层品质的关键因素,高压注水一方面能够激活先存裂缝,一方面还能在先存裂缝基础上发生延伸扩展,甚至可以产生新的裂缝,促进了断控缝洞体在纵横向上的互相连通;②高压注水过程中断裂体内部发生力学与流动之间的耦合变化,渗流环境得到改善,通过循环举升,从而提高油气采收率;③根据断裂体形态、产状以及断裂面动态剪切变形连通性,可优选定向井最佳井点和井眼轨迹,并优化注水方案;④塔里木盆地断控油藏试验区通过高压注水,采收率提高5个百分点,该方法为超深断控型油藏高效开发提供了较好的理论依据和技术支撑。

深沟球轴承塑料保持架的联合仿真优化

为改善深沟球轴承塑料保持架的注塑变形问题,以锁口端部收缩值为优化评价指标,采用模流分析对保持架浇口数量、加强筋形状以及玻纤含量进行优化选择,通过Minitab软件设计响应曲面试验并结合分类回归树(CART)模型获得注塑工艺参数的最优预测组合。结果表明,优化后锁口端部收缩值由2.461 mm降至1.092 mm,下降55.63%,保持架注塑变形问题得到明显改善。再基于Helius联合仿真对保持架的熔接痕强度进行分析,将模流分析结果映射到ANSYS并通过结构求解器进行运算,证明了优化后的深沟球轴承塑料保持架无失效风险,熔接痕处强度满足要求。

Analysis and Design Innovation on Underground Gasifier for Medium-Deep Coal Seam

Over the past 80 years,dozens of underground coal gasification(UCG)mine field tests have been carried out around the world.However,in the early days,only a small number of shallow UCG projects in the former Soviet Union achieved commercialised production.In this century,a few pilot projects in Australia also achieved short-term small-scale commercialised production using modern UCG technology.However,the commercialisation of UCG,especially medium-deep UCG projects with good development prospects but difficult underground engineering conditions,has not progressed smoothly around the world.Considering investment economy,a single gasifier must realise a high daily output and accumulated output,as well as hold a long gasification tunnel to control a large number of coal resources.However,a long gasification tunnel can easily be affected by blockages and failure,for which the remedial solutions are difficult and expensive,which greatly restricts the investment economy.The design of the underground gasifier determines the success or failure of UCG projects,and it also requires the related petroleum engineering technology.Combining the advantages of the linear horizontal well(L-CRIP)and parallel horizontal well(P-CRIP),this paper proposes a new design scheme for an“inclined ladder”underground gasifier.That is to say,the combination of the main shaft of paired P-CRIP and multiple branch horizontal well gasification tunnels is adopted to realise the control of a large number of coal resources in a single gasifier.The completion of the main shaft by well cementation is beneficial for maintaining the integrity of the main shaft and the stability of the main structure.The branch horizontal well is used as the gasification tunnel,but the length and number of retracting injection points are limited,effectively reducing the probability of blockage or failure.The branch horizontal well spacing can be adjusted flexibly to avoid minor faults and large cracks,which is conducive to increasing the resource utilisation rate.In addition,for multi-layer thin coal seams or ultra-thick coal seams,a multi-layer gasifier sharing vertical well sections can be deployed,thereby saving investment on the vertical well sections.Through preliminary analysis,this gasifier design scheme can be realised in engineering,making it suitable for largescale deployment where it can increase the resource utilisation rate and ensure stable and controllable operations.The new gasifier has outstanding advantages in investment economy,and good prospects for application in the commercial UCG projects of medium-deep coal seams.

基于GATv2模型的虚假数据注入攻击检测方法

虚假数据注入攻击(False data injection attack,FDIA)能够躲避传统不良数据检测器,给智能电网的稳定运行带来了挑战。因此,提出了一种基于改进图注意力网络(Graph attention network v2,GATv2)模型的FDIA检测方法。首先,基于电力系统结构和FDIA的特性,构建模型所需数据集;然后,根据电力系统的拓扑信息和运行信息建立图数据;设计基于GATv2的检测模型对电网图数据的空间特征进行提取,进而检测注入的虚假数据攻击;最后,在IEEE 14节点和IEEE 118节点系统上验证了GATv2模型的有效性,且仿真结果表明GATv2模型检测性能优于其他模型,检测准确率达到98%以上,在不同攻击节点数和不同攻击强度情况中都具有较好的鲁棒性。

罂粟碱注射液联合重组牛碱性成纤维细胞生长因子治疗深度烧伤残余创面的临床研究

目的观察罂粟碱注射液联合重组牛碱性成纤维细胞生长因子(rb-bFGF)治疗深度烧伤残余创面的临床疗效。方法回顾性选取2019年1月至2023年6月入中国人民解放军联勤保障部队第九一〇医院治疗的深度烧伤患者80例作为研究对象,参考用药不同分为联合用药组(n=40)与单独用药组(n=40)。联合用药组采用rb-bFGF与罂粟碱注射液联合治疗,于5 cm×5 cm无菌纱布上涂抹300 IU/cm^(2)rb-bFGF之后将其于创面上覆盖,每日换药1次,肌肉注射罂粟碱注射液每日30 mg,每日2次。单独用药组单用rb-bFGF,用法同联合用药组。两组均持续治疗14 d。比较两组患者的治疗前及治疗后14 d的血清炎症因子[肿瘤坏死因子-α(TNF-α)、白细胞介素(IL)-10、IL-6、IL-4、IL-1β]水平,治疗后3、7、10、14 d的创面分泌物评分和创缘反应评分,创面愈合时间,总有效率及不良反应发生率。结果联合用药组患者治疗后14 d的血清TNF-α、IL-6、L-1β水平分别为(65.27±8.77)、(105.21±9.14)、(20.21±1.18)μg/L,均明显低于单独用药组[(89.26±9.32)、(128.32±8.21)、(29.36±1.28)μg/L],IL-10、IL-4水平分别为(537.75±22.92)、(162.42±17.79)μg/L,均明显高于单独用药组[(497.41±22.63)、(137.27±17.41)μg/L],差异均有统计学意义(P<0.05)。联合用药组患者治疗后3、7、10、14 d创面分泌物评分分别为(1.64±0.25)、(0.97±0.24)、(0.78±0.20)、(0.38±0.11)分,均低于单独用药组[(1.82±0.29)、(1.28±0.26)、(1.04±0.24)、(0.65±0.14)分],差异均有统计学意义(P<0.05)。联合用药组患者治疗后3、7、10、14 d创缘反应评分分别为(0.82±0.13)、(0.39±0.09)、(0.20±0.04)、(0.04±0.02)分,均低于单独用药组[(1.19±0.21)、(0.68±0.11)、(0.49±0.10)、(0.21±0.04)分],差异均有统计学意义(P<0.05)。联合用药组患者治疗后创面愈合时间为(22.84±3.02)d,明显短于单独用药组[(27.94±3.14)d],差异有统计学意义(P<0.05)。联合用药组患者的治疗后总有效率为97.50%,明显高于单独用药组(80.00%),差异有统计学意义(P<0.05)。两组均未发生皮肤刺痛及红痒等不良反应。结论深度烧伤残余创面治疗中,与单用rb-bFGF治疗相比,罂粟碱注射液联合rb-bFGF的临床疗效明显提高,可进一步减轻炎症反应,加速创面愈合,且无明显不良反应。

深沟球轴承喷油润滑搅油损失研究

为了揭示喷油润滑时深沟球轴承搅油损失随喷油润滑条件的变化,提高齿轮箱综合传动系统的性能,建立深沟球轴承喷油润滑下的数值计算模型,并用SKF模型进行验证。采用数值模拟和设计正交方案的方法研究喷油润滑时深沟球轴承内部流场运动状态,以及在不同工况参数下深沟球轴承喷油润滑的搅油损失,并通过极差分析和方差分析确定各个因素对轴承搅油损失的影响程度。研究表明:在喷油润滑过程中,外圈表面润滑油体积分数随着润滑油的进入不断提高,并且逐渐趋于均匀稳定,而内圈表面润滑油体积分数则始终很低;喷嘴角度对轴承内部润滑和搅油功率损失影响很大,当喷嘴朝向外圈时,搅油力矩最小,但润滑性能较差,当喷嘴朝向内圈时,润滑性能最好,但搅油力矩稍大;各个因素对轴承搅油损失影响由大到小顺序为节圆直径、转速、喷油压力、喷嘴直径、温度。研究结果对探究深沟球轴承喷油润滑搅油机制和提升车辆传动效率提供了重要的设计和理论参考。