Effectiveness of Combined Application of Shock Index and Early Warning Scoring System in Patients with Acute Gastrointestinal Hemorrhage

Objective:To explore the effect of the combined application of the Shock Index(SI)and the Early Warning Score(EWS)in patients with acute gastrointestinal bleeding.Methods:Seventy patients with acute gastrointestinal bleeding admitted to a hospital from June 2022 to May 2024 were selected and randomly divided into two groups:the control group and the observation group,with 35 patients in each group.The control group received conventional emergency care measures,while the observation group received SI combined with NEWS emergency care measures.The treatment effects in both groups were compared.Results:The observation group had shorter waiting times for consultation(4.45±1.59 minutes),intravenous access establishment(6.79±2.52 minutes),hemostasis time(4.41±1.52 hours),and hospital stays(8.39±2.13 days)compared to the control group,which had times of 5.46±1.34 minutes,8.41±2.16 minutes,5.16±1.47 hours,and 10.26±2.98 days,respectively.The differences were statistically significant(P<0.05).Before management,there were no significant differences in the levels of hemoglobin,prealbumin,and serum protein between the two groups(P>0.05).However,after systematic emergency management,the serum indexes in both groups significantly improved,with the observation group showing greater improvement than the control group,and these differences were statistically significant(P<0.05).In the observation group,only one case of cardiovascular complications occurred during the rescue period,with an incidence rate of 2.86%.In contrast,the control group experienced eight cases of complications,including hemorrhagic shock,anemia,multi-organ failure,cardiovascular complications,and gastrointestinal rebleeding,with an incidence rate of 22.85%.The difference between the groups was statistically significant(P<0.05).Conclusion:The application of SI combined with EWS emergency care measures in patients with acute gastrointestinal hemorrhage can effectively improve serum indexes,shorten resuscitation time and hospital stay,and reduce the risk of complications such as hemorrhagic shock,anemia,infection,multi-organ failure,cardiovascular complications,acute renal failure,and gastrointestinal rebleeding.This approach has positive clinical application value.

Optimization of the Placement and Size of Photovoltaic Source

This paper presents a new optimization study of the placement and size of a photovoltaic source(PVS)in a distribution grid,based on annual records of meteorological parameters(irradiance,temperature).Based on the recorded data,the production output as well as the daily average power(24-h vector)of the PVS is extracted over the year.When a power vector is available,it can be used as an input when searching for the optimal size of the PVS.This allows to take into account the constraint of the variation of the power generated by this source considering the variation of the power consumed by the electrical loads during the whole day.A multi-objective fitness function has been considered.The latter minimizes the active losses and maximizes the voltage stability index during the day,while considering the constraints of the system,that is,the security,technical,geographical,and meteorological constraints.This problem was solved using the Non-dominated Sorting Genetic Algorithm NSGA-II optimization technique under MATLAB 2021.It was applied to the distribution network of Ghardaïa of 59 nodes.

A Full-Scale Optimization of a Crop Spatial Planting Structure and its Associated Effects

Driven by the concept of agricultural sustainable development,crop planting structure optimization(CPSO)has become an effective measure to reduce regional crop water demand,ensure food security,and protect the environment.However,traditional optimization of crop planting structures often ignores the impact on regional food supply–demand relations and interprovincial food trading.Therefore,using a system analysis concept and taking virtual water output as the connecting point,this study proposes a theoretical CPSO framework based on a multi-aspect and full-scale evaluation index system.To this end,a water footprint(WF)simulation module denoted as soil and water assessment tool–water footprint(SWAT-WF)is constructed to simulate the amount and components of regional crop WFs.A multi-objective spatial CPSO model with the objectives of maximizing the regional economic water productivity(EWP),minimizing the blue water dependency(BWFrate),and minimizing the grey water footprint(GWFgrey)is established to achieve an optimal planting layout.Considering various benefits,a fullscale evaluation index system based on region,province,and country scales is constructed.Through an entropy weight technique for order preference by similarity to an ideal solution(TOPSIS)comprehensive evaluation model,the optimal plan is selected from a variety of CPSO plans.The proposed framework is then verified through a case study of the upper–middle reaches of the Heihe River Basin in Gansu province,China.By combining the theory of virtual water trading with system analysis,the optimal planting structure is found.While sacrificing reasonable regional economic benefits,the optimization of the planting structure significantly improves the regional water resource benefits and ecological benefits at different scales.

Different effects of economic and structural performance indexes on model construction of structural topology optimization

The objective and constraint functions related to structural optimization designs are classified into economic and performance indexes in this paper.The influences of their different roles in model construction of structural topology optimization are also discussed.Furthermore,two structural topology optimization models,optimizing a performance index under the limitation of an economic index,represented by the minimum compliance with a volume constraint（MCVC）model,and optimizing an economic index under the limitation of a performance index,represented by the minimum weight with a displacement constraint（MWDC）model,are presented.Based on a comparison of numerical example results,the conclusions can be summarized as follows：（1）under the same external loading and displacement performance conditions,the results of the MWDC model are almost equal to those of the MCVC model;（2）the MWDC model overcomes the difficulties and shortcomings of the MCVC model;this makes the MWDC model more feasible in model construction;（3）constructing a model of minimizing an economic index under the limitations of performance indexes is better at meeting the needs of practical engineering problems and completely satisfies safety and economic requirements in mechanical engineering,which have remained unchanged since the early days of mechanical engineering.

Dynamic Analysis and Dimensional Synthesis of Easy-to-Protect Large-Load Robot for Extracting Fermented Grains

To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.

An Adaptive Parameter-Free Optimal Number of Market Segments Estimation Algorithm Based on a New Internal Validity Index

An appropriate optimal number of market segments(ONS)estimation is essential for an enterprise to achieve successful market segmentation,but at present,there is a serious lack of attention to this issue in market segmentation.In our study,an independent adaptive ONS estimation method BWCON-NSDK-means++is proposed by integrating a newinternal validity index(IVI)Between-Within-Connectivity(BWCON)and a newstable clustering algorithmNatural-SDK-means++(NSDK-means++)in a novel way.First,to complete the evaluation dimensions of the existing IVIs,we designed a connectivity formula based on the neighbor relationship and proposed the BWCON by integrating the connectivity with other two commonly considered measures of compactness and separation.Then,considering the stability,number of parameters and clustering performance,we proposed the NSDK-means++to participate in the integrationwhere the natural neighbor was used to optimize the initial cluster centers(ICCs)determination strategy in the SDK-means++.At last,to ensure the objectivity of the estimatedONS,we designed a BWCON-based ONS estimation framework that does not require the user to set any parameters in advance and integrated the NSDK-means++into this framework forming a practical ONS estimation tool BWCON-NSDK-means++.The final experimental results showthat the proposed BWCONand NSDK-means++are significantlymore suitable than their respective existing models to participate in the integration for determining theONS,and the proposed BWCON-NSDK-means++is demonstrably superior to the BWCON-KMA,BWCONMBK,BWCON-KM++,BWCON-RKM++,BWCON-SDKM++,BWCON-Single linkage,BWCON-Complete linkage,BWCON-Average linkage and BWCON-Ward linkage in terms of the ONS estimation.Moreover,as an independentmarket segmentation tool,the BWCON-NSDK-means++also outperforms the existing models with respect to the inter-market differentiation and sub-market size.

A modified multi-objective particle swarm optimization approach and its application to the design of a deepwater composite riser

A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multiobjective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid’s area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Paretooptimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effec tively deal with multi-objective optimizations with black-box functions.

Design of Optical Filter Using Bald Eagle Search Optimization Algorithm

Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber.Better working conditions of such machines can be monitored by analyzing its radiations.Various wavelengths such as 656.3,486.1,464.7 nm are quite significant which are used for health monitoring of thermonuclear machines.The optical thinfilmfilters which work on construc-tive and destructive interference are the ideal choices.Thesefilters are multi-layered with a pair of high and low refractive index dielectric materials.Significantly high transmission index at the desired wavelength and relatively low transmission at the other wavelengths are desired.With this as the objective,it is necessary to design thefilter.Various optimization techniques are used for identifying the suitable design of thefilters.To choose the parameter combination that provides the most excellent performance,optimization of the design para-meters is entailed.The goal of this work is to improve the optical bandfilter using the Bald eagle search optimization(BES)method.The ideal design is determined by assessing several characteristics such as thickness,refractive index,Full-Width at Half-Maximum(FWHM),and the impact of choosing optical properties,which increases transmission potential.Initially,an alternate multi-layer stack with 28,30,and 32 layers is created by altering the thickness while keeping the dielectric substances high and low refractive indices constant.By adjusting the thickness of each layer,the BES algorithm achieves the best practical solution.The proposed method is implemented using MATLAB and the outcomes show the efficacy of the proposed technique.The transmittance,reflectance,and FWHM using the pro-posed BES are found to be 99.9356%,0.065%,and 1.2 nm respectively.

Predicting of Power Quality Steady State Index Based on Chaotic Theory Using Least Squares Support Vector Machine

An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.

Effects of fluid flow rate and viscosity on gravel-pack plugging and the optimization of sand-control wells production

Series of experiments were performed to simulate the invasion of formation sand into and the plugging process of gravel-pack at different viscosities and flowing rates of fluid.Two types of formation sands with the medium size of 0.10 mm and 0.16 mm and the quartz sand and ceramsite of 0.6-1.2 mm were used in the experiments.A new viscosity-velocity index(the product of fluid viscosity and velocity)was put forward to characterize the influencing mechanism and law of physical property and flow condition of formation fluid on gravel-pack plugging,and a new method to optimize the production rate of wells controlling sand production with gravel-packing was proposed.The results show that the permeability of formation sand invaded zone and final permeability of plugged gravel-pack have negative correlations with viscosity and flow velocity of fluid,the higher the flow velocity and viscosity,the lower the permeability of formation sand invaded zone and final permeability of plugged gravel-pack will be.The flow velocity and viscosity of fluid are key factors affecting plugging degree of the gravel zone.The viscosity-velocity index(v-v index)can reflect the flow characteristics of fluid very well and make it easier to analyze the plugging mechanism of gravel zone.For different combinations of fluid viscosity and flow velocity,if the v-v index is the same or close,their impact on the final gravel permeability would be the same or close.With the increase of the v-v index,the permeability of plugged gravel zone decreases first,then the reduction rate slows down till the permeability stabilizes.By optimizing production and increasing production step by step,the optimal working scheme for sand-control well can reduce the damage to gravel-pack zone permeability caused by sand-carrying fluid effectively,and increase well productivity and extend the sand control life.

Energy Optimization of the Fin/Rudder Roll Stabilization System Based on the Multi-objective Genetic Algorithm （MOGA）

Energy optimization is one of the key problems for ship roll reduction systems in the last decade. According to the nonlinear characteristics of ship motion, the four degrees of freedom nonlinear model of Fin/Rudder roll stabilization can be established. This paper analyzes energy consumption caused by overcoming the resistance and the yaw, which is added to the fin/rudder roll stabilization system as new performance index. In order to achieve the purpose of the roll reduction, ship course keeping and energy optimization, the self-tuning PID controller based on the multi-objective genetic algorithm （MOGA） method is used to optimize performance index. In addition, random weight coefficient is adopted to build a multi-objective genetic algorithm optimization model. The objective function is improved so that the objective function can be normalized to a constant level. Simulation results showed that the control method based on MOGA, compared with the traditional control method, not only improves the efficiency of roll stabilization and yaw control precision, but also optimizes the energy of the system. The proposed methodology can get a better performance at different sea states.

STUDY ON THE OPTIMIZATION OF TRANSPORT CONTROL POLICY IN COMMUNICATION NETWORK

In communication networks with policy-based Transport Control on-Demand (TCoD) function,the transport control policies play a great impact on the network effectiveness. To evaluate and optimize the transport policies in communication network,a policy-based TCoD network model is given and a comprehensive evaluation index system of the network effectiveness is put forward from both network application and handling mechanism perspectives. A TCoD network prototype system based on Asynchronous Transfer Mode/Multi-Protocol Label Switching (ATM/MPLS) is introduced and some experiments are performed on it. The prototype system is evaluated and analyzed with the comprehensive evaluation index system. The results show that the index system can be used to judge whether the communication network can meet the application requirements or not,and can provide references for the optimization of the transport policies so as to improve the communication network effectiveness.

变负载下柔性系统的改进THEI输入整形器振动抑制

针对高精度运动平台中柔性系统负载改变而导致的固有频率和阻尼比双参数共同变化下输入整形器不敏感性优化问题,提出一种改进双股峰EI(two-hump extra-insensitive,THEI)输入整形器的设计方法,实现在相同滞后时间的前提下改善THEI输入整形器的不敏感性。该改进THEI整形器在正向设计传统THEI输入整形器的基础上,加入对双参数不敏感性的反向优化。首先,利用三维灵敏度曲线推导了用于量化THEI输入整形器双参数不敏感性的评价指标。其次,建立了以幅值调节因子为设计变量的优化脉冲约束下THEI输入整形器双参数不敏感性优化模型;基于蚁群优化(ant colony optimization,ACO)算法求解设计变量,并更新改进THEI输入整形器的脉冲幅值,实现不敏感性最优。最后,数值仿真和试验结果共同验证了所提方法的有效性。

A Proposal on the Novel Method to Estimate Optimal Sleep Duration Based on Self-Reported Survey Data

Background: Many adolescents have a sleep debt. Individuals sleeping for their optimal sleep duration are expected to experience no sleepiness. Then, it is important to recognize one’s optimal sleep duration to reduce sleep debt. However, there is no simple method to determine this value. Since body mass index and sleep duration exhibit a U-shaped association, it is expected that a person taking optimal sleep duration would show no marked deviation from the mean body mass index value for the population evaluated. By using self-reported sleepiness and standardized body mass index, this study aimed to estimate individual optimal sleep duration. Methods: Data from 2540 grade 5 - 11 students were used. Students who declared no sleepiness during class and also had a gender- and grade-standardized body mass index of ±1.5 were termed ideal students. The average sleep durations of ideal students were compared with those of non-ideal students. The differences of sleep duration between ideal and no-ideal students were added to habitual sleep duration of each non-ideal student to obtain assumed optimal sleep duration. A multiple regression line to predict assumed optimal sleep duration was calculated using the least squares method. Results: The mean sleep duration of 666 ideal students exceeded the lower limit of daily sleep duration proposed as “may be appropriate” for children aged 6 - 17 years by National Sleep Foundation of the USA, being longer than those of non-ideal students. Significant regression formula for assumed optimal sleep duration was obtained (adjusted R2 = 0.996, p Conclusions: No contradiction was identified in the sleep duration obtained from ideal students as with optimal sleep duration. Although further studies to confirm the current estimation are needed, a simple formula to estimate individual optimal sleep duration through easily obtainable parameters was proposed.

Optimization of modulation index in optical fiber gas sensors using wavelength modulation spectroscopy

ＯｐｔｉｍｉｚａｔｉｏｎｏｆｍｏｄｕｌａｔｉｏｎｉｎｄｅｘｉｎｏｐｔｉｃａｌｆｉｂｅｒｇａｓｓｅｎｓｏｒｓｕｓｉｎｇｗａｖｅｌｅｎｇｔｈｍｏｄｕｌａｔｉｏｎｓｐｅｃｔｒｏｓｃｏｐｙＷｅｉＪｉｎ（Ｄｅｐｔ．ｏｆＥｌｅｃｔｒ．Ｅｎｇ．，ＨｏｎｇＫｏｎｇＰ...

基于改进Theil指数和Shift-Share模型的2012—2021年中国产业偏离分析

文章首先通过对现有文献的梳理和分析,发现针对产业偏离的测算,传统的产业偏离度E系数、Theil指数及Shift-Share模型均存在一定的缺陷,E系数和Theil指数的缺陷主要体现在计算原理方面,而Shift-Share模型的缺陷主要表现在参照系选择的合理性和数据采集的可行性方面。然后,基于现有模型的基本原理,提出了更为合理和更具可操作性的产业偏离测算方法,再采用实证研究的方法,根据2012—2021年的数据,对中国的产业偏离情况进行具体分析,得出尽管中国存在产业偏离,但产业偏离度在逐渐减小。最后,基于修正模型的计算结果,并结合当前的国际国内环境,提出如下政策建议:1)第一产业要依靠创新和科技引领,促进农村劳动力在城乡间有序转移,实现农业生产的规模化和现代化;2)第二产业要加快产业的升级换代,建立和保持独立、自主、完整的工业体系,加大在基础研究方面的投入,尽早突破美西方的技术封锁;3)第三产业的发展重点应该在金融和科教两个方面,要进一步提升香港地区、上海和北京等城市的世界金融中心地位,依靠金融创新来规避现行国际金融体系的不利约束和影响,同时要将科教兴国战略落到实处,努力探索适合中国国情的从小学到大学各阶段的教育模式。

Optimized Adsorption of Small and Medium Molecules by a Biosorbent Based on Hevea Hulls

In the context of the recovery of agricultural waste, many researches have focused on the preparation of adsorbents from natural waste from fruit trees, egg shells, palm waste or sawdust. This work aims to optimize the preparation of a biosorbent from rubber hulls by studying its ability to adsorb small and medium molecules. The influence of parameters such as drying temperature (X1), particle size (X2), stirring time (X3) and sodium hypochloride mass (X4) was studied. The results indicate that the model used for biosorbent optimization on methylene blue and iodine index is significant. In addition, this model has greater adsorption capabilities on small molecules than with large molecules. Statistical analysis of the data shows that temperature is the most influential factor in the adsorption of small molecules. On the other hand, particle size has a significant influence on the adsorption of large molecules. The optimum biosorbent preparation values are 1.0 for drying temperature (X1), −1.0 for biosorbent grain size (X2), 1.0 for stirring time (X3) and 1.0 for sodium hypochloride mass (X4).

Optimization Analysis on Comprehensive Evaluation Index of Wetland Parks

Wetland park is an important mode of wetland protection, meanwhile, construction of comprehensive index system has become the hotspot and keystone of the researches on Wetland Parks. Basing on different development stages, this paper firstly divided the Wetland Parks into three categories, including the start-up stage, the development stage and the refinement stage. And then screened and identified the direction and keypoints of comprehensive evaluation for wetland parks in different development stages using expert scoring, questionnaire and analytic hierarchy process(AHP).

Optimal Hedging Strategies of Stock Index Futures Based on the Perspective of Information Asymmetry

Based on two different risk measurement criteria, this article studied the optimal hedging strategies of stock index futures in the case of asymmetric information, and discussed the influence of insider information on the hedging effect. Through simulation analysis, it can be shown that hedging people with insider information can save hedging costs to a certain extent, which also explains the reason why investors try to obtain corporate information in actual investment activities.

Using Narrow Line-Width Laser to Measure the Thickness and Refractive Index of the Film

We demonstrate applications of a novel setup which is used for measuring the relative phase difference between S and P polarization at an oblique incidence point in optically denser medium by analyzing the relative frequency shift of adjacent axial modes of S and P resonances of a monolithic folded Fabry-Perot cavity (MFC). The relative phase difference at a reflection point A in an optically denser medium is inferred to be around -167.4° for a confocal cavity and -201.1° for a parallel cavity. Given the n1, n3, φ1, φ3, λ, and Δ, the elliptic formula tan(ψ)exp(iΔ) = Rp/Rs is used to find a solution for thickness d and refractive index n2 of the thin film coated on point A, where Rs and Rp are total refractive index of s and p component of light related to two unknown values. Since it is hard to deduce an analytical solution for thickness and refractive index of the film, we firstly used exhaustion method to find the set of solution about thickness and refractive index when assumed there is no light absorption by the film and then Particle Swarm Optimization (PSO) to find a set of solution of thickness and complex refractive index which accounts the light absorption by the film.