Short Period Logistics Integrating: a Model for Vendors'Evaluating and Selecting

Vendors’Evaluating and Selecting is one study focu s in SCM and VMO. It is one of the very important operations management and can ad vance to implement the strategic aims. With the increase in use of total quality management and just-in-time concepts by a wide range of firms, the vendor sel ection question has become extremely important. It is necessary for firms to tak e part in the global competition and global manufacture. There are some decision -making techniques which can be used for evaluating and selecting vendors, such as weighting point methods, utility theary, multi-objective programming, analy tic hierarchy process, vendor profile analysis, and so on. Analytic Hierarchy Pr ocess(AHP) is a technique in common use for quantifying the problem. Since AHP i s put forward in 1973 by Satty, it has been accepted. However, this technique ha s its shortcomings, and one of them is that distributing weights is subjective. In recent years,some scholars prove that it is defferent from factual doing usin g subjective ways for vendors’ evaluating and selecting. In fact, the methods f or vendors’evaluating and selecting should be given by practical circs. Today, there’s somebody who has brought forward that it is studied by deviding four ty pes of relationships in view of two major factors: the reference time horizon of the relationship; and the content of the relationship in terms of the nature of the interation between supplier and customer. In the paper, we only consider th e scenario of short-term and logistic intergration brought forward by Cristina and Andrea. In the scenario, we only consider current manufacturing performance. In fact, the scenario is often seen in these developing countries.We bring up a model for grey system analysis on vendors’evaluating and selecting to attempt to expore this problem. The model integrates AHP and the grey system theory and attempt to eliminate the subjective factors in AHP using objective datum. Moreov er, it is based on the feature of data insufficiency and uncertainty and sample information of abnormality in system data.So,it overcomes the issues of deficien t information and absent data(it is often seen in management).

Assessment of Physico-Chemical and Microbial Quality of Sugarcane Juice Sold by Street Vendors in Three Regions of Bangladesh

Sugar cane juice is a popular refreshing drink in most part of Bangladesh. It has great taste and health benefits;also it is available most of the public places at reasonable prices which consumed by road side customers including general public, shopping personals, tourists, students. In our country, street vendors crushing sugarcane between roller crusher and sold without any heat treatment or preservative, also served with or without added ice and lemon juice. The study aimed to identify and compare the physico-chemical and microbial quality of sugarcane juice. The chemical qualities of juices including moisture, PH, ash, total soluble solid, total sugar, reducing sugar and titrable acidity were found slightly different in Mymensingh, Gazipur and Narayangonj areas. The highest and lowest value of moisture, ash, PH, total soluble solids, total sugar, reducing sugar and titrable acidity were found in 84.33% - 79.26% (Gazipur-Mymensingh), 0.57% - 0.04% (Mymensingh-Gazipur), 5.9 - 2.9 (Gazipur-Narayangonj), 17.48% - 4.98% (Mymensingh-Narayangonj), 21.9% - 6.56% (Mymensingh-Gazipur), 3.7 - 2.1 (Gazipur-Mymensingh) and 0.523% - 0.007% (Narayangonj-Gazipur) respectively. For microbiological analysis, the total viable count of sugar cane juice in Mymensingh, Gazipur and Narayangonj were ranged from 0.6 × 105 - 43.6 × 105 cfu/ml, 4.6 × 105 - 21.6 × 105 cfu/ml and 3.6 × 105 - 36.6 × 105 cfu/ml respectively, where the permitted value is 1.0 × 104 cfu/ml, whereas the total coliform count was ranged from 0.4 × 105 - 6.4 × 105 cfu/ml, 0.6 × 105 - 8.4 × 105 cfu/ml and 0.00 - 8.4 × 105 cfu/ml, where the permitted value is 100 cfu/ml and total fungal count was ranged from 5.5 × 105 - 56.5 × 105 cfu/ml, 21.5 × 105 - 54.5 × 105 cfu/ml and 32.5 × 105 - 68.5 × 105 cfu/ml, where the permitted value is 1000 cfu/ml. According to the Gulf standard, the microbiological parameters of all the collected sugar cane juice were out of the permitted standards, so that a serious health outbreak can be caused anytime.

On Evaluating University Teachers’ Morality and Ethics in the New Era

University teachers play an important role in promoting moral and political education among university students.Regular and long-term construction of teachers’morality and ethics will contribute to the success of the fundamental task of cultivating talents.The present study proposes that due to the multiple identities of university teachers,it is necessary to evaluate the construction of teachers’morality and ethics in terms of what to evaluate and how to evaluate?It is expected that the attempt will provide useful guidance for the construction of university teachers’morality and ethics.

High Prevalence of Musculoskeletal Disorders and Self-Medication among Street Vendors in Bangui, Central African Republic (CAR)

Introduction: Musculoskeletal disorders (MSDs) are a set of peri-articular conditions that result mainly in pain and functional discomfort. They represent a major occupational health problem in all areas of activity. The objective of this work was to determine the prevalence of MSDs among street vendors in the city of Bangui in the Central African Republic (CAR). Methods: A cross-sectional study was conducted from September 01 to October 31, 2021 in Bangui, the capital of CAR. The study population consisted of street vendors which were included at the entrance of 4 large markets of Bangui after giving informed consent. The sample size, calculated according to the Schwartz formula, was 384. Sociodemographic data (age, gender, level of education, marital status), professional data (the duration of sale in hours, the distance traveled per day);and health data (the health problems suffered by itinerant sellers and the means of dealing with them) were collected using a pre-established self-questionnaire. This collected data was processed using Microsoft Excel 2013 and Epi-Info version 7 software. Results: Among 384 street vendors included, women represented a quarter (24.9%). The average age was 27 years;the 25-34 age group was the most represented (50%). About two-thirds (64.8%) sold for at least 12 hours and traveled more than 10 km (69.3%) per day. The main health problems reported by street vendors were musculoskeletal disorders (95.8%). Their locations concerned the upper limbs shoulder 65.36% (251), elbow 24.22% (93). Non-ergonomic postures that stress the back and joints all day long, causing pain are risk factors for MSDs. These MSDs were treated by self-medication with non-steroidal anti-inflammatory drugs (22.0%), mainly sold on the street. Conclusion: MSDs dominated the health problems of street vendors. These problems raise the need for recognition and support for these workers to optimize their performance while preserving their health through awareness and good management of MSDs whose chronicity generates a disability.

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Evaluating grant proposals:lessons from using metrics as screening device

Purpose:This study examines the effects of using publication-based metrics for the initial screening in the application process for a project leader.The key questions are whether formal policy affects the allocation of funds to researchers with a better publication record and how the previous academic performance of principal investigators is related to future project results.Design/methodology/approach:We compared two competitions,before and after the policy raised the publication threshold for the principal investigators.We analyzed 9,167 papers published by 332 winners in physics and the social sciences and humanities(SSH),and 11,253 publications resulting from each funded project.Findings:We found that among physicists,even in the first period,grants tended to be allocated to prolific authors publishing in high-quality journals.In contrast,the SSH project grantees had been less prolific in publishing internationally in both periods;however,in the second period,the selection of grant recipients yielded better results regarding awarding grants to more productive authors in terms of the quantity and quality of publications.There was no evidence that this better selection of grant recipients resulted in better publication records during grant realization.Originality:This study contributes to the discussion of formal policies that rely on metrics for the evaluation of grant proposals.The Russian case shows that such policy may have a profound effect on changing the supply side of applicants,especially in disciplines that are less suitable for metric-based evaluations.In spite of the criticism given to metrics,they might be a useful additional instrument in academic systems where professional expertise is corrupted and prevents allocation of funds to prolific researchers.

Evaluating Parameterizations for Turbulent Fluxes over the Landfast Sea-Ice Surface in Prydz Bay, Antarctica

It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).

Method for Evaluating Bolt Competitive Failure Life Under Composite Excitation

In this study,the competitive failure mechanism of bolt loosening and fatigue is elucidated via competitive failure tests on bolts under composite excitation.Based on the competitive failure mechanism,the mode prediction model and“load ratio-life prediction curve”(ξ-N curve)of the bolt competitive failure are established.Given the poor correlation of theξ-N curve,an evaluation model of the bolt competitive failure life is proposed based on Miner’s linear damage accumulation theory.Based on the force analysis of the thread surface and simulation of the bolt connection under composite excitation,a theoretical equation of the bolt competitive failure life is established to validate the model for evaluating the bolt competitive failure life.The results reveal that the proposed model can accurately predict the competitive failure life of bolts under composite excitation,and thereby,it can provide guidance to engineering applications.

Evaluating the weekly changes in terrestrial water storage estimated by two different inversion strategies in the Amazon River Basin

In this study,we estimated the weekly Gravity Recovery and Climate Experiment(GRACE)spherical harmonic(SH)solutions and regional mascon solutions using GRACE-based Geopotential Difference(GPD)data and investigated their abilities in retrieving terrestrial water storage(TWS)changes over the Amazon River Basin(ARB)from January 2003 to February 2013.The performance of the weekly GPD-SH and GPDmascon solutions was evaluated by comparing them with the weekly GFZ-SH solutions,Global Land Data Assimilation Systems(GLDAS)-NOAH hydrological model outputs,and monthly GFZ-SH,GPD-SH,and CSRmascon solutions in the spatio-temporal and spectral domains.The results demonstrate that the weekly GPD-SH and GPD-mascon present good consistency with the weekly GFZ-SH solutions and GLDAS-NOAH estimates in the spatio-temporal domains,but GPD-mascon presents stronger signal amplitudes and more spatial details.The comparison of the monthly average of weekly estimates and monthly solutions demonstrates that the weekly GPD-mascon and GFZ-SH with DDK1 filtering are close to the monthly CSRmascon and GFZ-SH solutions,respectively.However,the signal amplitudes of TWS changes from GPD-SH and GFZ-SH with 650 km Gaussian filtering are smaller than the monthly solutions,and the corresponding Root Mean Square Errors between the TWS change time series from the monthly average of weekly solutions and monthly estimates are 18.12 mm(GPD-mascon),18.81 mm(GFZ-SH-DDK1),24.93 mm(GPDSH-G650km),and 33.07 mm(GFZ-SH-G650km),respectively.Additionally,the TWS change time series derived from weekly solutions present more high-frequency time-varying information than monthly solutions.Furthermore,the 300 km Gaussian filtering can improve the signal amplitudes of TWS changes from the weekly GPD-SH solutions more than those with 650 km Gaussian filtering,but the corresponding noise level is higher.The weekly GPD-SH and GPD-mascon solutions can extend the application scopes of GRACE and provide good complements to the current GRACE monthly solutions.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.

A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

Machine learning in metal-ion battery research: Advancing material prediction, characterization, and status evaluation

Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.

Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

Benchmark experiment on slab^(238)U with D-T neutrons for validation of evaluated nuclear data

A benchmark experiment on^(238)U slab samples was conducted using a deuterium-tritium neutron source at the China Institute of Atomic Energy.The leakage neutron spectra within energy levels of 0.8-16 MeV at 60°and 120°were measured using the time-of-flight method.The samples were prepared as rectangular slabs with a 30 cm square base and thicknesses of 3,6,and 9 cm.The leakage neutron spectra were also calculated using the MCNP-4C program based on the latest evaluated files of^(238)U evaluated neutron data from CENDL-3.2,ENDF/B-Ⅷ.0,JENDL-5.0,and JEFF-3.3.Based on the comparison,the deficiencies and improvements in^(238)U evaluated nuclear data were analyzed.The results showed the following.(1)The calculated results for CENDL-3.2 significantly overestimated the measurements in the energy interval of elastic scattering at 60°and 120°.(2)The calculated results of CENDL-3.2 overestimated the measurements in the energy interval of inelastic scattering at 120°.(3)The calculated results for CENDL-3.2 significantly overestimated the measurements in the 3-8.5 MeV energy interval at 60°and 120°.(4)The calculated results with JENDL-5.0 were generally consistent with the measurement results.

Unequal Distribution of Innovation Efforts for Neglected Tropical Diseases: The Role of Funding Evaluation Criteria

Background: International research and innovation efforts for neglected tropical diseases have increased in recent decades due to disparities in overall health research funding in relation to global burden of disease. However, within the field of neglected tropical diseases some seem far more neglected than others. In this research the aim is to investigate the distribution of resources and efforts, as well as the mechanisms that underpin funding allocation for neglected tropical diseases. Methodology: A systematic literature review was conducted to establish a comprehensive overview of known indicators for innovation efforts related to a wide range of neglected tropical diseases. Articles were selected based on a subjective evaluation of their relevance, the presence of original data, and the breadth of their scope. This was followed by thirteen in-depth open-ended interviews with representatives of private, public and philanthropic funding organizations, concerning evaluation criteria for funding research proposals. Results: The findings reveal a large difference in the extent to which the individual diseases are neglected with notable differences between absolute and relative efforts. Criteria used in the evaluation of research proposals relate to potential impact, the probability of success and strategic fit. Private organizations prioritize strategic fit and economic impact;philanthropic organizations prioritize short-term societal impact;and public generally prioritize the probability of success by accounting for follow-up funding and involvement of industry. Funding decisions of different types of organizations are highly interrelated. Conclusions: This study shows that the evaluation of funding proposals introduces and retains unequal funding distribution, reinforcing the relative neglect of diseases. Societal impact is the primary rationale for funding but application of it as a funding criterion is associated with significant challenges. Furthermore, current application of evaluation criteria leads to a primary focus on short-term impact. Through current practice, the relatively most neglected diseases will remain so, and a long-term strategy is needed to resolve this.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

I-DCGAN and TOPSIS-IFP:A simulation generation model for radiographic flaw detection images in light alloy castings and an algorithm for quality evaluation of generated images

The intelligent detection technology driven by X-ray images and deep learning represents the forefront of advanced techniques and development trends in flaw detection and automated evaluation of light alloy castings.However,the efficacy of deep learning models hinges upon a substantial abundance of flaw samples.The existing research on X-ray image augmentation for flaw detection suffers from shortcomings such as poor diversity of flaw samples and low reliability of quality evaluation.To this end,a novel approach was put forward,which involves the creation of the Interpolation-Deep Convolutional Generative Adversarial Network(I-DCGAN)for flaw detection image generation and a comprehensive evaluation algorithm named TOPSIS-IFP.I-DCGAN enables the generation of high-resolution,diverse simulated images with multiple appearances,achieving an improvement in sample diversity and quality while maintaining a relatively lower computational complexity.TOPSIS-IFP facilitates multi-dimensional quality evaluation,including aspects such as diversity,authenticity,image distribution difference,and image distortion degree.The results indicate that the X-ray radiographic images of magnesium and aluminum alloy castings achieve optimal performance when trained up to the 800th and 600th epochs,respectively.The TOPSIS-IFP value reaches 78.7%and 73.8%similarity to the ideal solution,respectively.Compared to single index evaluation,the TOPSIS-IFP algorithm achieves higher-quality simulated images at the optimal training epoch.This approach successfully mitigates the issue of unreliable quality associated with single index evaluation.The image generation and comprehensive quality evaluation method developed in this paper provides a novel approach for image augmentation in flaw recognition,holding significant importance for enhancing the robustness of subsequent flaw recognition networks.