基于SPIKES沟通模式的病情告知在安宁疗护中的应用研究

目的探讨基于SPIKES沟通模式的病情告知在安宁疗护工作中对患者正性、负性情绪及死亡态度的影响。方法选取某三级甲等综合医院2019年2月-12月收治住院的肿瘤临终患者49例为对照组,2020年1月-2020年11月收治住院的肿瘤临终患者46例为观察组。对照组患者予以常规的病情告知,观察组采用基于SPIKES沟通模式的病情告知。比较两组患者的正性、负性情绪及死亡态度。结果实行病情告知措施前两组患者的正性、负性情绪及死亡态度评分比较差异无统计学意义(p>0.05);实行病情告知后观察组患者负性情绪评分明显低于对照组(p<0.05),观察组患者在自然接受、趋近接受2个维度评分高于对照组,死亡恐惧及死亡逃避2个维度评分低于对照组,且差异有统计学意义(p<0.05)。结论基于SPIKES沟通模式的病情告知,可以缓解临终患者的负性情绪,降低其对死亡的恐惧、能自然接纳死亡,对安宁疗护工作的顺利开展起到积极作用。

SPIKES沟通模型在年轻乳腺癌患者病情告知中的应用

近年来,年轻乳腺癌患者疾速递增,约占女性罹患肿瘤的26%,成为年轻女性中死亡率增长最快的癌症之一[1]。癌患者得知病情后容易陷入恐惧和悲观中,影响预后[2],如何将坏消息告诉患者,针对癌症患者制定具有人性化和无害化的告知策略和方式,减少对其不利影响,成为医务人员需要思考的重要问题。

医患沟通:SPIKES模型探讨医疗坏消息告知策略

告知医疗坏消息是医患沟通的重要内容之一,也是临床实践过程中必不可少的环节。本文通过概述告知医疗坏消息的重要性,提出告知六步走策略:SPIKES模型,旨在提供一个系统而简易的沟通策略,从而解决医疗告知中的难题。这不仅有利于增强医生医疗实践的信心,也有利于提高患者在困难情况下积极的治疗效果与专业满意度,进而有利于构建和谐医患关系。

Survival of the biocontrol agents Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116 on the spikes of barley in the field

Fusarium head blight (FHB) caused by Fusarium graminearum is a devastating disease that results in extensive yield losses to wheat and barley. A green fluorescent protein (GFP) expressing plasmid pRP22-GFP was constructed for monitoring the colonization of two biocontrol agents, Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116, on the spikes of barley and their effect on suppression of FHB. Survival and colonization of the Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116 strains on spikes of barley were observed by tracking the bacterial transformants with GFP expression. Our field study revealed that plasmid pRP22-GFP was stably maintained in the bacterial strains without selective pressure. The retrieved GFP-tagged strains showed that the bacterial population fluctuation accorded with that of the rain events. Furthermore, both biocontrol strains gave significant protection against FHB on spikes of barley in fields. The greater suppression of barley FHB disease was resulted from the treat-ment of barley spikes with biocontrol agents before inoculation with F. graminearum.

Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states

Epileptic seizures are known for their unpredictable nature.However,recent research provides that the transition to seizure event is not random but the result of evidence accumulations.Therefore,a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients.Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes,spikes,and the amplitude.In this study,spike rate is used as the indicator to anticipate seizures in electroencephalogram(EEG) signal.Spikes detection step is used in EEG signal during interictal,preictal,and ictal periods followed by a mean filter to smooth the spike number.The maximum spike rate in interictal periods is used as an indicator to predict seizures.When the spike number in the preictal period exceeds the threshold,an alarm is triggered.Using the CHB-MIT database,the proposed approach has ensured92% accuracy in seizure prediction for all patients.

Finite-thickness effect of the fluids on bubbles and spikes in Richtmyer–Meshkov instability for arbitrary Atwood numbers

This paper investigates the finite-thickness effect of two superimposed fluids on bubbles and spikes in Richtmyer–Meshkov instability(RMI) for arbitrary Atwood numbers by using the method of the small parameter expansion up to the second order. When the thickness of the two fluids tends to be infinity, our results can reproduce the classical results where RMI happens at the interface separating two semi-infinity-thickness fluids of different densities. It is found that the thickness has a large influence on the amplitude evolution of bubbles and spikes compared with those in classical RMI. Based on the thickness relationship of the two fluids, the thickness effect on bubbles and spikes for four cases is discussed. The thickness encourages(or reduces)the growth of bubbles or spikes, depending on not only Atwood number, but also the relationship of the thickness ratio of the heavy and light fluids, which is explicitly determined in this paper.

Automatic spikes detection in seismogram

Data processing for seismic network is very complex and fussy,because a lot of data is recorded in seismicnetwork every day,which make it impossible to process these data all by manual work.Therefore,seismic datashould be processed automatically to produce a initial results about events detection and location.Afterwards,these results are reviewed and modified by analyst.In automatic processing data quality checking is important.There are three main problem data that exist in real seismic records,which include:spike,repeated data and

Clinical and electroencephalogram characteristics and treatment outcomes in children with benign epilepsy and centrotemporal spikes

BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients’intellectual development and quality of life.Electroencephalograms(EEG)can predict an accelerated decline in cognitive function.AIM To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children.METHODS A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected.Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed,and children’s intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale.RESULTS EEG showed that the discharge proportion in the awake and sleep periods was 66.04%,and the peak/peak discharge was mainly single-sided,accounting for 81.13%,while the discharge generalization accounted for 31.13%.There was no significant difference in any of these variables between sexes and ages(P>0.05).The proportion of patients with early onset(<5 years old)and seizure frequency>3 times/half a year was 40.00%and 60.00%,respectively;the incidence rate and seizure frequency in the younger age group(<5 years old)were significantly higher than those in the treatment-effective group(P<0.05),while the discharge index was significantly lower than that in the treatment-effective group(P<0.05).The discharge index was negatively correlated with fine motor skill and language development(r=-0.274 and-0.247,respectively;P<0.05),but not with the rest(P>0.05).Logistic regression analysis showed that low age onset(<5 years old)and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children(odds ratio=11.304 and 5.784,respectively;P<0.05).The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group(P<0.05).However,there was no significant difference between groups after treatment in gross and fine motor skills,adaptability,language,and personal social development(P>0.05).CONCLUSION The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes,and the therapeutic effect is influenced by age of onset and attack frequency.

Ultrasonic Rangefinder Spikes Rejection Using Discrete Wavelet Transform: Application to UAV

This paper presents a spikes removing methodology for ultrasonic rangefinders with an application to a quadrotor unmanned aerial vehicle. Ultrasonic sensors suffer from spikes in distance measurements due to specular reflectance and acoustic noise. Removing these spikes is necessary for improving the hovering performance of the quadrotor. The spikes removing algorithm is based on the discrete wavelet transform. The algorithm is implemented in simulation to study the effect of the altitude measurement spikes on the control performance of the quadrotor with and without the algorithm. The algorithm is also implemented digitally on ultrasonic measurements from a real flight. Results show that the method is capable of rejecting the spikes in the measurements efficiently leaving the altitude control signal unaffected.

Eighty Cases of Heel Bone Spikes Treated With Little Needle-Knife

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Microwave Millisecond Spikes on July 30, 1997

The characteristics of the millisecond spikes with short durations and weak flux densities which were observed with high time resolution (1 ms) during a great type Ⅳ solar radio burst of 1990 July 30 are introduced. The time profiles of the spikes are statistically analyzed and the parameters of the spike source are also estimated.

2019 Spikes Asia策略和实效类奖项Tangrams Awards评委主席群专访 创意之外看实效

Tangrams奖前身为亚洲营销实效和策略奖,如今为亚洲顶尖创意奖(Spikes Asia Awards)下设的一个主要奖项,包括实效类、媒介策略类、数字策略类、大数据和分析以及电子商务类几个类别。作为亚太区最大规模的策略和实效类奖项,Tangrams表彰的是活动作品中所展现的先进营销实效思维,以及最出色的有效品牌构建和稳健的商业转化结果,在创意卓越之外,又为行业提供了营销策略和实效方面的基准。

Diffusion Process of High Concentration Spikes in a Quasi-Homogeneous Turbulent Flow

When a mass spreads in a turbulent flow, areas with obviously high concentration of the mass compared with surrounding areas are formed by organized structures of turbulence. In this study, we extract the high concentration areas and investigate their diffusion process. For this purpose, a combination of Planar Laser Induced Fluorescence (PLIF) and Particle Image Velocimetry (PIV) techniques was employed to obtain simultaneously the two fields of the concentration of injected dye and of the velocity in a water turbulent channel flow. With focusing on a quasi-homogeneous turbulence in the channel central region, a series of PLIF and PIV images were acquired at several different downstream positions. We applied a conditional sampling technique to the PLIF images to extract the high concentration areas, or spikes, and calculated the conditional-averaged statistics of the extracted areas such as length scale, mean concentration, and turbulent diffusion coefficient. We found that the averaged length scale was constant with downstream distance from the diffusion source and was smaller than integral scale of the turbulent eddies. The spanwise distribution of the mean concentration was basically Gaussian, and the spanwise width of the spikes increased linearly with downstream distance from the diffusion source. Moreover, the turbulent diffusion coefficient was found to increase in proportion to the spanwise distance from the source. These results reveal aspects different from those of regular mass diffusion and let us conclude that the diffusion process of the spikes differs from that of regular mass diffusion.

Extracting Epileptic Feature Spikes Using Independent Component Analysis

In recent years, blind source separation （BSS） by independent component analysis （ICA） has been drawing much attention because of its potential applications in signal processing such as in speech recognition systems, telecommunication and medical signal processing. In this paper, two algorithms of independent component analysis （fixed-point IC,4 and natural gradient-flexible ICA） are adopted to extract human epileptic feature spikes from interferential signals. Experiment results show that epileptic spikes can be extracted from noise successfully. The kurtosis of the epileptic component signal separated is much better than that of other noisy signals. It shows that ICA is an effective tool to extract epileptic spikes from patients＇ electroencephalogram EEG and shows promising application to assist physicians to diagnose epilepsy and estimate the epileptogenic region in clinic.

Analysis of High Concentration Spikes Appearing in Mass Plume in Nearly Homogeneous Turbulent Flow Based on the PDF Transport Equation

To evaluate the pollutant dispersion in background turbulent flows, most researches focus on statistical variation of concentrations or its fluctuations. However, those time-averaged quantities may be insufficient for risk assessment, because there emerge many high-intensity pollutant areas in the instantaneous concentration field. In this study, we tried to estimate the frequency of appearance of the high concentration areas in a turbulent flow based on the Probability Density Function (PDF) of concentration. The high concentration area was recognized by two conditions based on the concentration and the concentration gradient values. We considered that the estimation equation for the frequency of appearance of the recognized areas consisted of two terms based on each condition. In order to represent the two terms with physical quantities of velocity and concentration fields, simultaneous PIV (Particle Image Velocimetry) and PLIF (Planar Laser-Induced Fluorescence) measurement and PLIF time-serial measurement were performed in a quasi-homogeneous turbulent flow. According to the experimental results, one of the terms, related to the condition of the concentration, was found to be represented by the concentration PDF, while the other term, by the streamwise mean velocity and the integral length scale of the turbulent flow. Based on the results, we developed an estimation equation including the concentration PDF and the flow features of mean velocity and integral scale of turbulence. In the area where the concentration PDF was a Gaussian one, the difference between the frequencies of appearance estimated by the equation and calculated from the experimental data was within 25%, which showed good accuracy of our proposed estimation equation. Therefore, our proposed equation is feasible for estimating the frequency of appearance of high concentration areas in a limited area in turbulent mass diffusion.

2019年Spikes Asia聚焦品牌目的 亚太区品牌主如何成为改变代言人

近几年,品牌纷纷在社会问题上表明立场。最勇敢的国际品牌和广告公司所做的创意作品,都激发着行为、多样化人群结构、政策法规以及保护地球方式上的改变。91%的千禧一代会选择那些支持社会事业的品牌。为此,亚洲的创意作品应该去迎合新一代消费者的这项需求。品牌应更多地在社会、政治和环境问题上做出道德指引。设立明确的目标、接受'改变代言人'这个新角色.

这条路上,有热爱的形状——2019戛纳幼狮中国区选拔赛暨2019 Young Spikes青年赛中国区选拔赛纪实

“很多人调侃自己是‘广告狗’,但是我不觉得,我觉得做广告非常嗨。”完成2019戛纳幼狮中国区选拔赛暨2019 Young Spikes青年赛中国区选拔赛(以下简称“选拔赛”)评审工作后,其中一位评委在“伯乐大讲堂”对所有的选手说出了这番话,希望用自己的经历激励大家在今后的广告事业中不忘初心、保持热爱,这也是选拔赛评审团“黄金天团”、选拔赛独家赞助商REDS,以及选拔赛主办方《现代广告》对所有选手的一致期许。

An algorithm for automatic identification of multiple developmental stages of rice spikes based on improved Faster R-CNN

Spike development directly affects the yield and quality of rice. We describe an algorithm for automatically identifying multiple developmental stages of rice spikes(AI-MDSRS) that transforms the automatic identification of multiple developmental stages of rice spikes into the detection of rice spikes of diverse maturity levels. The scales vary greatly in different growth and development stages because rice spikes are dense and small, posing challenges for their effective and accurate detection. We describe a rice spike detection model based on an improved faster regions with convolutional neural network(Faster R-CNN).The model incorporates the following optimization strategies: first, Inception_Res Net-v2 replaces VGG16 as a feature extraction network;second, a feature pyramid network(FPN) replaces single-scale feature maps to fuse with region proposal network(RPN);third, region of interest(Ro I) alignment replaces Ro I pooling, and distance-intersection over union(DIo U) is used as a standard for non-maximum suppression(NMS). The performance of the proposed model was compared with that of the original Faster R-CNN and YOLOv4 models. The mean average precision(m AP) of the rice spike detection model was92.47%, a substantial improvement on the original Faster R-CNN model(with 40.96% m AP) and 3.4%higher than that of the YOLOv4 model, experimentally indicating that the model is more accurate and reliable. The identification results of the model for the heading–flowering, milky maturity, and full maturity stages were within two days of the results of manual observation, fully meeting the needs of agricultural activities.